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Topical Collection "Proteins and Protein-Ligand Interactions"

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A topical collection in International Journal of Molecular Sciences (ISSN 1422-0067). This collection belongs to the section "Biochemistry, Molecular Biology and Biophysics".

Editors

Collection Editor
Dr. Tatyana Karabencheva-Christova

Faculty of Health and Life Sciences, Department of Applied Sciences, Northumbria University, UK
Website | E-Mail
Interests: computational chemical biology; enzyme mechanisms; catalytic activity and inhibition; computer-aided drug design; conformational dynamics of proteins and nucleic acids; biomolecular spectroscopy; bioinorganic enzymology
Collection Editor
Dr. Christo Z. Christov

Senior Lecturer in Computational Biochemistry Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University Ellison Building, Newcastle-upon-Tyne, NE1 8ST, UK
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Fax: +44 191 227 3519
Interests: computational biomolecular science; enzyme mechanisms; protein conformational dynamics; biomolecular spectroscopy; combined quantum mechanical and molecular mechanical methods (QM/MM); quantum chemistry; molecular dynamics; protein-ligands interactions; bioinorganic electronic structure and mechanisms

Topical Collection Information

Dear Colleagues,

Proteins are biopolymers present in all living cells/organisms that take part in basically all processes in life by exerting extremely broad functional versatility such us structural, catalytic, signaling, transportational and regulatory.

All protein functions are realized by highly specific and highly effective protein-ligand interactions, where ligands can be either other protein molecules, nucleic acids, lipids, small molecules, substrates, allosteric modulators, inhibitors or some drugs. Indeed the specificity of protein-ligand interactions and their regulatory mechanisms are responsible for normal cell functionality and alterations might lead to pathological processes. Knowledge about the nature of those interactions at the atomistic level and the impact of the conformational flexibility and mutational effects on them is crucially important for understanding the molecular nature of cell processes and will contribute to the fields of drug design and biotechnology.

This collection of IJMS aims to present a tribune to broad range state-of-the-art experimental or computational studies or their synergetic combination for understanding protein-ligand interactions in their very broad context. We are also looking for contributions underlining the impact of the investigated processes in biomedicine and molecular pathology as well as applications of protein-ligands interactions in biotechnology and food industry.

Dr. Tatyana Karabencheva-Christova
Dr. Christo Z. Christov
Collection Editors

Manuscript Submission Information

Manuscripts for the topical collection can be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on this website. The topical collection considers regular research articles, short communications and review articles. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs).

Keywords

  • protein
  • protein-protein interactions
  • protein-ligand interactions
  • protein-lipid complexes
  • protein-nucleic acids interactions
  • enzyme inhibition
  • drug design
  • computational modelling
  • docking, binding studies
  • QSAR

Published Papers (68 papers)

