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Special Issue "Recent Developments on Protein–Ligand Interactions: From Structure, Function to Applications"

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: 31 January 2020.

Special Issue Editor

Prof. Dr. Alexandre G. de Brevern
E-Mail Website
Guest Editor
Department of Biological Research on the Red Blood Cells, INTS, Paris Diderot University, Paris, France
Interests: structural bioinformatics; bioinformatics; next-generation sequence; drug design; biostatistics

Special Issue Information

Dear Colleagues,

Protein–ligand interactions play a fundamental role in most major biological functions, but also in drug discovery. With the increasing structural information of proteins and protein–ligand complexes, molecular modelling, molecular dynamics, and chemoinformatics approaches are often required for the efficient analysis of a large number of such complexes and to provide insights. Similarly, numerous computational approaches have been developed to characterize and use the knowledge of such interactions, which can lead to drug candidates. For instance, one main application is to identify tractable chemical startpoints that non-covalently modulate the activity of a biological molecule. This new information brings questions that affect chemistry, biology, and even poses specific computer problems. Papers related to any aspect of protein–ligand analysis and/or prediction using computational approaches, as well as new developments dedicated to these tasks, will be considered for this Special Issue.

Prof. Dr. Alexandre G. de Brevern
Guest Editor

Manuscript Submission Information

Manuscripts should 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. Manuscripts can be submitted until the deadline. 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 the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • protein–ligand analysis
  • protein–ligand interaction fingerprints
  • structure protein–ligand interaction relationships
  • structure–activity relationships
  • molecular modeling
  • molecular dynamics
  • chemogenomics
  • chemical biology
  • drug discovery and design
  • fragment-based lead discovery
  • 2D interaction maps
  • 3D activity
  • hot spots
  • pharmacophore

Published Papers (10 papers)

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Research

Open AccessArticle
DockNmine, a Web Portal to Assemble and Analyse Virtual and Experimental Interaction Data
Int. J. Mol. Sci. 2019, 20(20), 5062; https://doi.org/10.3390/ijms20205062 - 12 Oct 2019
Abstract
Scientists have to perform multiple experiments producing qualitative and quantitative data to determine if a compound is able to bind to a given target. Due to the large diversity of the potential ligand chemical space, the possibility of experimentally exploring a lot of [...] Read more.
Scientists have to perform multiple experiments producing qualitative and quantitative data to determine if a compound is able to bind to a given target. Due to the large diversity of the potential ligand chemical space, the possibility of experimentally exploring a lot of compounds on a target rapidly becomes out of reach. Scientists therefore need to use virtual screening methods to determine the putative binding mode of ligands on a protein and then post-process the raw docking experiments with a dedicated scoring function in relation with experimental data. Two of the major difficulties for comparing docking predictions with experiments mostly come from the lack of transferability of experimental data and the lack of standardisation in molecule names. Although large portals like PubChem or ChEMBL are available for general purpose, there is no service allowing a formal expert annotation of both experimental data and docking studies. To address these issues, researchers build their own collection of data in flat files, often in spreadsheets, with limited possibilities of extensive annotations or standardisation of ligand descriptions allowing cross-database retrieval. We have conceived the dockNmine platform to provide a service allowing an expert and authenticated annotation of ligands and targets. First, this portal allows a scientist to incorporate controlled information in the database using reference identifiers for the protein (Uniprot ID) and the ligand (SMILES description), the data and the publication associated to it. Second, it allows the incorporation of docking experiments using forms that automatically parse useful parameters and results. Last, the web interface provides a lot of pre-computed outputs to assess the degree of correlations between docking experiments and experimental data. Full article
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Open AccessArticle
Analysis of Procollagen C-Proteinase Enhancer-1/Glycosaminoglycan Binding Sites and of the Potential Role of Calcium Ions in the Interaction
Int. J. Mol. Sci. 2019, 20(20), 5021; https://doi.org/10.3390/ijms20205021 - 10 Oct 2019
Abstract
In this study, we characterize the interactions between the extracellular matrix protein, procollagen C-proteinase enhancer-1 (PCPE-1), and glycosaminoglycans (GAGs), which are linear anionic periodic polysaccharides. We applied molecular modeling approaches to build a structural model of full-length PCPE-1, which is not experimentally available, [...] Read more.
In this study, we characterize the interactions between the extracellular matrix protein, procollagen C-proteinase enhancer-1 (PCPE-1), and glycosaminoglycans (GAGs), which are linear anionic periodic polysaccharides. We applied molecular modeling approaches to build a structural model of full-length PCPE-1, which is not experimentally available, to predict GAG binding poses for various GAG lengths, types and sulfation patterns, and to determine the effect of calcium ions on the binding. The computational data are analyzed and discussed in the context of the experimental results previously obtained using surface plasmon resonance binding assays. We also provide experimental data on PCPE-1/GAG interactions obtained using inhibition assays with GAG oligosaccharides ranging from disaccharides to octadecasaccharides. Our results predict the localization of GAG-binding sites at the amino acid residue level onto PCPE-1 and is the first attempt to describe the effects of ions on protein-GAG binding using modeling approaches. In addition, this study allows us to get deeper insights into the in silico methodology challenges and limitations when applied to GAG-protein interactions. Full article
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Open AccessArticle
Application of the Movable Type Free Energy Method to the Caspase-Inhibitor Binding Affinity Study
Int. J. Mol. Sci. 2019, 20(19), 4850; https://doi.org/10.3390/ijms20194850 - 29 Sep 2019
Abstract
Many studies have provided evidence suggesting that caspases not only contribute to the neurodegeneration associated with Alzheimer’s disease (AD) but also play essential roles in promoting the underlying pathology of this disease. Studies regarding the caspase inhibition draw researchers’ attention through time due [...] Read more.