2016

Jump to: 2015, 2014, 2013

Open AccessReview Prediction of Protein–Protein Interactions by Evidence Combining Methods
Int. J. Mol. Sci. 2016, 17(11), 1946; doi:10.3390/ijms17111946
Received: 30 September 2016 / Revised: 15 November 2016 / Accepted: 15 November 2016 / Published: 22 November 2016
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Abstract
Most cellular functions involve proteins’ features based on their physical interactions with other partner proteins. Sketching a map of protein–protein interactions (PPIs) is therefore an important inception step towards understanding the basics of cell functions. Several experimental techniques operating in vivo or in
[...] Read more.
Most cellular functions involve proteins’ features based on their physical interactions with other partner proteins. Sketching a map of protein–protein interactions (PPIs) is therefore an important inception step towards understanding the basics of cell functions. Several experimental techniques operating in vivo or in vitro have made significant contributions to screening a large number of protein interaction partners, especially high-throughput experimental methods. However, computational approaches for PPI predication supported by rapid accumulation of data generated from experimental techniques, 3D structure definitions, and genome sequencing have boosted the map sketching of PPIs. In this review, we shed light on in silico PPI prediction methods that integrate evidence from multiple sources, including evolutionary relationship, function annotation, sequence/structure features, network topology and text mining. These methods are developed for integration of multi-dimensional evidence, for designing the strategies to predict novel interactions, and for making the results consistent with the increase of prediction coverage and accuracy. Full article
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Open AccessArticle Systematic Analysis of Protein Interaction Network Associated with Azoospermia
Int. J. Mol. Sci. 2016, 17(11), 1857; doi:10.3390/ijms17111857
Received: 27 July 2016 / Revised: 19 October 2016 / Accepted: 1 November 2016 / Published: 10 November 2016
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Abstract
Non-obstructive azoospermia is a severe infertility factor. Currently, the etiology of this condition remains elusive with several possible molecular pathway disruptions identified in the post-meiotic spermatozoa. In the presented study, in order to identify all possible candidate genes associated with azoospermia and to
[...] Read more.
Non-obstructive azoospermia is a severe infertility factor. Currently, the etiology of this condition remains elusive with several possible molecular pathway disruptions identified in the post-meiotic spermatozoa. In the presented study, in order to identify all possible candidate genes associated with azoospermia and to map their relationship, we present the first protein-protein interaction network related to azoospermia and analyze the complex effects of the related genes systematically. Using Online Mendelian Inheritance in Man, the Human Protein Reference Database and Cytoscape, we created a novel network consisting of 209 protein nodes and 737 interactions. Mathematical analysis identified three proteins, ar, dazap2, and esr1, as hub nodes and a bottleneck protein within the network. We also identified new candidate genes, CREBBP and BCAR1, which may play a role in azoospermia. The gene ontology analysis suggests a genetic link between azoospermia and liver disease. The KEGG analysis also showed 45 statistically important pathways with 31 proteins associated with colorectal, pancreatic, chronic myeloid leukemia and prostate cancer. Two new genes and associated diseases are promising for further experimental validation. Full article
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Open AccessArticle Predicting Protein–Protein Interaction Sites Using Sequence Descriptors and Site Propensity of Neighboring Amino Acids
Int. J. Mol. Sci. 2016, 17(11), 1788; doi:10.3390/ijms17111788
Received: 8 September 2016 / Revised: 14 October 2016 / Accepted: 18 October 2016 / Published: 26 October 2016
PDF Full-text (513 KB) | HTML Full-text | XML Full-text
Abstract
Information about the interface sites of Protein–Protein Interactions (PPIs) is useful for many biological research works. However, despite the advancement of experimental techniques, the identification of PPI sites still remains as a challenging task. Using a statistical learning technique, we proposed a computational
[...] Read more.
Information about the interface sites of Protein–Protein Interactions (PPIs) is useful for many biological research works. However, despite the advancement of experimental techniques, the identification of PPI sites still remains as a challenging task. Using a statistical learning technique, we proposed a computational tool for predicting PPI interaction sites. As an alternative to similar approaches requiring structural information, the proposed method takes all of the input from protein sequences. In addition to typical sequence features, our method takes into consideration that interaction sites are not randomly distributed over the protein sequence. We characterized this positional preference using protein complexes with known structures, proposed a numerical index to estimate the propensity and then incorporated the index into a learning system. The resulting predictor, without using structural information, yields an area under the ROC curve (AUC) of 0.675, recall of 0.597, precision of 0.311 and accuracy of 0.583 on a ten-fold cross-validation experiment. This performance is comparable to the previous approach in which structural information was used. Upon introducing the B-factor data to our predictor, we demonstrated that the AUC can be further improved to 0.750. The tool is accessible at http://bsaltools.ym.edu.tw/predppis. Full article
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Open AccessArticle Integrated Computational Approach for Virtual Hit Identification against Ebola Viral Proteins VP35 and VP40
Int. J. Mol. Sci. 2016, 17(11), 1748; doi:10.3390/ijms17111748
Received: 28 July 2016 / Revised: 18 September 2016 / Accepted: 22 September 2016 / Published: 26 October 2016
PDF Full-text (11195 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The Ebola virus (EBOV) has been recognised for nearly 40 years, with the most recent EBOV outbreak being in West Africa, where it created a humanitarian crisis. Mortalities reported up to 30 March 2016 totalled 11,307. However, up until now, EBOV drugs have
[...] Read more.
The Ebola virus (EBOV) has been recognised for nearly 40 years, with the most recent EBOV outbreak being in West Africa, where it created a humanitarian crisis. Mortalities reported up to 30 March 2016 totalled 11,307. However, up until now, EBOV drugs have been far from achieving regulatory (FDA) approval. It is therefore essential to identify parent compounds that have the potential to be developed into effective drugs. Studies on Ebola viral proteins have shown that some can elicit an immunological response in mice, and these are now considered essential components of a vaccine designed to protect against Ebola haemorrhagic fever. The current study focuses on chemoinformatic approaches to identify virtual hits against Ebola viral proteins (VP35 and VP40), including protein binding site prediction, drug-likeness, pharmacokinetic and pharmacodynamic properties, metabolic site prediction, and molecular docking. Retrospective validation was performed using a database of non-active compounds, and early enrichment of EBOV actives at different false positive rates was calculated. Homology modelling and subsequent superimposition of binding site residues on other strains of EBOV were carried out to check residual conformations, and hence to confirm the efficacy of potential compounds. As a mechanism for artefactual inhibition of proteins through non-specific compounds, virtual hits were assessed for their aggregator potential compared with previously reported aggregators. These systematic studies have indicated that a few compounds may be effective inhibitors of EBOV replication and therefore might have the potential to be developed as anti-EBOV drugs after subsequent testing and validation in experiments in vivo. Full article
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Open AccessArticle Effects of Mutations on Structure–Function Relationships of Matrix Metalloproteinase-1
Int. J. Mol. Sci. 2016, 17(10), 1727; doi:10.3390/ijms17101727
Received: 22 August 2016 / Revised: 16 September 2016 / Accepted: 3 October 2016 / Published: 14 October 2016
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Abstract
Matrix metalloproteinase-1 (MMP-1) is one of the most widely studied enzymes involved in collagen degradation. Mutations of specific residues in the MMP-1 hemopexin-like (HPX) domain have been shown to modulate activity of the MMP-1 catalytic (CAT) domain. In order to reveal the structural
[...] Read more.
Matrix metalloproteinase-1 (MMP-1) is one of the most widely studied enzymes involved in collagen degradation. Mutations of specific residues in the MMP-1 hemopexin-like (HPX) domain have been shown to modulate activity of the MMP-1 catalytic (CAT) domain. In order to reveal the structural and conformational effects of such mutations, a molecular dynamics (MD) study was performed of in silico mutated residues in the X-ray crystallographic structure of MMP-1 complexed with a collagen-model triple-helical peptide (THP). The results indicate an important role of the mutated residues in MMP-1 interactions with the THP and communication between the CAT and the HPX domains. Each mutation has a distinct impact on the correlated motions in the MMP-1•THP. An increased collagenase activity corresponded to the appearance of a unique anti-correlated motion and decreased correlated motions, while decreased collagenase activity corresponded both to increased and decreased anti-correlated motions. Full article
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Open AccessReview In Vivo Analysis of Protein–Protein Interactions with Bioluminescence Resonance Energy Transfer (BRET): Progress and Prospects
Int. J. Mol. Sci. 2016, 17(10), 1704; doi:10.3390/ijms17101704
Received: 15 August 2016 / Revised: 26 September 2016 / Accepted: 29 September 2016 / Published: 11 October 2016
PDF Full-text (1233 KB) | HTML Full-text | XML Full-text
Abstract
Proteins are the elementary machinery of life, and their functions are carried out mostly by molecular interactions. Among those interactions, protein–protein interactions (PPIs) are the most important as they participate in or mediate all essential biological processes. However, many common methods for PPI
[...] Read more.
Proteins are the elementary machinery of life, and their functions are carried out mostly by molecular interactions. Among those interactions, protein–protein interactions (PPIs) are the most important as they participate in or mediate all essential biological processes. However, many common methods for PPI investigations are slightly unreliable and suffer from various limitations, especially in the studies of dynamic PPIs. To solve this problem, a method called Bioluminescence Resonance Energy Transfer (BRET) was developed about seventeen years ago. Since then, BRET has evolved into a whole class of methods that can be used to survey virtually any kinds of PPIs. Compared to many traditional methods, BRET is highly sensitive, reliable, easy to perform, and relatively inexpensive. However, most importantly, it can be done in vivo and allows the real-time monitoring of dynamic PPIs with the easily detectable light signal, which is extremely valuable for the PPI functional research. This review will take a comprehensive look at this powerful technique, including its principles, comparisons with other methods, experimental approaches, classifications, applications, early developments, recent progress, and prospects. Full article
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Open AccessArticle Interactions of β-Conglycinin (7S) with Different Phenolic Acids—Impact on Structural Characteristics and Proteolytic Degradation of Proteins
Int. J. Mol. Sci. 2016, 17(10), 1671; doi:10.3390/ijms17101671
Received: 3 August 2016 / Revised: 9 September 2016 / Accepted: 22 September 2016 / Published: 2 October 2016
PDF Full-text (3275 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
p-Coumalic acid (PCA), caffeic acid (CA), gallic acid (GA) and chlorogenic acid (CGA) are the major phenolic acids that co-exist with soy protein components in foodstuffs. Surprisingly, there are only a handful of reports that describe their interaction with β-Conglycinin (7S), a
[...] Read more.
p-Coumalic acid (PCA), caffeic acid (CA), gallic acid (GA) and chlorogenic acid (CGA) are the major phenolic acids that co-exist with soy protein components in foodstuffs. Surprisingly, there are only a handful of reports that describe their interaction with β-Conglycinin (7S), a major soy protein. In this report, we investigated the interaction between phenolic acids and soy protein 7S and observed an interaction between each of these phenolic acids and soy protein 7S, which was carried out by binding. Further analysis revealed that the binding activity of the phenolic acids was structure dependent. Here, the binding affinity of CA and GA towards 7S was found to be stronger than that of PCA, because CA and GA have one more hydroxyl group. Interestingly, the binding of phenolic acids with soy protein 7S did not affect protein digestion by pepsin and trypsin. These findings aid our understanding of the relationship between different phenolic acids and proteins in complex food systems. Full article
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Open AccessArticle Identification of Protein–Protein Interactions via a Novel Matrix-Based Sequence Representation Model with Amino Acid Contact Information
Int. J. Mol. Sci. 2016, 17(10), 1623; doi:10.3390/ijms17101623
Received: 15 July 2016 / Revised: 7 September 2016 / Accepted: 7 September 2016 / Published: 24 September 2016
PDF Full-text (839 KB) | HTML Full-text | XML Full-text
Abstract
Identification of protein–protein interactions (PPIs) is a difficult and important problem in biology. Since experimental methods for predicting PPIs are both expensive and time-consuming, many computational methods have been developed to predict PPIs and interaction networks, which can be used to complement experimental
[...] Read more.
Identification of protein–protein interactions (PPIs) is a difficult and important problem in biology. Since experimental methods for predicting PPIs are both expensive and time-consuming, many computational methods have been developed to predict PPIs and interaction networks, which can be used to complement experimental approaches. However, these methods have limitations to overcome. They need a large number of homology proteins or literature to be applied in their method. In this paper, we propose a novel matrix-based protein sequence representation approach to predict PPIs, using an ensemble learning method for classification. We construct the matrix of Amino Acid Contact (AAC), based on the statistical analysis of residue-pairing frequencies in a database of 6323 protein–protein complexes. We first represent the protein sequence as a Substitution Matrix Representation (SMR) matrix. Then, the feature vector is extracted by applying algorithms of Histogram of Oriented Gradient (HOG) and Singular Value Decomposition (SVD) on the SMR matrix. Finally, we feed the feature vector into a Random Forest (RF) for judging interaction pairs and non-interaction pairs. Our method is applied to several PPI datasets to evaluate its performance. On the S . c e r e v i s i a e dataset, our method achieves 94 . 83 % accuracy and 92 . 40 % sensitivity. Compared with existing methods, and the accuracy of our method is increased by 0 . 11 percentage points. On the H . p y l o r i dataset, our method achieves 89 . 06 % accuracy and 88 . 15 % sensitivity, the accuracy of our method is increased by 0 . 76 % . On the H u m a n PPI dataset, our method achieves 97 . 60 % accuracy and 96 . 37 % sensitivity, and the accuracy of our method is increased by 1 . 30 % . In addition, we test our method on a very important PPI network, and it achieves 92 . 71 % accuracy. In the Wnt-related network, the accuracy of our method is increased by 16 . 67 % . The source code and all datasets are available at https://figshare.com/s/580c11dce13e63cb9a53. Full article
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Open AccessArticle Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics
Int. J. Mol. Sci. 2016, 17(9), 1396; doi:10.3390/ijms17091396
Received: 4 July 2016 / Revised: 13 August 2016 / Accepted: 16 August 2016 / Published: 25 August 2016
PDF Full-text (755 KB) | HTML Full-text | XML Full-text
Abstract
Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental
[...] Read more.
Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research. Full article
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Open AccessReview Reconstruction and Application of Protein–Protein Interaction Network
Int. J. Mol. Sci. 2016, 17(6), 907; doi:10.3390/ijms17060907
Received: 2 April 2016 / Revised: 31 May 2016 / Accepted: 3 June 2016 / Published: 8 June 2016
Cited by 1 | PDF Full-text (774 KB) | HTML Full-text | XML Full-text
Abstract
The protein-protein interaction network (PIN) is a useful tool for systematic investigation of the complex biological activities in the cell. With the increasing interests on the proteome-wide interaction networks, PINs have been reconstructed for many species, including virus, bacteria, plants, animals, and humans.
[...] Read more.
The protein-protein interaction network (PIN) is a useful tool for systematic investigation of the complex biological activities in the cell. With the increasing interests on the proteome-wide interaction networks, PINs have been reconstructed for many species, including virus, bacteria, plants, animals, and humans. With the development of biological techniques, the reconstruction methods of PIN are further improved. PIN has gradually penetrated many fields in biological research. In this work we systematically reviewed the development of PIN in the past fifteen years, with respect to its reconstruction and application of function annotation, subsystem investigation, evolution analysis, hub protein analysis, and regulation mechanism analysis. Due to the significant role of PIN in the in-depth exploration of biological process mechanisms, PIN will be preferred by more and more researchers for the systematic study of the protein systems in various kinds of organisms. Full article
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Open AccessArticle Identification of Protein–Excipient Interaction Hotspots Using Computational Approaches
Int. J. Mol. Sci. 2016, 17(6), 853; doi:10.3390/ijms17060853
Received: 18 February 2016 / Revised: 12 April 2016 / Accepted: 24 May 2016 / Published: 1 June 2016
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Abstract
Protein formulation development relies on the selection of excipients that inhibit protein–protein interactions preventing aggregation. Empirical strategies involve screening many excipient and buffer combinations using force degradation studies. Such methods do not readily provide information on intermolecular interactions responsible for the protective effects
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Protein formulation development relies on the selection of excipients that inhibit protein–protein interactions preventing aggregation. Empirical strategies involve screening many excipient and buffer combinations using force degradation studies. Such methods do not readily provide information on intermolecular interactions responsible for the protective effects of excipients. This study describes a molecular docking approach to screen and rank interactions allowing for the identification of protein–excipient hotspots to aid in the selection of excipients to be experimentally screened. Previously published work with Drosophila Su(dx) was used to develop and validate the computational methodology, which was then used to determine the formulation hotspots for Fab A33. Commonly used excipients were examined and compared to the regions in Fab A33 prone to protein–protein interactions that could lead to aggregation. This approach could provide information on a molecular level about the protective interactions of excipients in protein formulations to aid the more rational development of future formulations. Full article
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Open AccessArticle Stable Toll-Like Receptor 10 Knockdown in THP-1 Cells Reduces TLR-Ligand-Induced Proinflammatory Cytokine Expression
Int. J. Mol. Sci. 2016, 17(6), 859; doi:10.3390/ijms17060859
Received: 10 February 2016 / Revised: 24 May 2016 / Accepted: 26 May 2016 / Published: 1 June 2016
PDF Full-text (1843 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Toll-like receptor 10 (TLR10) is the only orphan receptor whose natural ligand and function are unknown among the 10 human TLRs. In this study, to test whether TLR10 recognizes some known TLR ligands, we established a stable TLR10 knockdown human monocytic cell line
[...] Read more.
Toll-like receptor 10 (TLR10) is the only orphan receptor whose natural ligand and function are unknown among the 10 human TLRs. In this study, to test whether TLR10 recognizes some known TLR ligands, we established a stable TLR10 knockdown human monocytic cell line THP-1 using TLR10 short hairpin RNA lentiviral particle and puromycin selection. Among 60 TLR10 knockdown clones that were derived from each single transduced cell, six clones were randomly selected, and then one of those clones, named E7, was chosen for the functional study. E7 exhibited approximately 50% inhibition of TLR10 mRNA and protein expression. Of all the TLRs, only the expression of TLR10 changed significantly in this cell line. Additionally, phorbol 12-myristate 13-acetate-induced macrophage differentiation of TLR10 knockdown cells was not affected in the knockdown cells. When exposed to TLR ligands, such as synthetic diacylated lipoprotein (FSL-1), lipopolysaccharide (LPS), and flagellin, significant induction of proinflammatory cytokine gene expression including Interleukin-8 (IL-8), Interleukin-1 beta (IL-1β), Tumor necrosis factor-alpha (TNF-α) and Chemokine (C–C Motif) Ligand 20 (CCL20) expression, was found in the control THP-1 cells, whereas the TLR10 knockdown cells exhibited a significant reduction in the expression of IL-8, IL-1β, and CCL20. TNF-α was the only cytokine for which the expression did not decrease in the TLR10 knockdown cells from that measured in the control cells. Analysis of putative binding sites for transcription factors using a binding-site-prediction program revealed that the TNF-α promoter does not have putative binding sites for AP-1 or c-Jun, comprising a major transcription factor along with NF-κB for TLR signaling. Our results suggest that TLR10 is involved in the recognition of FSL-1, LPS, and flagellin and TLR-ligand-induced expression of TNF-α does not depend on TLR10. Full article
Open AccessArticle Computational Studies of a Mechanism for Binding and Drug Resistance in the Wild Type and Four Mutations of HIV-1 Protease with a GRL-0519 Inhibitor
Int. J. Mol. Sci. 2016, 17(6), 819; doi:10.3390/ijms17060819
Received: 4 March 2016 / Revised: 16 May 2016 / Accepted: 16 May 2016 / Published: 27 May 2016
PDF Full-text (4580 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Drug resistance of mutations in HIV-1 protease (PR) is the most severe challenge to the long-term efficacy of HIV-1 PR inhibitor in highly active antiretroviral therapy. To elucidate the molecular mechanism of drug resistance associated with mutations (D30N, I50V, I54M, and V82A) and
[...] Read more.
Drug resistance of mutations in HIV-1 protease (PR) is the most severe challenge to the long-term efficacy of HIV-1 PR inhibitor in highly active antiretroviral therapy. To elucidate the molecular mechanism of drug resistance associated with mutations (D30N, I50V, I54M, and V82A) and inhibitor (GRL-0519) complexes, we have performed five molecular dynamics (MD) simulations and calculated the binding free energies using the molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) method. The ranking of calculated binding free energies is in accordance with the experimental data. The free energy spectra of each residue and inhibitor interaction for all complexes show a similar binding model. Analysis based on the MD trajectories and contribution of each residues show that groups R2 and R3 mainly contribute van der Waals energies, while groups R1 and R4 contribute electrostatic interaction by hydrogen bonds. The drug resistance of D30N can be attributed to the decline in binding affinity of residues 28 and 29. The size of Val50 is smaller than Ile50 causes the residue to move, especially in chain A. The stable hydrophobic core, including the side chain of Ile54 in the wild type (WT) complex, became unstable in I54M because the side chain of Met54 is flexible with two alternative conformations. The binding affinity of Ala82 in V82A decreases relative to Val82 in WT. The present study could provide important guidance for the design of a potent new drug resisting the mutation inhibitors. Full article
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Open AccessArticle RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein Sequences
Int. J. Mol. Sci. 2016, 17(5), 757; doi:10.3390/ijms17050757
Received: 10 April 2016 / Revised: 29 April 2016 / Accepted: 4 May 2016 / Published: 18 May 2016
Cited by 1 | PDF Full-text (697 KB) | HTML Full-text | XML Full-text
Abstract
Protein-Protein Interactions (PPIs) play essential roles in most cellular processes. Knowledge of PPIs is becoming increasingly more important, which has prompted the development of technologies that are capable of discovering large-scale PPIs. Although many high-throughput biological technologies have been proposed to detect PPIs,
[...] Read more.
Protein-Protein Interactions (PPIs) play essential roles in most cellular processes. Knowledge of PPIs is becoming increasingly more important, which has prompted the development of technologies that are capable of discovering large-scale PPIs. Although many high-throughput biological technologies have been proposed to detect PPIs, there are unavoidable shortcomings, including cost, time intensity, and inherently high false positive and false negative rates. For the sake of these reasons, in silico methods are attracting much attention due to their good performances in predicting PPIs. In this paper, we propose a novel computational method known as RVM-AB that combines the Relevance Vector Machine (RVM) model and Average Blocks (AB) to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the AB feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier. We performed five-fold cross-validation experiments on yeast and Helicobacter pylori datasets, and achieved very high accuracies of 92.98% and 95.58% respectively, which is significantly better than previous works. In addition, we also obtained good prediction accuracies of 88.31%, 89.46%, 91.08%, 91.55%, and 94.81% on other five independent datasets C. elegans, M. musculus, H. sapiens, H. pylori, and E. coli for cross-species prediction. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the yeast dataset. The experimental results demonstrate that our RVM-AB method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool. To facilitate extensive studies for future proteomics research, we developed a freely available web server called RVMAB-PPI in Hypertext Preprocessor (PHP) for predicting PPIs. The web server including source code and the datasets are available at http://219.219.62.123:8888/ppi_ab/. Full article
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Open AccessReview Recent Progress in Treating Protein–Ligand Interactions with Quantum-Mechanical Methods
Int. J. Mol. Sci. 2016, 17(5), 742; doi:10.3390/ijms17050742
Received: 16 March 2016 / Revised: 18 April 2016 / Accepted: 3 May 2016 / Published: 16 May 2016
Cited by 1 | PDF Full-text (227 KB) | HTML Full-text | XML Full-text
Abstract
We review the first successes and failures of a “new wave” of quantum chemistry-based approaches to the treatment of protein/ligand interactions. These approaches share the use of “enhanced”, dispersion (D), and/or hydrogen-bond (H) corrected density functional theory (DFT) or semi-empirical quantum mechanical (SQM)
[...] Read more.
We review the first successes and failures of a “new wave” of quantum chemistry-based approaches to the treatment of protein/ligand interactions. These approaches share the use of “enhanced”, dispersion (D), and/or hydrogen-bond (H) corrected density functional theory (DFT) or semi-empirical quantum mechanical (SQM) methods, in combination with ensemble weighting techniques of some form to capture entropic effects. Benchmark and model system calculations in comparison to high-level theoretical as well as experimental references have shown that both DFT-D (dispersion-corrected density functional theory) and SQM-DH (dispersion and hydrogen bond-corrected semi-empirical quantum mechanical) perform much more accurately than older DFT and SQM approaches and also standard docking methods. In addition, DFT-D might soon become and SQM-DH already is fast enough to compute a large number of binding modes of comparably large protein/ligand complexes, thus allowing for a more accurate assessment of entropic effects. Full article
Open AccessReview Confocal Spectroscopy to Study Dimerization, Oligomerization and Aggregation of Proteins: A Practical Guide
Int. J. Mol. Sci. 2016, 17(5), 655; doi:10.3390/ijms17050655
Received: 19 February 2016 / Revised: 15 April 2016 / Accepted: 20 April 2016 / Published: 30 April 2016
PDF Full-text (3721 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Protein self-association is a key feature that can modulate the physiological role of proteins or lead to deleterious effects when uncontrolled. Protein oligomerization is a simple way to modify the activity of a protein, as the modulation of binding interfaces allows for self-activation
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Protein self-association is a key feature that can modulate the physiological role of proteins or lead to deleterious effects when uncontrolled. Protein oligomerization is a simple way to modify the activity of a protein, as the modulation of binding interfaces allows for self-activation or inhibition, or variation in the selectivity of binding partners. As such, dimerization and higher order oligomerization is a common feature in signaling proteins, for example, and more than 70% of enzymes have the potential to self-associate. On the other hand, protein aggregation can overcome the regulatory mechanisms of the cell and can have disastrous physiological effects. This is the case in a number of neurodegenerative diseases, where proteins, due to mutation or dysregulation later in life, start polymerizing and often fibrillate, leading to the creation of protein inclusion bodies in cells. Dimerization, well-defined oligomerization and random aggregation are often difficult to differentiate and characterize experimentally. Single molecule “counting” methods are particularly well suited to the study of self-oligomerization as they allow observation and quantification of behaviors in heterogeneous conditions. However, the extreme dilution of samples often causes weak complexes to dissociate, and rare events can be overlooked. Here, we discuss a straightforward alternative where the principles of single molecule detection are used at higher protein concentrations to quantify oligomers and aggregates in a background of monomers. We propose a practical guide for the use of confocal spectroscopy to quantify protein oligomerization status and also discuss about its use in monitoring changes in protein aggregation in drug screening assays. Full article
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Open AccessArticle Identification of Toxic Pyrrolizidine Alkaloids and Their Common Hepatotoxicity Mechanism
Int. J. Mol. Sci. 2016, 17(3), 318; doi:10.3390/ijms17030318
Received: 30 December 2015 / Revised: 19 February 2016 / Accepted: 24 February 2016 / Published: 7 March 2016
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Abstract
Pyrrolizidine Alkaloids (PAs) are currently one of the most important botanical hepatotoxic ingredients. Glutathion (GSH) metabolism is the most reported pathway involved in hepatotoxicity mechanism of PAs. We speculate that, for different PAs, there should be a common mechanism underlying their hepatotoxicity in
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Pyrrolizidine Alkaloids (PAs) are currently one of the most important botanical hepatotoxic ingredients. Glutathion (GSH) metabolism is the most reported pathway involved in hepatotoxicity mechanism of PAs. We speculate that, for different PAs, there should be a common mechanism underlying their hepatotoxicity in GSH metabolism. Computational methods were adopted to test our hypothesis in consideration of the limitations of current experimental approaches. Firstly, the potential targets of 22 PAs (from three major PA types) in GSH metabolism were identified by reverse docking; Secondly, glutathione S-transferase A1 (GSTA1) and glutathione peroxidase 1 (GPX1) targets pattern was found to be a special characteristic of toxic PAs with stepwise multiple linear regressions; Furthermore, the molecular mechanism underlying the interactions within toxic PAs and these two targets was demonstrated with the ligand-protein interaction analysis; Finally, GSTA1 and GPX1 were proved to be significant nodes in GSH metabolism. Overall, toxic PAs could be identified by GSTA1 and GPX1 targets pattern, which suggests their common hepatotoxicity mechanism: the interfering of detoxication in GSH metabolism. In addition, all the strategies developed here could be extended to studies on toxicity mechanism of other toxins. Full article
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Open AccessReview Insights into Protein–Ligand Interactions: Mechanisms, Models, and Methods
Int. J. Mol. Sci. 2016, 17(2), 144; doi:10.3390/ijms17020144
Received: 9 November 2015 / Revised: 13 January 2016 / Accepted: 18 January 2016 / Published: 26 January 2016
Cited by 6 | PDF Full-text (891 KB) | HTML Full-text | XML Full-text
Abstract
Molecular recognition, which is the process of biological macromolecules interacting with each other or various small molecules with a high specificity and affinity to form a specific complex, constitutes the basis of all processes in living organisms. Proteins, an important class of biological
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Molecular recognition, which is the process of biological macromolecules interacting with each other or various small molecules with a high specificity and affinity to form a specific complex, constitutes the basis of all processes in living organisms. Proteins, an important class of biological macromolecules, realize their functions through binding to themselves or other molecules. A detailed understanding of the protein–ligand interactions is therefore central to understanding biology at the molecular level. Moreover, knowledge of the mechanisms responsible for the protein-ligand recognition and binding will also facilitate the discovery, design, and development of drugs. In the present review, first, the physicochemical mechanisms underlying protein–ligand binding, including the binding kinetics, thermodynamic concepts and relationships, and binding driving forces, are introduced and rationalized. Next, three currently existing protein-ligand binding models—the “lock-and-key”, “induced fit”, and “conformational selection”—are described and their underlying thermodynamic mechanisms are discussed. Finally, the methods available for investigating protein–ligand binding affinity, including experimental and theoretical/computational approaches, are introduced, and their advantages, disadvantages, and challenges are discussed. Full article
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2015