Many studies have provided evidence suggesting that caspases not only contribute to the neurodegeneration associated with Alzheimer’s disease (AD) but also play essential roles in promoting the underlying pathology of this disease. Studies regarding the caspase inhibition draw researchers’ attention through time due to its therapeutic value in the treatment of AD. In this work, we apply the “Movable Type” (MT) free energy method, a Monte Carlo sampling method extrapolating the binding free energy by simulating the partition functions for both free-state and bound-state protein and ligand configurations, to the caspase-inhibitor binding affinity study. Two test benchmarks are introduced to examine the robustness and sensitivity of the MT method concerning the caspase inhibition complexing. The first benchmark employs a large-scale test set including more than a hundred active inhibitors binding to caspase-3. The second benchmark includes several smaller test sets studying the relative binding free energy differences for minor structural changes at the caspase-inhibitor interaction interfaces. Calculation results show that the RMS errors for all test sets are below 1.5 kcal/mol compared to the experimental binding affinity values, demonstrating good performance in simulating the caspase-inhibitor complexing. For better understanding the protein-ligand interaction mechanism, we then take a closer look at the global minimum binding modes and free-state ligand conformations to study two pairs of caspase-inhibitor complexes with (1) different caspase targets binding to the same inhibitor, and (2) different polypeptide inhibitors targeting the same caspase target. By comparing the contact maps at the binding site of different complexes, we revealed how small structural changes affect the caspase-inhibitor interaction energies. Overall, this work provides a new free energy approach for studying the caspase inhibition, with structural insight revealed for both free-state and bound-state molecular configurations. Full article
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Open AccessArticle
Investigation of Phospholipase Cγ1 Interaction with SLP76 Using Molecular Modeling Methods for Identifying Novel Inhibitors
Int. J. Mol. Sci. 2019, 20(19), 4721; https://doi.org/10.3390/ijms20194721 - 23 Sep 2019
Abstract
The enzyme phospholipase C gamma 1 (PLCγ1) has been identified as a potential drug target of interest for various pathological conditions such as immune disorders, systemic lupus erythematosus, and cancers. Targeting its SH3 domain has been recognized as an efficient pharmacological approach for [...] Read more.
The enzyme phospholipase C gamma 1 (PLCγ1) has been identified as a potential drug target of interest for various pathological conditions such as immune disorders, systemic lupus erythematosus, and cancers. Targeting its SH3 domain has been recognized as an efficient pharmacological approach for drug discovery against PLCγ1. Therefore, for the first time, a combination of various biophysical methods has been employed to shed light on the atomistic interactions between PLCγ1 and its known binding partners. Indeed, molecular modeling of PLCγ1 with SLP76 peptide and with previously reported inhibitors (ritonavir, anethole, daunorubicin, diflunisal, and rosiglitazone) facilitated the identification of the common critical residues (Gln805, Arg806, Asp808, Glu809, Asp825, Gly827, and Trp828) as well as the quantification of their interaction through binding energies calculations. These features are in agreement with previous experimental data. Such an in depth biophysical analysis of each complex provides an opportunity to identify new inhibitors through pharmacophore mapping, molecular docking and MD simulations. From such a systematic procedure, a total of seven compounds emerged as promising inhibitors, all characterized by a strong binding with PLCγ1 and a comparable or higher binding affinity to ritonavir (∆Gbind < −25 kcal/mol), one of the most potent inhibitor reported till now. Full article
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Open AccessArticle
A Galactoside-Binding Protein Tricked into Binding Unnatural Pyranose Derivatives: 3-Deoxy-3-Methyl-Gulosides Selectively Inhibit Galectin-1
Int. J. Mol. Sci. 2019, 20(15), 3786; https://doi.org/10.3390/ijms20153786 - 02 Aug 2019
Abstract
Galectins are a family of galactoside-recognizing proteins involved in different galectin-subtype-specific inflammatory and tumor-promoting processes, which motivates the development of inhibitors that are more selective galectin inhibitors than natural ligand fragments. Here, we describe the synthesis and evaluation of 3-C-methyl-gulopyranoside derivatives [...] Read more.
Galectins are a family of galactoside-recognizing proteins involved in different galectin-subtype-specific inflammatory and tumor-promoting processes, which motivates the development of inhibitors that are more selective galectin inhibitors than natural ligand fragments. Here, we describe the synthesis and evaluation of 3-C-methyl-gulopyranoside derivatives and their evaluation as galectin inhibitors. Methyl 3-deoxy-3-C-(hydroxymethyl)-β-d-gulopyranoside showed 7-fold better affinity for galectin-1 than the natural monosaccharide fragment analog methyl β-d-galactopyranoside, as well as a high selectivity over galectin-2, 3, 4, 7, 8, and 9. Derivatization of the 3-C-hydroxymethyl into amides gave gulosides with improved selectivities and affinities; methyl 3-deoxy-3-C-(methyl-2,3,4,5,6-pentafluorobenzamide)-β-d-gulopyranoside had Kd 700 µM for galectin-1, while not binding any other galectin. Full article