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Open AccessReview Proteins and Their Interacting Partners: An Introduction to Protein–Ligand Binding Site Prediction Methods
Int. J. Mol. Sci. 2015, 16(12), 29829-29842; doi:10.3390/ijms161226202
Received: 20 September 2015 / Revised: 2 December 2015 / Accepted: 10 December 2015 / Published: 15 December 2015
Cited by 4 | PDF Full-text (523 KB) | HTML Full-text | XML Full-text
Abstract
Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in
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Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein–ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein–ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein–ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems. Full article
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Open AccessArticle The Intrinsic Dynamics and Unfolding Process of an Antibody Fab Fragment Revealed by Elastic Network Model
Int. J. Mol. Sci. 2015, 16(12), 29720-29731; doi:10.3390/ijms161226197
Received: 2 November 2015 / Revised: 3 December 2015 / Accepted: 7 December 2015 / Published: 11 December 2015
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Abstract
Antibodies have been increasingly used as pharmaceuticals in clinical treatment. Thermal stability and unfolding process are important properties that must be considered in antibody design. In this paper, the structure-encoded dynamical properties and the unfolding process of the Fab fragment of the phosphocholine-binding
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Antibodies have been increasingly used as pharmaceuticals in clinical treatment. Thermal stability and unfolding process are important properties that must be considered in antibody design. In this paper, the structure-encoded dynamical properties and the unfolding process of the Fab fragment of the phosphocholine-binding antibody McPC603 are investigated by use of the normal mode analysis of Gaussian network model (GNM). Firstly, the temperature factors for the residues of the protein were calculated with GNM and then compared with the experimental measurements. A good result was obtained, which provides the validity for the use of GNM to study the dynamical properties of the protein. Then, with this approach, the mean-square fluctuation (MSF) of the residues, as well as the MSF in the internal distance (MSFID) between all pairwise residues, was calculated to investigate the mobility and flexibility of the protein, respectively. It is found that the mobility and flexibility of the constant regions are higher than those of the variable regions, and the six complementarity-determining regions (CDRs) in the variable regions also exhibit relative large mobility and flexibility. The large amplitude motions of the CDRs are considered to be associated with the immune function of the antibody. In addition, the unfolding process of the protein was simulated by iterative use of the GNM. In our method, only the topology of protein native structure is taken into account, and the protein unfolding process is simulated through breaking the native contacts one by one according to the MSFID values between the residues. It is found that the flexible regions tend to unfold earlier. The sequence of the unfolding events obtained by our method is consistent with the hydrogen-deuterium exchange experimental results. Our studies imply that the unfolding behavior of the Fab fragment of antibody McPc603 is largely determined by the intrinsic dynamics of the protein. Full article
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Open AccessReview Computational Prediction of RNA-Binding Proteins and Binding Sites
Int. J. Mol. Sci. 2015, 16(11), 26303-26317; doi:10.3390/ijms161125952
Received: 1 October 2015 / Revised: 20 October 2015 / Accepted: 23 October 2015 / Published: 3 November 2015
Cited by 5 | PDF Full-text (509 KB) | HTML Full-text | XML Full-text
Abstract
Proteins and RNA interaction have vital roles in many cellular processes such as protein synthesis, sequence encoding, RNA transfer, and gene regulation at the transcriptional and post-transcriptional levels. Approximately 6%–8% of all proteins are RNA-binding proteins (RBPs). Distinguishing these RBPs or their binding
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Proteins and RNA interaction have vital roles in many cellular processes such as protein synthesis, sequence encoding, RNA transfer, and gene regulation at the transcriptional and post-transcriptional levels. Approximately 6%–8% of all proteins are RNA-binding proteins (RBPs). Distinguishing these RBPs or their binding residues is a major aim of structural biology. Previously, a number of experimental methods were developed for the determination of protein–RNA interactions. However, these experimental methods are expensive, time-consuming, and labor-intensive. Alternatively, researchers have developed many computational approaches to predict RBPs and protein–RNA binding sites, by combining various machine learning methods and abundant sequence and/or structural features. There are three kinds of computational approaches, which are prediction from protein sequence, prediction from protein structure, and protein-RNA docking. In this paper, we review all existing studies of predictions of RNA-binding sites and RBPs and complexes, including data sets used in different approaches, sequence and structural features used in several predictors, prediction method classifications, performance comparisons, evaluation methods, and future directions. Full article
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Open AccessReview Structural Features of the ATP-Binding Cassette (ABC) Transporter ABCA3
Int. J. Mol. Sci. 2015, 16(8), 19631-19644; doi:10.3390/ijms160819631
Received: 14 June 2015 / Revised: 23 July 2015 / Accepted: 7 August 2015 / Published: 19 August 2015
Cited by 1 | PDF Full-text (2711 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In this review we reported and discussed the structural features of the ATP-Binding Cassette (ABC) transporter ABCA3 and how the use of bioinformatics tools could help researchers to obtain a reliable structural model of this important transporter. In fact, a model of ABCA3
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In this review we reported and discussed the structural features of the ATP-Binding Cassette (ABC) transporter ABCA3 and how the use of bioinformatics tools could help researchers to obtain a reliable structural model of this important transporter. In fact, a model of ABCA3 is still lacking and no crystallographic structures (of the transporter or of its orthologues) are available. With the advent of next generation sequencing, many disease-causing mutations have been discovered and many more will be found in the future. In the last few years, ABCA3 mutations have been reported to have important pediatric implications. Thus, clinicians need a reliable structure to locate relevant mutations of this transporter and make genotype/phenotype correlations of patients affected by ABCA3-related diseases. In conclusion, we strongly believe that the model preliminarily generated by these novel bioinformatics tools could be the starting point to obtain more refined models of the ABCA3 transporter. Full article
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Open AccessArticle Structural and Dynamical Insight into PPARγ Antagonism: In Silico Study of the Ligand-Receptor Interactions of Non-Covalent Antagonists
Int. J. Mol. Sci. 2015, 16(7), 15405-15424; doi:10.3390/ijms160715405
Received: 12 May 2015 / Revised: 26 June 2015 / Accepted: 30 June 2015 / Published: 8 July 2015
Cited by 6 | PDF Full-text (3144 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The structural and dynamical properties of the peroxisome proliferator-activated receptor γ (PPARγ) nuclear receptor have been broadly studied in its agonist state but little is known about the key features required for the receptor antagonistic activity. Here we report a series of molecular
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The structural and dynamical properties of the peroxisome proliferator-activated receptor γ (PPARγ) nuclear receptor have been broadly studied in its agonist state but little is known about the key features required for the receptor antagonistic activity. Here we report a series of molecular dynamics (MD) simulations in combination with free energy estimation of the recently discovered class of non-covalent PPARγ antagonists. Their binding modes and dynamical behavior are described in details. Two key interactions have been detected within the cavity between helices H3, H11 and the activation helix H12, as well as with H12. The strength of the ligand-amino acid residues interactions has been analyzed in relation to the specificity of the ligand dynamical and antagonistic features. According to our results, the PPARγ activation helix does not undergo dramatic conformational changes, as seen in other nuclear receptors, but rather perturbations that occur through a significant ligand-induced reshaping of the ligand-receptor and the receptor-coactivator binding pockets. The H12 residue Tyr473 and the charge clamp residue Glu471 play a central role for the receptor transformations. Our results also demonstrate that MD can be a helpful tool for the compound phenotype characterization (full agonists, partial agonists or antagonists) when insufficient experimental data are available. Full article
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Open AccessArticle Combinatorial Pharmacophore-Based 3D-QSAR Analysis and Virtual Screening of FGFR1 Inhibitors
Int. J. Mol. Sci. 2015, 16(6), 13407-13426; doi:10.3390/ijms160613407
Received: 25 March 2015 / Revised: 1 June 2015 / Accepted: 1 June 2015 / Published: 11 June 2015
Cited by 2 | PDF Full-text (3943 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) signaling pathway plays crucial roles in cell proliferation, angiogenesis, migration, and survival. Aberration in FGFRs correlates with several malignancies and disorders. FGFRs have proved to be attractive targets for therapeutic intervention in cancer, and it
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The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) signaling pathway plays crucial roles in cell proliferation, angiogenesis, migration, and survival. Aberration in FGFRs correlates with several malignancies and disorders. FGFRs have proved to be attractive targets for therapeutic intervention in cancer, and it is of high interest to find FGFR inhibitors with novel scaffolds. In this study, a combinatorial three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed based on previously reported FGFR1 inhibitors with diverse structural skeletons. This model was evaluated for its prediction performance on a diverse test set containing 232 FGFR inhibitors, and it yielded a SD value of 0.75 pIC50 units from measured inhibition affinities and a Pearson’s correlation coefficient R2 of 0.53. This result suggests that the combinatorial 3D-QSAR model could be used to search for new FGFR1 hit structures and predict their potential activity. To further evaluate the performance of the model, a decoy set validation was used to measure the efficiency of the model by calculating EF (enrichment factor). Based on the combinatorial pharmacophore model, a virtual screening against SPECS database was performed. Nineteen novel active compounds were successfully identified, which provide new chemical starting points for further structural optimization of FGFR1 inhibitors. Full article
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Open AccessArticle Do Matrix Metalloproteases and Tissue Inhibitors of Metalloproteases in Tenocytes of the Rotator Cuff Differ with Varying Donor Characteristics?
Int. J. Mol. Sci. 2015, 16(6), 13141-13157; doi:10.3390/ijms160613141
Received: 9 March 2015 / Accepted: 28 May 2015 / Published: 9 June 2015
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Abstract
An imbalance between matrix metalloproteases (MMPs) and the tissue inhibitors of metalloproteases (TIMPs) may have a negative impact on the healing of rotator cuff tears. The aim of the project was to assess a possible relationship between clinical and radiographic characteristics of patients
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An imbalance between matrix metalloproteases (MMPs) and the tissue inhibitors of metalloproteases (TIMPs) may have a negative impact on the healing of rotator cuff tears. The aim of the project was to assess a possible relationship between clinical and radiographic characteristics of patients such as the age, sex, as well as the degenerative status of the tendon and the MMPs and TIMPs in their tenocyte-like cells (TLCs). TLCs were isolated from ruptured supraspinatus tendons and quantitative Real-Time PCR and ELISA was performed to analyze the expression and secretion of MMPs and TIMPs. In the present study, MMPs, mostly gelatinases and collagenases such as MMP-2, -9 and -13 showed an increased expression and protein secretion in TLCs of donors with higher age or degenerative status of the tendon. Furthermore, the expression and secretion of TIMP-1, -2 and -3 was enhanced with age, muscle fatty infiltration and tear size. The interaction between MMPs and TIMPs is a complex process, since TIMPs are not only inhibitors, but also activators of MMPs. This study shows that MMPs and TIMPs might play an important role in degenerative tendon pathologies. Full article
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Open AccessArticle Prediction of Protein–Protein Interactions with Clustered Amino Acids and Weighted Sparse Representation
Int. J. Mol. Sci. 2015, 16(5), 10855-10869; doi:10.3390/ijms160510855
Received: 9 April 2015 / Revised: 6 May 2015 / Accepted: 7 May 2015 / Published: 13 May 2015
Cited by 6 | PDF Full-text (726 KB) | HTML Full-text | XML Full-text
Abstract
With the completion of the Human Genome Project, bioscience has entered into the era of the genome and proteome. Therefore, protein–protein interactions (PPIs) research is becoming more and more important. Life activities and the protein–protein interactions are inseparable, such as DNA synthesis, gene
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With the completion of the Human Genome Project, bioscience has entered into the era of the genome and proteome. Therefore, protein–protein interactions (PPIs) research is becoming more and more important. Life activities and the protein–protein interactions are inseparable, such as DNA synthesis, gene transcription activation, protein translation, etc. Though many methods based on biological experiments and machine learning have been proposed, they all spent a long time to learn and obtained an imprecise accuracy. How to efficiently and accurately predict PPIs is still a big challenge. To take up such a challenge, we developed a new predictor by incorporating the reduced amino acid alphabet (RAAA) information into the general form of pseudo-amino acid composition (PseAAC) and with the weighted sparse representation-based classification (WSRC). The remarkable advantages of introducing the reduced amino acid alphabet is being able to avoid the notorious dimensionality disaster or overfitting problem in statistical prediction. Additionally, experiments have proven that our method achieved good performance in both a low- and high-dimensional feature space. Among all of the experiments performed on the PPIs data of Saccharomyces cerevisiae, the best one achieved 90.91% accuracy, 94.17% sensitivity, 87.22% precision and a 83.43% Matthews correlation coefficient (MCC) value. In order to evaluate the prediction ability of our method, extensive experiments are performed to compare with the state-of-the-art technique, support vector machine (SVM). The achieved results show that the proposed approach is very promising for predicting PPIs, and it can be a helpful supplement for PPIs prediction. Full article
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Open AccessArticle Role of Long-Range Protein Dynamics in Different Thymidylate Synthase Catalyzed Reactions
Int. J. Mol. Sci. 2015, 16(4), 7304-7319; doi:10.3390/ijms16047304
Received: 18 February 2015 / Revised: 26 March 2015 / Accepted: 30 March 2015 / Published: 1 April 2015
Cited by 2 | PDF Full-text (1861 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Recent studies of Escherichia coli thymidylate synthase (ecTSase) showed that a highly conserved residue, Y209, that is located 8 Å away from the reaction site, plays a key role in the protein’s dynamics. Those crystallographic studies indicated that Y209W mutant is
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Recent studies of Escherichia coli thymidylate synthase (ecTSase) showed that a highly conserved residue, Y209, that is located 8 Å away from the reaction site, plays a key role in the protein’s dynamics. Those crystallographic studies indicated that Y209W mutant is a structurally identical but dynamically altered relative to the wild type (WT) enzyme, and that its turnover catalytic rate governed by a slow hydride-transfer has been affected. The most challenging test of an examination of a fast chemical conversion that precedes the rate-limiting step has been achieved here. The physical nature of both fast and slow C-H bond activations have been compared between the WT and mutant by means of observed and intrinsic kinetic isotope effects (KIEs) and their temperature dependence. The findings indicate that the proton abstraction step has not been altered as much as the hydride transfer step. Additionally, the comparison indicated that other kinetic steps in the TSase catalyzed reaction were substantially affected, including the order of the substrate binding. Enigmatically, although Y209 is H-bonded to 3'-OH of 2'-deoxyuridine-5'-mono­phosphate (dUMP), its altered dynamics is more pronounced on the binding of the remote cofactor, (6R)-N5,N10-methylene-5,6,7,8-tetrahydrofolate (CH2H4folate), revealing the importance of long-range dynamics of the enzymatic complex and its catalytic function. Full article
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Open AccessArticle Molecular Dynamics Simulations of Acylpeptide Hydrolase Bound to Chlorpyrifosmethyl Oxon and Dichlorvos
Int. J. Mol. Sci. 2015, 16(3), 6217-6234; doi:10.3390/ijms16036217
Received: 23 December 2014 / Revised: 3 February 2015 / Accepted: 4 March 2015 / Published: 18 March 2015
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Abstract
Acylpeptide hydrolases (APHs) catalyze the removal of N-acylated amino acids from blocked peptides. Like other prolyloligopeptidase (POP) family members, APHs are believed to be important targets for drug design. To date, the binding pose of organophosphorus (OP) compounds of APH, as well
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Acylpeptide hydrolases (APHs) catalyze the removal of N-acylated amino acids from blocked peptides. Like other prolyloligopeptidase (POP) family members, APHs are believed to be important targets for drug design. To date, the binding pose of organophosphorus (OP) compounds of APH, as well as the different OP compounds binding and inducing conformational changes in two domains, namely, α/β hydrolase and β-propeller, remain poorly understood. We report a computational study of APH bound to chlorpyrifosmethyl oxon and dichlorvos. In our docking study, Val471 and Gly368 are important residues for chlorpyrifosmethyl oxon and dichlorvos binding. Molecular dynamics simulations were also performed to explore the conformational changes between the chlorpyrifosmethyl oxon and dichlorvos bound to APH, which indicated that the structural feature of chlorpyrifosmethyl oxon binding in APH permitted partial opening of the β-propeller fold and allowed the chlorpyrifosmethyl oxon to easily enter the catalytic site. These results may facilitate the design of APH-targeting drugs with improved efficacy. Full article
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Open AccessReview An Overview of the Prediction of Protein DNA-Binding Sites
Int. J. Mol. Sci. 2015, 16(3), 5194-5215; doi:10.3390/ijms16035194
Received: 31 December 2014 / Revised: 21 February 2015 / Accepted: 27 February 2015 / Published: 6 March 2015
Cited by 6 | PDF Full-text (771 KB) | HTML Full-text | XML Full-text
Abstract
Interactions between proteins and DNA play an important role in many essential biological processes such as DNA replication, transcription, splicing, and repair. The identification of amino acid residues involved in DNA-binding sites is critical for understanding the mechanism of these biological activities. In
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Interactions between proteins and DNA play an important role in many essential biological processes such as DNA replication, transcription, splicing, and repair. The identification of amino acid residues involved in DNA-binding sites is critical for understanding the mechanism of these biological activities. In the last decade, numerous computational approaches have been developed to predict protein DNA-binding sites based on protein sequence and/or structural information, which play an important role in complementing experimental strategies. At this time, approaches can be divided into three categories: sequence-based DNA-binding site prediction, structure-based DNA-binding site prediction, and homology modeling and threading. In this article, we review existing research on computational methods to predict protein DNA-binding sites, which includes data sets, various residue sequence/structural features, machine learning methods for comparison and selection, evaluation methods, performance comparison of different tools, and future directions in protein DNA-binding site prediction. In particular, we detail the meta-analysis of protein DNA-binding sites. We also propose specific implications that are likely to result in novel prediction methods, increased performance, or practical applications. Full article
Open AccessArticle Efficient Prediction of Progesterone Receptor Interactome Using a Support Vector Machine Model
Int. J. Mol. Sci. 2015, 16(3), 4774-4785; doi:10.3390/ijms16034774
Received: 14 January 2015 / Revised: 20 February 2015 / Accepted: 25 February 2015 / Published: 3 March 2015
Cited by 1 | PDF Full-text (877 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Protein-protein interaction (PPI) is essential for almost all cellular processes and identification of PPI is a crucial task for biomedical researchers. So far, most computational studies of PPI are intended for pair-wise prediction. Theoretically, predicting protein partners for a single protein is likely
[...] Read more.
Protein-protein interaction (PPI) is essential for almost all cellular processes and identification of PPI is a crucial task for biomedical researchers. So far, most computational studies of PPI are intended for pair-wise prediction. Theoretically, predicting protein partners for a single protein is likely a simpler problem. Given enough data for a particular protein, the results can be more accurate than general PPI predictors. In the present study, we assessed the potential of using the support vector machine (SVM) model with selected features centered on a particular protein for PPI prediction. As a proof-of-concept study, we applied this method to identify the interactome of progesterone receptor (PR), a protein which is essential for coordinating female reproduction in mammals by mediating the actions of ovarian progesterone. We achieved an accuracy of 91.9%, sensitivity of 92.8% and specificity of 91.2%. Our method is generally applicable to any other proteins and therefore may be of help in guiding biomedical experiments. Full article
Open AccessArticle Binding Mode Analysis of Zerumbone to Key Signal Proteins in the Tumor Necrosis Factor Pathway
Int. J. Mol. Sci. 2015, 16(2), 2747-2766; doi:10.3390/ijms16022747
Received: 24 October 2014 / Accepted: 7 January 2015 / Published: 26 January 2015
Cited by 1 | PDF Full-text (9089 KB) | HTML Full-text | XML Full-text
Abstract
Breast cancer is the second most common cancer among women worldwide. Several signaling pathways have been implicated as causative and progression agents. The tumor necrosis factor (TNF) α protein plays a dual role in promoting and inhibiting cancer depending largely on the pathway
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Breast cancer is the second most common cancer among women worldwide. Several signaling pathways have been implicated as causative and progression agents. The tumor necrosis factor (TNF) α protein plays a dual role in promoting and inhibiting cancer depending largely on the pathway initiated by the binding of the protein to its receptor. Zerumbone, an active constituent of Zingiber zerumbet, Smith, is known to act on the tumor necrosis factor pathway upregulating tumour necrosis factor related apoptosis inducing ligand (TRAIL) death receptors and inducing apoptosis in cancer cells. Zerumbone is a sesquiterpene that is able to penetrate into the hydrophobic pockets of proteins to exert its inhibiting activity with several proteins. We found a good binding with the tumor necrosis factor, kinase κB (IKKβ) and the Nuclear factor κB (NF-κB) component proteins along the TNF pathway. Our results suggest that zerumbone can exert its apoptotic activities by inhibiting the cytoplasmic proteins. It inhibits the IKKβ kinase that activates the NF-κB and also binds to the NF-κB complex in the TNF pathway. Blocking both proteins can lead to inhibition of cell proliferating proteins to be downregulated and possibly ultimate induction of apoptosis. Full article

2014

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Open AccessArticle The Importance of Polarity in the Evolution of the K+ Binding Site of Pyruvate Kinase
Int. J. Mol. Sci. 2014, 15(12), 22214-22226; doi:10.3390/ijms151222214
Received: 25 August 2014 / Revised: 25 October 2014 / Accepted: 18 November 2014 / Published: 2 December 2014
PDF Full-text (1325 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In a previous phylogenetic study of the family of pyruvate kinase, we found one cluster with Glu117 and another with Lys117. Those sequences with Glu117 have Thr113 and are K+-dependent, whereas those with Lys117 have Leu113 and are K+-independent.
[...] Read more.
In a previous phylogenetic study of the family of pyruvate kinase, we found one cluster with Glu117 and another with Lys117. Those sequences with Glu117 have Thr113 and are K+-dependent, whereas those with Lys117 have Leu113 and are K+-independent. The carbonyl oxygen of Thr113 is one of the residues that coordinate K+ in the active site. Even though the side chain of Thr113 does not participate in binding K+, the strict co-evolution between position 117 and 113 suggests that T113 may be the result of the evolutionary pressure to maintain the selectivity of pyruvate kinase activity for K+. Thus, we explored if the replacement of Thr113 by Leu alters the characteristics of the K+ binding site. We found that the polarity of the residue 113 is central in the partition of K+ into its site and that the substitution of Thr for Leu changes the ion selectivity for the monovalent cation with minor changes in the binding of the substrates. Therefore, Thr113 is instrumental in the selectivity of pyruvate kinase for K+. Full article
Open AccessArticle Analysis of Protein–Protein Interactions in MCF-7 and MDA-MB-231 Cell Lines Using Phthalic Acid Chemical
Int. J. Mol. Sci. 2014, 15(11), 20770-20788; doi:10.3390/ijms151120770
Received: 12 September 2014 / Revised: 16 October 2014 / Accepted: 27 October 2014 / Published: 13 November 2014
PDF Full-text (1287 KB) | HTML Full-text | XML Full-text
Abstract
Phthalates are a class of plasticizers that have been characterized as endocrine disrupters, and are associated with genital diseases, cardiotoxicity, hepatotoxicity, and nephrotoxicity in the GeneOntology gene/protein database. In this study, we synthesized phthalic acid chemical probes and demonstrated differing protein–protein interactions between
[...] Read more.
Phthalates are a class of plasticizers that have been characterized as endocrine disrupters, and are associated with genital diseases, cardiotoxicity, hepatotoxicity, and nephrotoxicity in the GeneOntology gene/protein database. In this study, we synthesized phthalic acid chemical probes and demonstrated differing protein–protein interactions between MCF-7 cells and MDA-MB-231 breast cancer cell lines. Phthalic acid chemical probes were synthesized using silicon dioxide particle carriers, which were modified using the silanized linker 3-aminopropyl triethoxyslane (APTES). Incubation with cell lysates from breast cancer cell lines revealed interactions between phthalic acid and cellular proteins in MCF-7 and MDA-MB-231 cells. Subsequent proteomics analyses indicated 22 phthalic acid-binding proteins in both cell types, including heat shock cognate 71-kDa protein, ATP synthase subunit beta, and heat shock protein HSP 90-beta. In addition, 21 MCF-7-specific and 32 MDA-MB-231 specific phthalic acid-binding proteins were identified, including related proteasome proteins, heat shock 70-kDa protein, and NADPH dehydrogenase and ribosomal correlated proteins, ras-related proteins, and members of the heat shock protein family, respectively. Full article
Open AccessArticle Caveolin-1 Limits the Contribution of BKCa Channel to MCF-7 Breast Cancer Cell Proliferation and Invasion
Int. J. Mol. Sci. 2014, 15(11), 20706-20722; doi:10.3390/ijms151120706
Received: 14 August 2014 / Revised: 9 October 2014 / Accepted: 22 October 2014 / Published: 12 November 2014
Cited by 3 | PDF Full-text (1282 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Increasing evidence suggests that caveolin-1 and large conductance Ca2+-activated potassium (BKCa) channels are implicated in the carcinogenesis processes, including cell proliferation and invasion. These two proteins have been proven to interact with each other in vascular endothelial and smooth muscle cells
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Increasing evidence suggests that caveolin-1 and large conductance Ca2+-activated potassium (BKCa) channels are implicated in the carcinogenesis processes, including cell proliferation and invasion. These two proteins have been proven to interact with each other in vascular endothelial and smooth muscle cells and modulate vascular contractility. In this study, we investigated the probable interaction between caveolin-1 and BKCa in MCF-7 breast cancer cells. We identified that caveolin-1 and BKCa were co-localized and could be reciprocally co-immunoprecipitated in human breast cancer MCF-7 cells. siRNA mediated caveolin-1 knockdown resulted in activation and increased surface expression of BKCa channel, and subsequently promoted the proliferation and invasiveness of breast cancer cells. These effects were attenuated in the presence of BKCa-siRNA. Conversely, up-regulated caveolin-1 suppressed function and surface expression of BKCa channel and exerted negative effects on breast cancer cell proliferation and invasion. Similarly, these opposing effects were abrogated by BKCa up-regulation. Collectively, our findings suggest that BKCa is a critical target for suppression by caveolin-1 in suppressing proliferation and invasion of breast cancer cells. The functional complex of caveolin-1 and BKCa in the membrane microdomain may be served as a potential therapeutic target in breast cancer. Full article
Open AccessArticle Metabolism of Cryptic Peptides Derived from Neuropeptide FF Precursors: The Involvement of Insulin-Degrading Enzyme
Int. J. Mol. Sci. 2014, 15(9), 16787-16799; doi:10.3390/ijms150916787
Received: 5 June 2014 / Revised: 3 September 2014 / Accepted: 9 September 2014 / Published: 22 September 2014
Cited by 3 | PDF Full-text (1306 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The term “cryptome” refers to the subset of cryptic peptides with bioactivities that are often unpredictable and very different from the parent protein. These cryptic peptides are generated by proteolytic cleavage of proteases, whose identification in vivo can be very challenging. In this
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The term “cryptome” refers to the subset of cryptic peptides with bioactivities that are often unpredictable and very different from the parent protein. These cryptic peptides are generated by proteolytic cleavage of proteases, whose identification in vivo can be very challenging. In this work, we show that insulin-degrading enzyme (IDE) is able to degrade specific amino acid sequences present in the neuropeptide pro-NPFFA (NPFF precursor), generating some cryptic peptides that are also observed after incubation with rat brain cortex homogenate. The reported experimental findings support the increasingly accredited hypothesis, according to which, due to its wide substrate selectivity, IDE is involved in a wide variety of physiopathological processes. Full article
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Open AccessArticle PL-PatchSurfer: A Novel Molecular Local Surface-Based Method for Exploring Protein-Ligand Interactions
Int. J. Mol. Sci. 2014, 15(9), 15122-15145; doi:10.3390/ijms150915122
Received: 24 April 2014 / Revised: 30 July 2014 / Accepted: 12 August 2014 / Published: 27 August 2014
Cited by 7 | PDF Full-text (1782 KB) | HTML Full-text | XML Full-text
Abstract
Structure-based computational methods have been widely used in exploring protein-ligand interactions, including predicting the binding ligands of a given protein based on their structural complementarity. Compared to other protein and ligand representations, the advantages of a surface representation include reduced sensitivity to subtle
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Structure-based computational methods have been widely used in exploring protein-ligand interactions, including predicting the binding ligands of a given protein based on their structural complementarity. Compared to other protein and ligand representations, the advantages of a surface representation include reduced sensitivity to subtle changes in the pocket and ligand conformation and fast search speed. Here we developed a novel method named PL-PatchSurfer (Protein-Ligand PatchSurfer). PL-PatchSurfer represents the protein binding pocket and the ligand molecular surface as a combination of segmented surface patches. Each patch is characterized by its geometrical shape and the electrostatic potential, which are represented using the 3D Zernike descriptor (3DZD). We first tested PL-PatchSurfer on binding ligand prediction and found it outperformed the pocket-similarity based ligand prediction program. We then optimized the search algorithm of PL-PatchSurfer using the PDBbind dataset. Finally, we explored the utility of applying PL-PatchSurfer to a larger and more diverse dataset and showed that PL-PatchSurfer was able to provide a high early enrichment for most of the targets. To the best of our knowledge, PL-PatchSurfer is the first surface patch-based method that treats ligand complementarity at protein binding sites. We believe that using a surface patch approach to better understand protein-ligand interactions has the potential to significantly enhance the design of new ligands for a wide array of drug-targets. Full article
Open AccessArticle A Novel Feature Extraction Scheme with Ensemble Coding for Protein–Protein Interaction Prediction
Int. J. Mol. Sci. 2014, 15(7), 12731-12749; doi:10.3390/ijms150712731
Received: 7 May 2014 / Revised: 23 June 2014 / Accepted: 14 July 2014 / Published: 18 July 2014
Cited by 3 | PDF Full-text (1796 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Protein–protein interactions (PPIs) play key roles in most cellular processes, such as cell metabolism, immune response, endocrine function, DNA replication, and transcription regulation. PPI prediction is one of the most challenging problems in functional genomics. Although PPI data have been increasing because of
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Protein–protein interactions (PPIs) play key roles in most cellular processes, such as cell metabolism, immune response, endocrine function, DNA replication, and transcription regulation. PPI prediction is one of the most challenging problems in functional genomics. Although PPI data have been increasing because of the development of high-throughput technologies and computational methods, many problems are still far from being solved. In this study, a novel predictor was designed by using the Random Forest (RF) algorithm with the ensemble coding (EC) method. To reduce computational time, a feature selection method (DX) was adopted to rank the features and search the optimal feature combination. The DXEC method integrates many features and physicochemical/biochemical properties to predict PPIs. On the Gold Yeast dataset, the DXEC method achieves 67.2% overall precision, 80.74% recall, and 70.67% accuracy. On the Silver Yeast dataset, the DXEC method achieves 76.93% precision, 77.98% recall, and 77.27% accuracy. On the human dataset, the prediction accuracy reaches 80% for the DXEC-RF method. We extended the experiment to a bigger and more realistic dataset that maintains 50% recall on the Yeast All dataset and 80% recall on the Human All dataset. These results show that the DXEC method is suitable for performing PPI prediction. The prediction service of the DXEC-RF classifier is available at http://ailab.ahu.edu.cn:8087/ DXECPPI/index.jsp. Full article
Open AccessArticle TupA: A Tungstate Binding Protein in the Periplasm of Desulfovibrio alaskensis G20
Int. J. Mol. Sci. 2014, 15(7), 11783-11798; doi:10.3390/ijms150711783
Received: 31 March 2014 / Revised: 29 May 2014 / Accepted: 29 May 2014 / Published: 2 July 2014
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Abstract
The TupABC system is involved in the cellular uptake of tungsten and belongs to the ABC (ATP binding cassette)-type transporter systems. The TupA component is a periplasmic protein that binds tungstate anions, which are then transported through the membrane by the TupB component
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The TupABC system is involved in the cellular uptake of tungsten and belongs to the ABC (ATP binding cassette)-type transporter systems. The TupA component is a periplasmic protein that binds tungstate anions, which are then transported through the membrane by the TupB component using ATP hydrolysis as the energy source (the reaction catalyzed by the ModC component). We report the heterologous expression, purification, determination of affinity binding constants and crystallization of the Desulfovibrio alaskensis G20 TupA. The tupA gene (locus tag Dde_0234) was cloned in the pET46 Enterokinase/Ligation-Independent Cloning (LIC) expression vector, and the construct was used to transform BL21 (DE3) cells. TupA expression and purification were optimized to a final yield of 10 mg of soluble pure protein per liter of culture medium. Native polyacrylamide gel electrophoresis was carried out showing that TupA binds both tungstate and molybdate ions and has no significant interaction with sulfate, phosphate or perchlorate. Quantitative analysis of metal binding by isothermal titration calorimetry was in agreement with these results, but in addition, shows that TupA has higher affinity to tungstate than molybdate. The protein crystallizes in the presence of 30% (w/v) polyethylene glycol 3350 using the hanging-drop vapor diffusion method. The crystals diffract X-rays beyond 1.4 Å resolution and belong to the P21 space group, with cell parameters a = 52.25 Å, b = 42.50 Å, c = 54.71 Å, β = 95.43°. A molecular replacement solution was found, and the structure is currently under refinement. Full article
Open AccessArticle Direct Interaction between Selenoprotein P and Tubulin
Int. J. Mol. Sci. 2014, 15(6), 10199-10214; doi:10.3390/ijms150610199
Received: 19 March 2014 / Revised: 12 May 2014 / Accepted: 23 May 2014 / Published: 6 June 2014
Cited by 3 | PDF Full-text (3430 KB) | HTML Full-text | XML Full-text
Abstract
Selenium (Se), an essential trace element for human health, mainly exerts its biological function via selenoproteins. Among the 25 selenoproteins identified in human, selenoprotein P (SelP) is the only one that contains multiple selenocysteines (Sec) in the sequence, and has been suggested to
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Selenium (Se), an essential trace element for human health, mainly exerts its biological function via selenoproteins. Among the 25 selenoproteins identified in human, selenoprotein P (SelP) is the only one that contains multiple selenocysteines (Sec) in the sequence, and has been suggested to function as a Se transporter. Upon feeding a selenium-deficient diet, mice lacking SelP develop severe neurological dysfunction and exhibit widespread brainstem neurodegeneration, indicating an important role of SelP in normal brain function. To further elucidate the function of SelP in the brain, SelP was screened by the yeast two-hybrid system from a human fetal brain cDNA library for interactive proteins. Our results demonstrated that SelP interacts with tubulin, alpha 1a (TUBA1A). The interaction between SelP and tubulin was verified by fluorescence resonance energy transfer (FRET) and co-immunoprecipitation (co-IP) assays. We further found that SelP interacts with the C-terminus of tubulin by its His-rich domain, as demonstrated by FRET and Isothermal Titration Calorimetry (ITC) assays. The implications of the interaction between SelP and tubulin in the brain and in Alzheimer’s disease are discussed. Full article
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Open AccessArticle A New Criterion to Evaluate Water Vapor Interference in Protein Secondary Structural Analysis by FTIR Spectroscopy
Int. J. Mol. Sci. 2014, 15(6), 10018-10033; doi:10.3390/ijms150610018
Received: 16 February 2014 / Revised: 26 May 2014 / Accepted: 27 May 2014 / Published: 4 June 2014
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Abstract
Second derivative and Fourier self-deconvolution (FSD) are two commonly used techniques to resolve the overlapped component peaks from the often featureless amide I band in Fourier transform infrared (FTIR) curve-fitting approach for protein secondary structural analysis. Yet, the reliability of these two techniques
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Second derivative and Fourier self-deconvolution (FSD) are two commonly used techniques to resolve the overlapped component peaks from the often featureless amide I band in Fourier transform infrared (FTIR) curve-fitting approach for protein secondary structural analysis. Yet, the reliability of these two techniques is greatly affected by the omnipresent water vapor in the atmosphere. Several criteria are currently in use as quality controls to ensure the protein absorption spectrum is negligibly affected by water vapor interference. In this study, through a second derivative study of liquid water, we first argue that the previously established criteria cannot guarantee a reliable evaluation of water vapor interference due to a phenomenon that we refer to as sample’s absorbance-dependent water vapor interference. Then, through a comparative study of protein and liquid water, we show that a protein absorption spectrum can still be significantly affected by water vapor interference even though it satisfies the established criteria. At last, we propose to use the comparison between the second derivative spectra of protein and liquid water as a new criterion to better evaluate water vapor interference for more reliable second derivative and FSD treatments on the protein amide I band. Full article
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Open AccessTechnical Note A Cautionary Note on the Use of Split-YFP/BiFC in Plant Protein-Protein Interaction Studies
Int. J. Mol. Sci. 2014, 15(6), 9628-9643; doi:10.3390/ijms15069628
Received: 3 April 2014 / Revised: 17 April 2014 / Accepted: 20 May 2014 / Published: 30 May 2014