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Open AccessArticle
NMR Fragment-Based Screening against Tandem RNA Recognition Motifs of TDP-43
Int. J. Mol. Sci. 2019, 20(13), 3230; https://doi.org/10.3390/ijms20133230 - 30 Jun 2019
Abstract
The TDP-43 is originally a nuclear protein but translocates to the cytoplasm in the pathological condition. TDP-43, as an RNA-binding protein, consists of two RNA Recognition Motifs (RRM1 and RRM2). RRMs are known to involve both protein-nucleotide and protein-protein interactions and mediate the [...] Read more.
The TDP-43 is originally a nuclear protein but translocates to the cytoplasm in the pathological condition. TDP-43, as an RNA-binding protein, consists of two RNA Recognition Motifs (RRM1 and RRM2). RRMs are known to involve both protein-nucleotide and protein-protein interactions and mediate the formation of stress granules. Thus, they assist the entire TDP-43 protein with participating in neurodegenerative and cancer diseases. Consequently, they are potential therapeutic targets. Protein-observed and ligand-observed nuclear magnetic resonance (NMR) spectroscopy were used to uncover the small molecule inhibitors against the tandem RRM of TDP-43. We identified three hits weakly binding the tandem RRMs using the ligand-observed NMR fragment-based screening. The binding topology of these hits is then depicted by chemical shift perturbations (CSP) of the 15N-labeled tandem RRM and RRM2, respectively, and modeled by the CSP-guided High Ambiguity Driven biomolecular DOCKing (HADDOCK). These hits mainly bind to the RRM2 domain, which suggests the druggability of the RRM2 domain of TDP-43. These hits also facilitate further studies regarding the hit-to-lead evolution against the TDP-43 RRM domain. Full article
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Open AccessArticle
3D-PP: A Tool for Discovering Conserved Three-Dimensional Protein Patterns
Int. J. Mol. Sci. 2019, 20(13), 3174; https://doi.org/10.3390/ijms20133174 - 28 Jun 2019
Abstract
Discovering conserved three-dimensional (3D) patterns among protein structures may provide valuable insights into protein classification, functional annotations or the rational design of multi-target drugs. Thus, several computational tools have been developed to discover and compare protein 3D-patterns. However, most of them only consider [...] Read more.
Discovering conserved three-dimensional (3D) patterns among protein structures may provide valuable insights into protein classification, functional annotations or the rational design of multi-target drugs. Thus, several computational tools have been developed to discover and compare protein 3D-patterns. However, most of them only consider previously known 3D-patterns such as orthosteric binding sites or structural motifs. This fact makes necessary the development of new methods for the identification of all possible 3D-patterns that exist in protein structures (allosteric sites, enzyme-cofactor interaction motifs, among others). In this work, we present 3D-PP, a new free access web server for the discovery and recognition all similar 3D amino acid patterns among a set of proteins structures (independent of their sequence similarity). This new tool does not require any previous structural knowledge about ligands, and all data are organized in a high-performance graph database. The input can be a text file with the PDB access codes or a zip file of PDB coordinates regardless of the origin of the structural data: X-ray crystallographic experiments or in silico homology modeling. The results are presented as lists of sequence patterns that can be further analyzed within the web page. We tested the accuracy and suitability of 3D-PP using two sets of proteins coming from the Protein Data Bank: (a) Zinc finger containing and (b) Serotonin target proteins. We also evaluated its usefulness for the discovering of new 3D-patterns, using a set of protein structures coming from in silico homology modeling methodologies, all of which are overexpressed in different types of cancer. Results indicate that 3D-PP is a reliable, flexible and friendly-user tool to identify conserved structural motifs, which could be relevant to improve the knowledge about protein function or classification. The web server can be freely utilized at https://appsbio.utalca.cl/3d-pp/. Full article
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Open AccessArticle
In Silico Study of the Resistance to Organophosphorus Pesticides Associated with Point Mutations in Acetylcholinesterase of Lepidoptera: B. mandarina, B. mori, C. auricilius, C. suppressalis, C. pomonella, H. armígera, P. xylostella, S. frugiperda, and S. litura
Int. J. Mol. Sci. 2019, 20(10), 2404; https://doi.org/10.3390/ijms20102404 - 15 May 2019
Abstract
An in silico analysis of the interaction between the complex-ligands of nine acetylcholinesterase (AChE) structures of Lepidopteran organisms and 43 organophosphorus (OPs) pesticides with previous resistance reports was carried out. To predict the potential resistance by structural modifications in Lepidoptera insects, due to [...] Read more.
An in silico analysis of the interaction between the complex-ligands of nine acetylcholinesterase (AChE) structures of Lepidopteran organisms and 43 organophosphorus (OPs) pesticides with previous resistance reports was carried out. To predict the potential resistance by structural modifications in Lepidoptera insects, due to proposed point mutations in AChE, a broad analysis was performed using computational tools, such as homology modeling and molecular docking. Two relevant findings were revealed: (1) Docking results give a configuration of the most probable spatial orientation of two interacting molecules (AChE enzyme and OP pesticide) and (2) a predicted ΔGb. The mutations evaluated in the form 1 acetylcholinesterase (AChE-1) and form 2 acetylcholinesterase (AChE-2) structures of enzymes do not affect in any way (there is no regularity of change or significant deviations) the values of the binding energy (ΔGb) recorded in the AChE–OPs complexes. However, the mutations analyzed in AChE are associated with a structural modification that causes an inadequate interaction to complete the phosphorylation of the enzyme. Full article
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Open AccessArticle
Enhancement of Binding Affinity of Folate to Its Receptor by Peptide Conjugation
Int. J. Mol. Sci. 2019, 20(9), 2152; https://doi.org/10.3390/ijms20092152 - 30 Apr 2019
Abstract
(1) Background: The folate receptor (FR) is a target for cancer treatment and detection. Expression of the FR is restricted in normal cells but overexpressed in many types of tumors. Folate was conjugated with peptides for enhancing binding affinity to the FR. (2) [...] Read more.
(1) Background: The folate receptor (FR) is a target for cancer treatment and detection. Expression of the FR is restricted in normal cells but overexpressed in many types of tumors. Folate was conjugated with peptides for enhancing binding affinity to the FR. (2) Materials and Methods: For conjugation, folate was coupled with propargyl or dibenzocyclooctyne, and 4-azidophenylalanine was introduced in peptides for “click” reactions. We measured binding kinetics including the rate constants of association (ka) and dissociation (kd) of folate-peptide conjugates with purified FR by biolayer interferometry. After optimization of the conditions for the click reaction, we successfully conjugated folate with designed peptides. (3) Results: The binding affinity, indicated by the equilibrium dissociation constant (KD), of folate toward the FR was enhanced by peptide conjugation. The enhanced FR binding affinity by peptide conjugation is a result of an increase in the number of interaction sites. (4) Conclusion: Such peptide-ligand conjugates will be important in the design of ligands with higher affinity. These high affinity ligands can be useful for targeted drug delivery system. Full article
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Open AccessArticle
Insight into Structural Characteristics of Protein-Substrate Interaction in Pimaricin Thioesterase
Int. J. Mol. Sci. 2019, 20(4), 877; https://doi.org/10.3390/ijms20040877 - 18 Feb 2019
Abstract
As a polyene antibiotic of great pharmaceutical significance, pimaricin has been extensively studied to enhance its productivity and effectiveness. In our previous studies, pre-reaction state (PRS) has been validated as one of the significant conformational categories before macrocyclization, and is critical to mutual [...] Read more.
As a polyene antibiotic of great pharmaceutical significance, pimaricin has been extensively studied to enhance its productivity and effectiveness. In our previous studies, pre-reaction state (PRS) has been validated as one of the significant conformational categories before macrocyclization, and is critical to mutual recognition and catalytic preparation in thioesterase (TE)-catalyzed systems. In our study, molecular dynamics (MD) simulations were conducted on pimaricin TE-polyketide complex and PRS, as well as pre-organization state (POS), a molecular conformation possessing a pivotal intra-molecular hydrogen bond, were detected. Conformational transition between POS and PRS was observed in one of the simulations, and POS was calculated to be energetically more stable than PRS by 4.58 kcal/mol. The structural characteristics of PRS and POS-based hydrogen-bonding, and hydrophobic interactions were uncovered, and additional simulations were carried out to rationalize the functions of several key residues (Q29, M210, and R186). Binding energies, obtained from MM/PBSA calculations, were further decomposed to residues, in order to reveal their roles in product release. Our study advanced a comprehensive understanding of pimaricin TE-catalyzed macrocyclization from the perspectives of conformational change, protein-polyketide recognition, and product release, and provided potential residues for rational modification of pimaricin TE. Full article
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