Cited by 15 | PDF Full-text (1208 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Since its introduction in plants 10 years ago, the bimolecular fluorescence complementation (BiFC) method, or split-YFP (yellow fluorescent protein), has gained popularity within the plant biology field as a method to study protein-protein interactions. BiFC is based on the restoration of fluorescence after
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Since its introduction in plants 10 years ago, the bimolecular fluorescence complementation (BiFC) method, or split-YFP (yellow fluorescent protein), has gained popularity within the plant biology field as a method to study protein-protein interactions. BiFC is based on the restoration of fluorescence after the two non-fluorescent halves of a fluorescent protein are brought together by a protein-protein interaction event. The major drawback of BiFC is that the fluorescent protein halves are prone to self-assembly independent of a protein-protein interaction event. To circumvent this problem, several modifications of the technique have been suggested, but these modifications have not lead to improvements in plant BiFC protocols. Therefore, it remains crucial to include appropriate internal controls. Our literature survey of recent BiFC studies in plants shows that most studies use inappropriate controls, and a qualitative rather than quantitative read-out of fluorescence. Therefore, we provide a cautionary note and beginner’s guideline for the setup of BiFC experiments, discussing each step of the protocol, including vector choice, plant expression systems, negative controls, and signal detection. In addition, we present our experience with BiFC with respect to self-assembly, peptide linkers, and incubation temperature. With this note, we aim to provide a guideline that will improve the quality of plant BiFC experiments. Full article
Open AccessArticle A Simple Three-Step Method for Design and Affinity Testing of New Antisense Peptides: An Example of Erythropoietin
Int. J. Mol. Sci. 2014, 15(6), 9209-9223; doi:10.3390/ijms15069209
Received: 30 March 2014 / Revised: 9 May 2014 / Accepted: 12 May 2014 / Published: 26 May 2014
Cited by 5 | PDF Full-text (545 KB) | HTML Full-text | XML Full-text
Abstract
Antisense peptide technology is a valuable tool for deriving new biologically active molecules and performing peptide–receptor modulation. It is based on the fact that peptides specified by the complementary (antisense) nucleotide sequences often bind to each other with a higher specificity and efficacy.
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Antisense peptide technology is a valuable tool for deriving new biologically active molecules and performing peptide–receptor modulation. It is based on the fact that peptides specified by the complementary (antisense) nucleotide sequences often bind to each other with a higher specificity and efficacy. We tested the validity of this concept on the example of human erythropoietin, a well-characterized and pharmacologically relevant hematopoietic growth factor. The purpose of the work was to present and test simple and efficient three-step procedure for the design of an antisense peptide targeting receptor-binding site of human erythropoietin. Firstly, we selected the carboxyl-terminal receptor binding region of the molecule (epitope) as a template for the antisense peptide modeling; Secondly, we designed an antisense peptide using mRNA transcription of the epitope sequence in the 3'→5' direction and computational screening of potential paratope structures with BLAST; Thirdly, we evaluated sense–antisense (epitope–paratope) peptide binding and affinity by means of fluorescence spectroscopy and microscale thermophoresis. Both methods showed similar Kd values of 850 and 816 µM, respectively. The advantages of the methods were: fast screening with a small quantity of the sample needed, and measurements done within the range of physicochemical parameters resembling physiological conditions. Antisense peptides targeting specific erythropoietin region(s) could be used for the development of new immunochemical methods. Selected antisense peptides with optimal affinity are potential lead compounds for the development of novel diagnostic substances, biopharmaceuticals and vaccines. Full article
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Open AccessArticle iHyd-PseAAC: Predicting Hydroxyproline and Hydroxylysine in Proteins by Incorporating Dipeptide Position-Specific Propensity into Pseudo Amino Acid Composition
Int. J. Mol. Sci. 2014, 15(5), 7594-7610; doi:10.3390/ijms15057594
Received: 7 February 2014 / Revised: 4 April 2014 / Accepted: 17 April 2014 / Published: 5 May 2014
Cited by 63 | PDF Full-text (1218 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Post-translational modifications (PTMs) play crucial roles in various cell functions and biological processes. Protein hydroxylation is one type of PTM that usually occurs at the sites of proline and lysine. Given an uncharacterized protein sequence, which site of its Pro (or Lys) can
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Post-translational modifications (PTMs) play crucial roles in various cell functions and biological processes. Protein hydroxylation is one type of PTM that usually occurs at the sites of proline and lysine. Given an uncharacterized protein sequence, which site of its Pro (or Lys) can be hydroxylated and which site cannot? This is a challenging problem, not only for in-depth understanding of the hydroxylation mechanism, but also for drug development, because protein hydroxylation is closely relevant to major diseases, such as stomach and lung cancers. With the avalanche of protein sequences generated in the post-genomic age, it is highly desired to develop computational methods to address this problem. In view of this, a new predictor called “iHyd-PseAAC” (identify hydroxylation by pseudo amino acid composition) was proposed by incorporating the dipeptide position-specific propensity into the general form of pseudo amino acid composition. It was demonstrated by rigorous cross-validation tests on stringent benchmark datasets that the new predictor is quite promising and may become a useful high throughput tool in this area. A user-friendly web-server for iHyd-PseAAC is accessible at http://app.aporc.org/iHyd-PseAAC/. Furthermore, for the convenience of the majority of experimental scientists, a step-by-step guide on how to use the web-server is given. Users can easily obtain their desired results by following these steps without the need of understanding the complicated mathematical equations presented in this paper just for its integrity. Full article
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Open AccessArticle Molecular Modelling Study of the PPARγ Receptor in Relation to the Mode of Action/Adverse Outcome Pathway Framework for Liver Steatosis
Int. J. Mol. Sci. 2014, 15(5), 7651-7666; doi:10.3390/ijms15057651
Received: 30 March 2014 / Revised: 18 April 2014 / Accepted: 21 April 2014 / Published: 5 May 2014
Cited by 6 | PDF Full-text (1396 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The comprehensive understanding of the precise mode of action and/or adverse outcome pathway (MoA/AOP) of chemicals has become a key step toward the development of a new generation of predictive toxicology tools. One of the challenges of this process is to test the
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The comprehensive understanding of the precise mode of action and/or adverse outcome pathway (MoA/AOP) of chemicals has become a key step toward the development of a new generation of predictive toxicology tools. One of the challenges of this process is to test the feasibility of the molecular modelling approaches to explore key molecular initiating events (MIE) within the integrated strategy of MoA/AOP characterisation. The description of MoAs leading to toxicity and liver damage has been the focus of much interest. Growing evidence underlines liver PPARγ ligand-dependent activation as a key MIE in the elicitation of liver steatosis. Synthetic PPARγ full agonists are of special concern, since they may trigger a number of adverse effects not observed with partial agonists. In this study, molecular modelling was performed based on the PPARγ complexes with full agonists extracted from the Protein Data Bank. The receptor binding pocket was analysed, and the specific ligand-receptor interactions were identified for the most active ligands. A pharmacophore model was derived, and the most important pharmacophore features were outlined and characterised in relation to their specific role for PPARγ activation. The results are useful for the characterisation of the chemical space of PPARγ full agonists and could facilitate the development of preliminary filtering rules for the effective virtual ligand screening of compounds with PPARγ full agonistic activity. Full article
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Open AccessReview The Oligomycin-Sensitivity Conferring Protein of Mitochondrial ATP Synthase: Emerging New Roles in Mitochondrial Pathophysiology
Int. J. Mol. Sci. 2014, 15(5), 7513-7536; doi:10.3390/ijms15057513
Received: 30 March 2014 / Revised: 18 April 2014 / Accepted: 21 April 2014 / Published: 30 April 2014
Cited by 15 | PDF Full-text (1853 KB) | HTML Full-text | XML Full-text
Abstract
The oligomycin-sensitivity conferring protein (OSCP) of the mitochondrial FOF1 ATP synthase has long been recognized to be essential for the coupling of proton transport to ATP synthesis. Located on top of the catalytic F1 sector, it makes stable contacts
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The oligomycin-sensitivity conferring protein (OSCP) of the mitochondrial FOF1 ATP synthase has long been recognized to be essential for the coupling of proton transport to ATP synthesis. Located on top of the catalytic F1 sector, it makes stable contacts with both F1 and the peripheral stalk, ensuring the structural and functional coupling between FO and F1, which is disrupted by the antibiotic, oligomycin. Recent data have established that OSCP is the binding target of cyclophilin (CyP) D, a well-characterized inducer of the mitochondrial permeability transition pore (PTP), whose opening can precipitate cell death. CyPD binding affects ATP synthase activity, and most importantly, it decreases the threshold matrix Ca2+ required for PTP opening, in striking analogy with benzodiazepine 423, an apoptosis-inducing agent that also binds OSCP. These findings are consistent with the demonstration that dimers of ATP synthase generate Ca2+-dependent currents with features indistinguishable from those of the PTP and suggest that ATP synthase is directly involved in PTP formation, although the underlying mechanism remains to be established. In this scenario, OSCP appears to play a fundamental role, sensing the signal(s) that switches the enzyme of life in a channel able to precipitate cell death. Full article
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Open AccessArticle Potential Activity of Fevicordin-A from Phaleria macrocarpa (Scheff) Boerl. Seeds as Estrogen Receptor Antagonist Based on Cytotoxicity and Molecular Modelling Studies
Int. J. Mol. Sci. 2014, 15(5), 7225-7249; doi:10.3390/ijms15057225
Received: 22 November 2013 / Revised: 10 January 2014 / Accepted: 15 January 2014 / Published: 25 April 2014
PDF Full-text (4603 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Fevicordin-A (FevA) isolated from Phaleria macrocarpa (Scheff) Boerl. seeds was evaluated for its potential anticancer activity by in vitro and in silico approaches. Cytotoxicity studies indicated that FevA was selective against cell lines of human breast adenocarcinoma (MCF-7) with an IC50 value
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Fevicordin-A (FevA) isolated from Phaleria macrocarpa (Scheff) Boerl. seeds was evaluated for its potential anticancer activity by in vitro and in silico approaches. Cytotoxicity studies indicated that FevA was selective against cell lines of human breast adenocarcinoma (MCF-7) with an IC50 value of 6.4 µM. At 11.2 µM, FevA resulted in 76.8% cell death of T-47D human breast cancer cell lines. Critical pharmacophore features amongst human Estrogen Receptor-α (hERα) antagonists were conserved in FevA with regard to a hypothesis that they could make notable contributions to its pharmacological activity. The binding stability as well as the dynamic behavior of FevA towards the hERα receptor in agonist and antagonist binding sites were probed using molecular dynamics (MD) simulation approach. Analysis of MD simulation suggested that the tail of FevA was accountable for the repulsion of the C-terminal of Helix-11 (H11) in both agonist and antagonist receptor forms. The flexibility of loop-534 indicated the ability to disrupt the hydrogen bond zipper network between H3 and H11 in hERα. In addition, MM/GBSA calculation from the molecular dynamic simulations also revealed a stronger binding affinity of FevA in antagonistic action as compared to that of agonistic action. Collectively, both the experimental and computational results indicated that FevA has potential as a candidate for an anticancer agent, which is worth promoting for further preclinical evaluation. Full article
Open AccessArticle Modeling and Docking Studies on Novel Mutants (K71L and T204V) of the ATPase Domain of Human Heat Shock 70 kDa Protein 1
Int. J. Mol. Sci. 2014, 15(4), 6797-6814; doi:10.3390/ijms15046797
Received: 25 January 2014 / Revised: 3 April 2014 / Accepted: 4 April 2014 / Published: 22 April 2014
Cited by 10 | PDF Full-text (1049 KB) | HTML Full-text | XML Full-text
Abstract
The purpose of exploring protein interactions between human adenovirus and heat shock protein 70 is to exploit a potentially synergistic interaction to enhance anti-tumoral efficacy and decrease toxicity in cancer treatment. However, the protein interaction of Hsp70 with E1A32 kDa of human adenovirus
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The purpose of exploring protein interactions between human adenovirus and heat shock protein 70 is to exploit a potentially synergistic interaction to enhance anti-tumoral efficacy and decrease toxicity in cancer treatment. However, the protein interaction of Hsp70 with E1A32 kDa of human adenovirus serotype 5 remains to be elucidated. In this study, two residues of ATPase domain of human heat shock 70 kDa protein 1 (PDB: 1 HJO) were mutated. 3D mutant models (K71L and T204V) using PyMol software were then constructed. The structures were evaluated by PROCHECK, ProQ, ERRAT, Verify 3D and ProSA modules. All evidence suggests that all protein models are acceptable and of good quality. The E1A32 kDa motif was retrieved from UniProt (P03255), as well as subjected to docking interaction with NBD, K71L and T204V, using the Autodock 4.2 program. The best lowest binding energy value of −9.09 kcal/mol was selected for novel T204V. Moreover, the protein-ligand complex structures were validated by RMSD, RMSF, hydrogen bonds and salt bridge analysis. This revealed that the T204V-E1A32 kDa motif complex was the most stable among all three complex structures. This study provides information about the interaction between Hsp70 and the E1A32 kDa motif, which emphasizes future perspectives to design rational drugs and vaccines in cancer therapy. Full article
Open AccessReview Towards Personalized Medicine Mediated by in Vitro Virus-Based Interactome Approaches
Int. J. Mol. Sci. 2014, 15(4), 6717-6724; doi:10.3390/ijms15046717
Received: 2 February 2014 / Revised: 24 March 2014 / Accepted: 9 April 2014 / Published: 21 April 2014
Cited by 4 | PDF Full-text (302 KB) | HTML Full-text | XML Full-text
Abstract
We have developed a simple in vitro virus (IVV) selection system based on cell-free co-translation, using a highly stable and efficient mRNA display method. The IVV system is applicable to the high-throughput and comprehensive analysis of proteins and protein–ligand interactions. Huge amounts of
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We have developed a simple in vitro virus (IVV) selection system based on cell-free co-translation, using a highly stable and efficient mRNA display method. The IVV system is applicable to the high-throughput and comprehensive analysis of proteins and protein–ligand interactions. Huge amounts of genomic sequence data have been generated over the last decade. The accumulated genetic alterations and the interactome networks identified within cells represent a universal feature of a disease, and knowledge of these aspects can help to determine the optimal therapy for the disease. The concept of the “integrome” has been developed as a means of integrating large amounts of data. We have developed an interactome analysis method aimed at providing individually-targeted health care. We also consider future prospects for this system. Full article
Open AccessReview Terminal Protection of Small Molecule-Linked DNA for Small Molecule–Protein Interaction Assays
Int. J. Mol. Sci. 2014, 15(4), 5221-5232; doi:10.3390/ijms15045221
Received: 25 January 2014 / Revised: 15 March 2014 / Accepted: 17 March 2014 / Published: 25 March 2014
Cited by 1 | PDF Full-text (527 KB) | HTML Full-text | XML Full-text
Abstract
Methods for the detection of specific interactions between diverse proteins and various small-molecule ligands are of significant importance in understanding the mechanisms of many critical physiological processes of organisms. The techniques also represent a major avenue to drug screening, molecular diagnostics,
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Methods for the detection of specific interactions between diverse proteins and various small-molecule ligands are of significant importance in understanding the mechanisms of many critical physiological processes of organisms. The techniques also represent a major avenue to drug screening, molecular diagnostics, and public safety monitoring. Terminal protection assay of small molecule-linked DNA is a demonstrated novel methodology which has exhibited great potential for the development of simple, sensitive, specific and high-throughput methods for the detection of small molecule–protein interactions. Herein, we review the basic principle of terminal protection assay, the development of associated methods, and the signal amplification strategies adopted for performance improving in small molecule–protein interaction assay. Full article
Open AccessReview Interactive Association of Drugs Binding to Human Serum Albumin
Int. J. Mol. Sci. 2014, 15(3), 3580-3595; doi:10.3390/ijms15033580
Received: 27 January 2014 / Revised: 17 February 2014 / Accepted: 18 February 2014 / Published: 27 February 2014
Cited by 30 | PDF Full-text (1231 KB) | HTML Full-text | XML Full-text
Abstract
Human serum albumin (HSA) is an abundant plasma protein, which attracts great interest in the pharmaceutical industry since it can bind a remarkable variety of drugs impacting their delivery and efficacy and ultimately altering the drug’s pharmacokinetic and pharmacodynamic properties. Additionally, HSA is
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Human serum albumin (HSA) is an abundant plasma protein, which attracts great interest in the pharmaceutical industry since it can bind a remarkable variety of drugs impacting their delivery and efficacy and ultimately altering the drug’s pharmacokinetic and pharmacodynamic properties. Additionally, HSA is widely used in clinical settings as a drug delivery system due to its potential for improving targeting while decreasing the side effects of drugs. It is thus of great importance from the viewpoint of pharmaceutical sciences to clarify the structure, function, and properties of HSA–drug complexes. This review will succinctly outline the properties of binding site of drugs in IIA subdomain within the structure of HSA. We will also give an overview on the binding characterization of interactive association of drugs to human serum albumin that may potentially lead to significant clinical applications. Full article
Open AccessArticle Multipose Binding in Molecular Docking
Int. J. Mol. Sci. 2014, 15(2), 2622-2645; doi:10.3390/ijms15022622
Received: 18 December 2013 / Revised: 17 January 2014 / Accepted: 21 January 2014 / Published: 14 February 2014
Cited by 8 | PDF Full-text (1872 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Molecular docking has been extensively applied in virtual screening of small molecule libraries for lead identification and optimization. A necessary prerequisite for successful differentiation between active and non-active ligands is the accurate prediction of their binding affinities in the complex by use of
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Molecular docking has been extensively applied in virtual screening of small molecule libraries for lead identification and optimization. A necessary prerequisite for successful differentiation between active and non-active ligands is the accurate prediction of their binding affinities in the complex by use of docking scoring functions. However, many studies have shown rather poor correlations between docking scores and experimental binding affinities. Our work aimed to improve this correlation by implementing a multipose binding concept in the docking scoring scheme. Multipose binding, i.e., the property of certain protein-ligand complexes to exhibit different ligand binding modes, has been shown to occur in nature for a variety of molecules. We conducted a high-throughput docking study and implemented multipose binding in the scoring procedure by considering multiple docking solutions in binding affinity prediction. In general, improvement of the agreement between docking scores and experimental data was observed, and this was most pronounced in complexes with large and flexible ligands and high binding affinities. Further developments of the selection criteria for docking solutions for each individual complex are still necessary for a general utilization of the multipose binding concept for accurate binding affinity prediction by molecular docking. Full article
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Open AccessArticle PhosphoTyrosyl Phosphatase Activator of Plasmodium falciparum: Identification of Its Residues Involved in Binding to and Activation of PP2A
Int. J. Mol. Sci. 2014, 15(2), 2431-2453; doi:10.3390/ijms15022431
Received: 4 December 2013 / Revised: 10 January 2014 / Accepted: 22 January 2014 / Published: 11 February 2014
Cited by 2 | PDF Full-text (2026 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In Plasmodium falciparum (Pf), the causative agent of the deadliest form of malaria, a tight regulation of phosphatase activity is crucial for the development of the parasite. In this study, we have identified and characterized PfPTPA homologous to PhosphoTyrosyl Phosphatase Activator, an activator
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In Plasmodium falciparum (Pf), the causative agent of the deadliest form of malaria, a tight regulation of phosphatase activity is crucial for the development of the parasite. In this study, we have identified and characterized PfPTPA homologous to PhosphoTyrosyl Phosphatase Activator, an activator of protein phosphatase 2A which is a major phosphatase involved in many biological processes in eukaryotic cells. The PfPTPA sequence analysis revealed that five out of six amino acids involved in interaction with PP2A in human are conserved in P. falciparum. Localization studies showed that PfPTPA and PfPP2A are present in the same compartment of blood stage parasites, suggesting a possible interaction of both proteins. In vitro binding and functional studies revealed that PfPTPA binds to and activates PP2A. Mutation studies showed that three residues (V283, G292 and M296) of PfPTPA are indispensable for the interaction and that the G292 residue is essential for its activity. In P. falciparum, genetic studies suggested the essentiality of PfPTPA for the completion of intraerythrocytic parasite lifecycle. Using Xenopus oocytes, we showed that PfPTPA blocked the G2/M transition. Taken together, our data suggest that PfPTPA could play a role in the regulation of the P. falciparum cell cycle through its PfPP2A regulatory activity. Full article
Open AccessShort Note Expression of a Deschampsia antarctica Desv. Polypeptide with Lipase Activity in a Pichia pastoris Vector
Int. J. Mol. Sci. 2014, 15(2), 2359-2367; doi:10.3390/ijms15022359
Received: 13 December 2013 / Revised: 18 January 2014 / Accepted: 28 January 2014 / Published: 7 February 2014
PDF Full-text (327 KB) | HTML Full-text | XML Full-text
Abstract
The current study isolated and characterized the Lip3F9 polypeptide sequence of Deschampsia antarctica Desv. (GeneBank Accession Number JX846628), which was found to be comprised of 291 base pairs and was, moreover, expressed in Pichia pastoris X-33 cells. The enzyme was secreted after 24
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The current study isolated and characterized the Lip3F9 polypeptide sequence of Deschampsia antarctica Desv. (GeneBank Accession Number JX846628), which was found to be comprised of 291 base pairs and was, moreover, expressed in Pichia pastoris X-33 cells. The enzyme was secreted after 24 h of P. pastoris culture incubation and through induction with methanol. The expressed protein showed maximum lipase activity (35 U/L) with an optimal temperature of 37 °C. The lipase-expressed enzyme lost 50% of its specific activity at 25 °C, a behavior characteristic of a psychrotolerant enzyme. Recombinant enzyme activity was measured in the presence of ionic and non-ionic detergents, and a decrease in enzyme activity was detected for all concentrations of ionic and non-ionic detergents assessed. Full article
Open AccessArticle Molecular Dynamics Simulation of the Crystallizable Fragment of IgG1—Insights for the Design of Fcabs
Int. J. Mol. Sci. 2014, 15(1), 438-455; doi:10.3390/ijms15010438
Received: 28 November 2013 / Revised: 19 December 2013 / Accepted: 27 December 2013 / Published: 2 January 2014
Cited by 4 | PDF Full-text (1697 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
An interesting format in the development of therapeutic monoclonal antibodies uses the crystallizable fragment of IgG1 as starting scaffold. Engineering of its structural loops allows generation of an antigen binding site. However, this might impair the molecule’s conformational stability, which can be overcome
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An interesting format in the development of therapeutic monoclonal antibodies uses the crystallizable fragment of IgG1 as starting scaffold. Engineering of its structural loops allows generation of an antigen binding site. However, this might impair the molecule’s conformational stability, which can be overcome by introducing stabilizing point mutations in the CH3 domains. These point mutations often affect the stability and unfolding behavior of both the CH2 and CH3 domains. In order to understand this cross-talk, molecular dynamics simulations of the domains of the Fc fragment of human IgG1 are reported. The structure of human IgG1-Fc obtained from X-ray crystallography is used as a starting point for simulations of the wild-type protein at two different pH values. The stabilizing effect of a single point mutation in the CH3 domain as well as the impact of the hinge region and the glycan tree structure connected to the CH2 domains is investigated. Regions of high local flexibility were identified as potential sites for engineering antigen binding sites. Obtained data are discussed with respect to the available X-ray structure of IgG1-Fc, directed evolution approaches that screen for stability and use of the scaffold IgG1-Fc in the design of antigen binding Fc proteins. Full article
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Open AccessArticle A Human XPC Protein Interactome—A Resource
Int. J. Mol. Sci. 2014, 15(1), 141-158; doi:10.3390/ijms15010141
Received: 6 November 2013 / Revised: 12 December 2013 / Accepted: 17 December 2013 / Published: 23 December 2013
Cited by 12 | PDF Full-text (382 KB) | HTML Full-text | XML Full-text
Abstract
Global genome nucleotide excision repair (GG-NER) is responsible for identifying and removing bulky adducts from non-transcribed DNA that result from damaging agents such as UV radiation and cisplatin. Xeroderma pigmentosum complementation group C (XPC) is one of the essential damage recognition proteins of
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Global genome nucleotide excision repair (GG-NER) is responsible for identifying and removing bulky adducts from non-transcribed DNA that result from damaging agents such as UV radiation and cisplatin. Xeroderma pigmentosum complementation group C (XPC) is one of the essential damage recognition proteins of the GG-NER pathway and its dysfunction results in xeroderma pigmentosum (XP), a disorder involving photosensitivity and a predisposition to cancer. To better understand the identification of DNA damage by XPC in the context of chromatin and the role of XPC in the pathogenesis of XP, we characterized the interactome of XPC using a high throughput yeast two-hybrid screening. Our screening showed 49 novel interactors of XPC involved in DNA repair and replication, proteolysis and post-translational modifications, transcription regulation, signal transduction, and metabolism. Importantly, we validated the XPC-OTUD4 interaction by co-IP and provided evidence that OTUD4 knockdown in human cells indeed affects the levels of ubiquitinated XPC, supporting a hypothesis that the OTUD4 deubiquitinase is involved in XPC recycling by cleaving the ubiquitin moiety. This high-throughput characterization of the XPC interactome provides a resource for future exploration and suggests that XPC may have many uncharacterized cellular functions. Full article
Open AccessArticle The C-Terminal Region of G72 Increases D-Amino Acid Oxidase Activity
Int. J. Mol. Sci. 2014, 15(1), 29-43; doi:10.3390/ijms15010029
Received: 28 October 2013 / Revised: 28 November 2013 / Accepted: 6 December 2013 / Published: 20 December 2013
Cited by 5 | PDF Full-text (1078 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The schizophrenia-related protein G72 plays a unique role in the regulation of D-amino acid oxidase (DAO) in great apes. Several psychiatric diseases, including schizophrenia and bipolar disorder, are linked to overexpression of DAO and G72. Whether G72 plays a positive or negative regulatory
[...] Read more.
The schizophrenia-related protein G72 plays a unique role in the regulation of D-amino acid oxidase (DAO) in great apes. Several psychiatric diseases, including schizophrenia and bipolar disorder, are linked to overexpression of DAO and G72. Whether G72 plays a positive or negative regulatory role in DAO activity, however, has been controversial. Exploring the molecular basis of the relationship between G72 and DAO is thus important to understand how G72 regulates DAO activity. We performed yeast two-hybrid experiments and determined enzymatic activity to identify potential sites in G72 involved in binding DAO. Our results demonstrate that residues 123–153 and 138–153 in the long isoform of G72 bind to DAO and enhance its activity by 22% and 32%, respectively. A docking exercise indicated that these G72 peptides can interact with loops in DAO that abut the entrance of the tunnel that substrate and cofactor must traverse to reach the active site. We propose that a unique gating mechanism underlies the ability of G72 to increase the activity of DAO. Because upregulation of DAO activity decreases d-serine levels, which may lead to psychiatric abnormalities, our results suggest a molecular mechanism involving interaction between DAO and the C-terminal region of G72 that can regulate N-methyl-d-aspartate receptor-mediated neurotransmission. Full article
Open AccessArticle Interaction of Classical Platinum Agents with the Monomeric and Dimeric Atox1 Proteins: A Molecular Dynamics Simulation Study
Int. J. Mol. Sci. 2014, 15(1), 75-99; doi:10.3390/ijms15010075
Received: 1 November 2013 / Revised: 5 December 2013 / Accepted: 12 December 2013 / Published: 20 December 2013
Cited by 2 | PDF Full-text (2474 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
We carried out molecular dynamics simulations and free energy calculations for a series of binary and ternary models of the cisplatin, transplatin and oxaliplatin agents binding to a monomeric Atox1 protein and a dimeric Atox1 protein to investigate their interaction mechanisms. All three
[...] Read more.
We carried out molecular dynamics simulations and free energy calculations for a series of binary and ternary models of the cisplatin, transplatin and oxaliplatin agents binding to a monomeric Atox1 protein and a dimeric Atox1 protein to investigate their interaction mechanisms. All three platinum agents could respectively combine with the monomeric Atox1 protein and the dimeric Atox1 protein to form a stable binary and ternary complex due to the covalent interaction of the platinum center with the Atox1 protein. The results suggested that the extra interaction from the oxaliplatin ligand–Atox1 protein interface increases its affinity only for the OxaliPt + Atox1 model. The binding of the oxaliplatin agent to the Atox1 protein might cause larger deformation of the protein than those of the cisplatin and transplatin agents due to the larger size of the oxaliplatin ligand. However, the extra interactions to facilitate the stabilities of the ternary CisPt + 2Atox1 and OxaliPt + 2Atox1 models come from the α1 helices and α2-β4 loops of the Atox1 protein–Atox1 protein interface due to the cis conformation of the platinum agents. The combinations of two Atox1 proteins in an asymmetric way in the three ternary models were analyzed. These investigations might provide detailed information for understanding the interaction mechanism of the platinum agents binding to the Atox1 protein in the cytoplasm. Full article
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Open AccessArticle Analysis of the Binding Sites of Porcine Sialoadhesin Receptor with PRRSV
Int. J. Mol. Sci. 2013, 14(12), 23955-23979; doi:10.3390/ijms141223955
Received: 13 September 2013 / Revised: 13 November 2013 / Accepted: 19 November 2013 / Published: 9 December 2013
Cited by 3 | PDF Full-text (1275 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Porcine reproductive and respiratory syndrome virus (PRRSV) can infect pigs and cause enormous economic losses to the pig industry worldwide. Porcine sialoadhesin (pSN) and CD163 have been identified as key viral receptors on porcine alveolar macrophages (PAM), a main target cell infected by
[...] Read more.
Porcine reproductive and respiratory syndrome virus (PRRSV) can infect pigs and cause enormous economic losses to the pig industry worldwide. Porcine sialoadhesin (pSN) and CD163 have been identified as key viral receptors on porcine alveolar macrophages (PAM), a main target cell infected by PRRSV. In this study, the protein structures of amino acids 1–119 from the pSN and cSN (cattle sialoadhesin) N-termini (excluding the 19-amino acid signal peptide) were modeled via homology modeling based on mSN (mouse sialoadhesin) template structures using bioinformatics tools. Subsequently, pSN and cSN homology structures were superposed onto the mSN protein structure to predict the binding sites of pSN. As a validation experiment, the SN N-terminus (including the wild-type and site-directed-mutant-types of pSN and cSN) was cloned and expressed as a SN-GFP chimera protein. The binding activity between SN and PRRSV was confirmed by WB (Western blotting), FAR-WB (far Western blotting), ELISA (enzyme-linked immunosorbent assay) and immunofluorescence assay. We found that the S107 amino acid residue in the pSN N-terminal played a crucial role in forming a special cavity, as well as a hydrogen bond for enhancing PRRSV binding during PRRSV infection. S107 may be glycosylated during PRRSV infection and may also be involved in forming the cavity for binding PRRSV along with other sites, including W2, Y44, S45, R97, R105, W106 and V109. Additionally, S107 might also be important for pSN binding with PRRSV. However, the function of these binding sites must be confirmed by further studies. Full article
Open AccessArticle Screening of Peptide Ligands for Pyrroloquinoline Quinone Glucose Dehydrogenase Using Antagonistic Template-Based Biopanning
Int. J. Mol. Sci. 2013, 14(12), 23244-23256; doi:10.3390/ijms141223244
Received: 31 July 2013 / Revised: 31 October 2013 / Accepted: 11 November 2013 / Published: 25 November 2013
Cited by 1 | PDF Full-text (599 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
We have developed a novel method, antagonistic template-based biopanning, for screening peptide ligands specifically recognizing local tertiary protein structures. We chose water-soluble pyrroloquinoline quinone (PQQ) glucose dehydrogenase (GDH-B) as a model enzyme for this screening. Two GDH-B mutants were constructed as antagonistic templates;
[...] Read more.
We have developed a novel method, antagonistic template-based biopanning, for screening peptide ligands specifically recognizing local tertiary protein structures. We chose water-soluble pyrroloquinoline quinone (PQQ) glucose dehydrogenase (GDH-B) as a model enzyme for this screening. Two GDH-B mutants were constructed as antagonistic templates; these have some point mutations to induce disruption of local tertiary structures within the loop regions that are located at near glucose-binding pocket. Using phage display, we selected 12-mer peptides that specifically bound to wild-type GDH-B but not to the antagonistic templates. Consequently, a peptide ligand showing inhibitory activity against GDH-B was obtained. These results demonstrate that the antagonistic template-based biopanning is useful for screening peptide ligands recognizing the specific local tertiary structure of proteins. Full article
Open AccessArticle Identification of Novel Small Molecules as Inhibitors of Hepatitis C Virus by Structure-Based Virtual Screening
Int. J. Mol. Sci. 2013, 14(11), 22845-22856; doi:10.3390/ijms141122845
Received: 12 September 2013 / Revised: 6 November 2013 / Accepted: 7 November 2013 / Published: 20 November 2013
Cited by 6 | PDF Full-text (505 KB) | HTML Full-text | XML Full-text
Abstract
Hepatitis C virus (HCV) NS3/NS4A serine protease is essential for viral replication, which is regarded as a promising drug target for developing direct-acting anti-HCV agents. In this study, sixteen novel compounds with cell-based HCV replicon activity ranging from 3.0 to 28.2 μM (IC
[...] Read more.
Hepatitis C virus (HCV) NS3/NS4A serine protease is essential for viral replication, which is regarded as a promising drug target for developing direct-acting anti-HCV agents. In this study, sixteen novel compounds with cell-based HCV replicon activity ranging from 3.0 to 28.2 μM (IC50) were successfully identified by means of structure-based virtual screening. Compound 5 and compound 11, with an IC50 of 3.0 μM and 5.1 μM, respectively, are the two most potent molecules with low cytotoxicity. Full article
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Open AccessArticle Acidic Residue Glu199 Increases SUMOylation Level of Nuclear Hormone Receptor NR5A1
Int. J. Mol. Sci. 2013, 14(11), 22331-22345; doi:10.3390/ijms141122331
Received: 9 October 2013 / Revised: 1 November 2013 / Accepted: 5 November 2013 / Published: 13 November 2013
Cited by 2 | PDF Full-text (356 KB) | HTML Full-text | XML Full-text
Abstract
Steroidogenic factor 1 (NR5A1/SF1) is a well-known master regulator in controlling adrenal and sexual development, as well as regulating numerous genes involved in adrenal and gonadal steroidogenesis. Several studies including ours have demonstrated that NR5A1 can be SUMOylated on lysine 194 (K194, the
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Steroidogenic factor 1 (NR5A1/SF1) is a well-known master regulator in controlling adrenal and sexual development, as well as regulating numerous genes involved in adrenal and gonadal steroidogenesis. Several studies including ours have demonstrated that NR5A1 can be SUMOylated on lysine 194 (K194, the major site) and lysine 119 (K119, the minor site), and the cycle of SUMOylation regulates NR5A1’s transcriptional activity. An extended consensus negatively charged amino acid-dependent SUMOylation motif (NDSM) enhances the specificity of substrate modification by SUMO has been reported; however, the mechanism of NDSM for NR5A1 remains to be clarified. In this study, we investigated the functional significance of the acidic residue located downstream from the core consensus SUMO site of NR5A1. Here we report that E199A (glutamic acid was replaced with alanine) of NR5A1 reduced, but not completely abolished, its SUMOylation level. We next characterized the functional role of NR5A1 E199A on target gene expression and protein levels. We found that E199A alone, as well as combination with K194R, increased Mc2r and Cyp19a1 reporter activities. Moreover, E199A alone as well as combination with K194R enhanced NR5A1-mediated STAR protein levels in mouse adrenocortical cancer Y1 cells. We also observed that E199A increased interaction of NR5A1 with CDK7 and SRC1. Overall, we provide the evidence that the acidic residue (E199) located downstream from the core consensus SUMO site of NR5A1 is, at least in part, required for SUMOylation of NR5A1 and for its mediated target gene and protein expression. Full article
Open AccessReview Maternal Embryonic Leucine Zipper Kinase (MELK): A Novel Regulator in Cell Cycle Control, Embryonic Development, and Cancer
Int. J. Mol. Sci. 2013, 14(11), 21551-21560; doi:10.3390/ijms141121551
Received: 26 September 2013 / Revised: 16 October 2013 / Accepted: 22 October 2013 / Published: 31 October 2013
Cited by 7 | PDF Full-text (197 KB) | HTML Full-text | XML Full-text
Abstract
Maternal embryonic leucine zipper kinase (MELK) functions as a modulator of intracellular signaling and affects various cellular and biological processes, including cell cycle, cell proliferation, apoptosis, spliceosome assembly, gene expression, embryonic development, hematopoiesis, and oncogenesis. In these cellular processes, MELK functions by binding
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Maternal embryonic leucine zipper kinase (MELK) functions as a modulator of intracellular signaling and affects various cellular and biological processes, including cell cycle, cell proliferation, apoptosis, spliceosome assembly, gene expression, embryonic development, hematopoiesis, and oncogenesis. In these cellular processes, MELK functions by binding to numerous proteins. In general, the effects of multiple protein interactions with MELK are oncogenic in nature, and the overexpression of MELK in kinds of cancer provides some evidence that it may be involved in tumorigenic process. In this review, our current knowledge of MELK function and recent discoveries in MELK signaling pathway were discussed. The regulation of MELK in cancers and its potential as a therapeutic target were also described. Full article
Open AccessArticle Investigations of the Binding of [Pt2(DTBPA)Cl2](II) and [Pt2(TPXA)Cl2](II) to DNA via Various Cross-Linking Modes
Int. J. Mol. Sci. 2013, 14(10), 19556-19586; doi:10.3390/ijms141019556
Received: 11 July 2013 / Revised: 14 August 2013 / Accepted: 10 September 2013 / Published: 26 September 2013
Cited by 2 | PDF Full-text (5891 KB) | HTML Full-text | XML Full-text
Abstract
We have constructed models for a series of platinum-DNA adducts that represent the binding of two agents, [Pt2(DTBPA)Cl2](II) and [Pt2(TPXA)Cl2](II), to DNA via inter- and intra-strand cross-linking, and carried out molecular dynamics simulations and DNA
[...] Read more.
We have constructed models for a series of platinum-DNA adducts that represent the binding of two agents, [Pt2(DTBPA)Cl2](II) and [Pt2(TPXA)Cl2](II), to DNA via inter- and intra-strand cross-linking, and carried out molecular dynamics simulations and DNA conformational dynamics calculations. The effects of trans- and cis-configurations of the centers of these di-nuclear platinum agents, and of different bridging linkers, have been investigated on the conformational distortions of platinum-DNA adducts formed via inter- and intra-strand cross-links. The results demonstrate that the DNA conformational distortions for the various platinum-DNA adducts with differing cross-linking modes are greatly influenced by the difference between the platinum-platinum distance for the platinum agent and the platinum-bound N7–N7 distance for the DNA molecule, and by the flexibility of the bridging linkers in the platinum agent. However, the effects of trans/cis-configurations of the platinum-centers on the DNA conformational distortions in the platinum-DNA adducts depend on the inter- and intra-strand cross-linking modes. In addition, we discuss the relevance of DNA base motions, including opening, shift and roll, to the changes in the parameters of the DNA major and minor grooves caused by binding of the platinum agent. Full article
Open AccessArticle Basic Amino Acid Residues of Human Eosinophil Derived Neurotoxin Essential for Glycosaminoglycan Binding
Int. J. Mol. Sci. 2013, 14(9), 19067-19085; doi:10.3390/ijms140919067
Received: 15 August 2013 / Revised: 6 September 2013 / Accepted: 11 September 2013 / Published: 16 September 2013
PDF Full-text (1414 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Human eosinophil derived neurotoxin (EDN), a granule protein secreted by activated eosinophils, is a biomarker for asthma in children. EDN belongs to the human RNase A superfamily possessing both ribonucleolytic and antiviral activities. EDN interacts with heparin oligosaccharides and heparin sulfate proteoglycans on
[...] Read more.
Human eosinophil derived neurotoxin (EDN), a granule protein secreted by activated eosinophils, is a biomarker for asthma in children. EDN belongs to the human RNase A superfamily possessing both ribonucleolytic and antiviral activities. EDN interacts with heparin oligosaccharides and heparin sulfate proteoglycans on bronchial epithelial Beas-2B cells. In this study, we demonstrate that the binding of EDN to cells requires cell surface glycosaminoglycans (GAGs), and the binding strength between EDN and GAGs depends on the sulfation levels of GAGs. Furthermore, in silico computer modeling and in vitro binding assays suggest critical roles for the following basic amino acids located within heparin binding regions (HBRs) of EDN 34QRRCKN39 (HBR1), 65NKTRKN70 (HBR2), and 113NRDQRRD119 (HBR3) and in particular Arg35, Arg36, and Arg38 within HBR1, and Arg114 and Arg117 within HBR3. Our data suggest that sulfated GAGs play a major role in EDN binding, which in turn may be related to the cellular effects of EDN. Full article
Open AccessArticle Trastuzumab-Peptide Interactions: Mechanism and Application in Structure-Based Ligand Design
Int. J. Mol. Sci. 2013, 14(8), 16836-16850; doi:10.3390/ijms140816836
Received: 15 July 2013 / Revised: 31 July 2013 / Accepted: 6 August 2013 / Published: 15 August 2013
Cited by 4 | PDF Full-text (1152 KB) | HTML Full-text | XML Full-text
Abstract
Understanding of protein-ligand interactions and its influences on protein stability is necessary in the research on all biological processes and correlative applications, for instance, the appropriate affinity ligand design for the purification of bio-drugs. In this study, computational methods were applied to identify
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Understanding of protein-ligand interactions and its influences on protein stability is necessary in the research on all biological processes and correlative applications, for instance, the appropriate affinity ligand design for the purification of bio-drugs. In this study, computational methods were applied to identify binding site interaction details between trastuzumab and its natural receptor. Trastuzumab is an approved antibody used in the treatment of human breast cancer for patients whose tumors overexpress the HER2 (human epidermal growth factor receptor 2) protein. However, rational design of affinity ligands to keep the stability of protein during the binding process is still a challenge. Herein, molecular simulations and quantum mechanics were used on protein-ligand interaction analysis and protein ligand design. We analyzed the structure of the HER2-trastuzumab complex by molecular dynamics (MD) simulations. The interaction energies of the mutated peptides indicate that trastuzumab binds to ligand through electrostatic and hydrophobic interactions. Quantitative investigation of interactions shows that electrostatic interactions play the most important role in the binding of the peptide ligand. Prime/MM-GBSA calculations were carried out to predict the binding affinity of the designed peptide ligands. A high binding affinity and specificity peptide ligand is designed rationally with equivalent interaction energy to the wild-type octadecapeptide. The results offer new insights into affinity ligand design. Full article
Open AccessArticle Disease-Causing Mutations in BEST1 Gene Are Associated with Altered Sorting of Bestrophin-1 Protein
Int. J. Mol. Sci. 2013, 14(7), 15121-15140; doi:10.3390/ijms140715121
Received: 14 May 2013 / Revised: 2 July 2013 / Accepted: 4 July 2013 / Published: 22 July 2013
Cited by 10 | PDF Full-text (4016 KB) | HTML Full-text | XML Full-text
Abstract
Mutations in BEST1 gene, encoding the bestrophin-1 (Best1) protein are associated with macular dystrophies. Best1 is predominantly expressed in the retinal pigment epithelium (RPE), and is inserted in its basolateral membrane. We investigated the cellular localization in polarized MDCKII cells of disease-associated Best1
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Mutations in BEST1 gene, encoding the bestrophin-1 (Best1) protein are associated with macular dystrophies. Best1 is predominantly expressed in the retinal pigment epithelium (RPE), and is inserted in its basolateral membrane. We investigated the cellular localization in polarized MDCKII cells of disease-associated Best1 mutant proteins to study specific sorting motifs of Best1. Real-time PCR and western blots for endogenous expression of BEST1 in MDCK cells were performed. Best1 mutant constructs were generated using site-directed mutagenesis and transfected in MDCK cells. For protein sorting, confocal microscopy studies, biotinylation assays and statistical methods for quantification of mislocalization were used. Analysis of endogenous expression of BEST1 in MDCK cells revealed the presence of BEST1 transcript but no protein. Confocal microscopy and quantitative analyses indicate that transfected normal human Best1 displays a basolateral localization in MDCK cells, while cell sorting of several Best1 mutants (Y85H, Q96R, L100R, Y227N, Y227E) was altered. In contrast to constitutively active Y227E, constitutively inactive Y227F Best1 mutant localized basolaterally similar to the normal Best1 protein. Our data suggest that at least three basolateral sorting motifs might be implicated in proper Best1 basolateral localization. In addition, non-phosphorylated tyrosine 227 could play a role for basolateral delivery. Full article
Open AccessArticle Dependence of Interaction Free Energy between Solutes on an External Electrostatic Field
Int. J. Mol. Sci. 2013, 14(7), 14408-14425; doi:10.3390/ijms140714408
Received: 24 May 2013 / Revised: 27 June 2013 / Accepted: 2 July 2013 / Published: 11 July 2013
Cited by 4 | PDF Full-text (1160 KB) | HTML Full-text | XML Full-text
Abstract
To explore the athermal effect of an external electrostatic field on the stabilities of protein conformations and the binding affinities of protein-protein/ligand interactions, the dependences of the polar and hydrophobic interactions on the external electrostatic field, −Eext, were studied using
[...] Read more.
To explore the athermal effect of an external electrostatic field on the stabilities of protein conformations and the binding affinities of protein-protein/ligand interactions, the dependences of the polar and hydrophobic interactions on the external electrostatic field, −Eext, were studied using molecular dynamics (MD) simulations. By decomposing Eext into, along, and perpendicular to the direction formed by the two solutes, the effect of Eext on the interactions between these two solutes can be estimated based on the effects from these two components. Eext was applied along the direction of the electric dipole formed by two solutes with opposite charges. The attractive interaction free energy between these two solutes decreased for solutes treated as point charges. In contrast, the attractive interaction free energy between these two solutes increased, as observed by MD simulations, for Eext = 40 or 60 MV/cm. Eext was applied perpendicular to the direction of the electric dipole formed by these two solutes. The attractive interaction free energy was increased for Eext = 100 MV/cm as a result of dielectric saturation. The force on the solutes along the direction of Eext computed from MD simulations was greater than that estimated from a continuum solvent in which the solutes were treated as point charges. To explore the hydrophobic interactions, Eext was applied to a water cluster containing two neutral solutes. The repulsive force between these solutes was decreased/increased for Eext along/perpendicular to the direction of the electric dipole formed by these two solutes. Full article
Open AccessArticle Phthalic Acid Chemical Probes Synthesized for Protein-Protein Interaction Analysis
Int. J. Mol. Sci. 2013, 14(7), 12914-12930; doi:10.3390/ijms140712914
Received: 2 May 2013 / Revised: 7 June 2013 / Accepted: 7 June 2013 / Published: 24 June 2013
Cited by 3 | PDF Full-text (1717 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Plasticizers are additives that are used to increase the flexibility of plastic during manufacturing. However, in injection molding processes, plasticizers cannot be generated with monomers because they can peel off from the plastics into the surrounding environment, water, or food, or become attached
[...] Read more.
Plasticizers are additives that are used to increase the flexibility of plastic during manufacturing. However, in injection molding processes, plasticizers cannot be generated with monomers because they can peel off from the plastics into the surrounding environment, water, or food, or become attached to skin. Among the various plasticizers that are used, 1,2-benzenedicarboxylic acid (phthalic acid) is a typical precursor to generate phthalates. In addition, phthalic acid is a metabolite of diethylhexyl phthalate (DEHP). According to Gene_Ontology gene/protein database, phthalates can cause genital diseases, cardiotoxicity, hepatotoxicity, nephrotoxicity, etc. In this study, a silanized linker (3-aminopropyl triethoxyslane, APTES) was deposited on silicon dioxides (SiO2) particles and phthalate chemical probes were manufactured from phthalic acid and APTES–SiO2. These probes could be used for detecting proteins that targeted phthalic acid and for protein-protein interactions. The phthalic acid chemical probes we produced were incubated with epithelioid cell lysates of normal rat kidney (NRK-52E cells) to detect the interactions between phthalic acid and NRK-52E extracted proteins. These chemical probes interacted with a number of chaperones such as protein disulfide-isomerase A6, heat shock proteins, and Serpin H1. Ingenuity Pathways Analysis (IPA) software showed that these chemical probes were a practical technique for protein-protein interaction analysis. Full article

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