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Special Issue "Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules"

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

Deadline for manuscript submissions: 29 March 2019

Special Issue Editors

Guest Editor
Research Associate Professor Tatyana Karabencheva-Christova

Department of Chemistry, Michigan Technological University, Houghton, MI 49931, USA
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
Guest Editor
Associate Professor Christo Z. Christov

Department of Chemistry, Michigan Technological University, Houghton, MI 49931, USA
Website | E-Mail
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

Special Issue Information

Dear Colleagues,

Computational Chemistry Methods are nowadays widely applied for studying biomolecular structure, mechanisms, dynamics, and function. Molecular Dynamic (MD) simulations methods, Quantum Mechanic (QM) methods, Combined Quantum Mechanics/Molecular Mechanics (QM/MM), Molecular Docking and other computational techniques have proven to be very useful for fundamental understanding of structure–function relationships in biomolecules, but also very useful for application in drug design, chemical biology and biotechnology. Importantly, the increased computational power and the development of high-performance computing made further possible the growth in synergistic computational–experimental studies in the most actual areas of biomolecular sciences in timeliness manner.  

The current Special Issue aims to attract high quality contributions of modeling biomolecular structure, dynamics, function and interactions with potential of interpretation of experimental data and application in drug design and protein design.

Topics of interest:

  • Development and validation of new Computational Modeling Methods
  • Computational Studies of proteins structure-function relationships
  • Computational investigations of nucleic acids structure–function relationships
  • Modelling of protein and nucleic acids dynamics
  • Protein Docking
  • Protein-ligand interactions
  • Nucleic acid ligand interactions
  • Protein design
  • Computational enzymology–enzymatic reaction mechanisms
  • Proteins homology modeling

Research Associate Professor Tatyana Karabencheva-Christova
Associate Professor Christo Z. Christov
Guest Editors

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Published Papers (14 papers)

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Research

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Open AccessArticle Atomistic Analysis of ToxN and ToxI Complex Unbinding Mechanism
Int. J. Mol. Sci. 2018, 19(11), 3524; https://doi.org/10.3390/ijms19113524
Received: 17 September 2018 / Revised: 14 October 2018 / Accepted: 2 November 2018 / Published: 9 November 2018
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Abstract
ToxIN is a triangular structure formed by three protein toxins (ToxNs) and three specific noncoding RNA antitoxins (ToxIs). To respond to stimuli, ToxI is preferentially degraded, releasing the ToxN. Thus, the dynamic character is essential in the normal function interactions between ToxN and [...] Read more.
ToxIN is a triangular structure formed by three protein toxins (ToxNs) and three specific noncoding RNA antitoxins (ToxIs). To respond to stimuli, ToxI is preferentially degraded, releasing the ToxN. Thus, the dynamic character is essential in the normal function interactions between ToxN and ToxI. Here, equilibrated molecular dynamics (MD) simulations were performed to study the stability of ToxN and ToxI. The results indicate that ToxI adjusts the conformation of 3′ and 5′ termini to bind to ToxN. Steered molecular dynamics (SMD) simulations combined with the recently developed thermodynamic integration in 3nD (TI3nD) method were carried out to investigate ToxN unbinding from the ToxIN complex. The potentials of mean force (PMFs) and atomistic pictures suggest the unbinding mechanism as follows: (1) dissociation of the 5′ terminus from ToxN, (2) missing the interactions involved in the 3′ terminus of ToxI without three nucleotides (G31, A32, and A33), (3) starting to unfold for ToxI, (4) leaving the binding package of ToxN for three nucleotides of ToxI, (5) unfolding of ToxI. This work provides information on the structure-function relationship at the atomistic level, which is helpful for designing new potent antibacterial drugs in the future. Full article
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Open AccessArticle Prediction of Novel Anoctamin1 (ANO1) Inhibitors Using 3D-QSAR Pharmacophore Modeling and Molecular Docking
Int. J. Mol. Sci. 2018, 19(10), 3204; https://doi.org/10.3390/ijms19103204
Received: 19 September 2018 / Revised: 10 October 2018 / Accepted: 15 October 2018 / Published: 17 October 2018
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Abstract
Recently, anoctamin1 (ANO1), a calcium-activated chloride channel, has been considered an important drug target, due to its involvement in various physiological functions, as well as its possibility for treatment of cancer, pain, diarrhea, hypertension, and asthma. Although several ANO1 inhibitors have been discovered [...] Read more.
Recently, anoctamin1 (ANO1), a calcium-activated chloride channel, has been considered an important drug target, due to its involvement in various physiological functions, as well as its possibility for treatment of cancer, pain, diarrhea, hypertension, and asthma. Although several ANO1 inhibitors have been discovered by high-throughput screening, a discovery of new ANO1 inhibitors is still in the early phase, in terms of their potency and specificity. Moreover, there is no computational model to be able to identify a novel lead candidate of ANO1 inhibitor. Therefore, three-dimensional quantitative structure-activity relationship (3D-QSAR) pharmacophore modeling approach was employed for identifying the essential chemical features to be required in the inhibition of ANO1. The pharmacophore hypothesis 2 (Hypo2) was selected as the best model based on the highest correlation coefficient of prediction on the test set (0.909). Hypo2 comprised a hydrogen bond acceptor, a hydrogen bond donor, a hydrophobic, and a ring aromatic feature with good statistics of the total cost (73.604), the correlation coefficient of the training set (0.969), and the root-mean-square deviation (RMSD) value (0.946). Hypo2 was well assessed by the test set, Fischer randomization, and leave-one-out methods. Virtual screening of the ZINC database with Hypo2 retrieved the 580 drug-like candidates with good potency and ADMET properties. Finally, two compounds were selected as novel lead candidates of ANO1 inhibitor, based on the molecular docking score and the interaction analysis. In this study, the best pharmacophore model, Hypo2, with notable predictive ability was successfully generated, and two potential leads of ANO1 inhibitors were identified. We believe that these compounds and the 3D-QSAR pharmacophore model could contribute to discovering novel and potent ANO1 inhibitors in the future. Full article
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Open AccessArticle A Hybrid Cuckoo Search and Differential Evolution Approach to Protein–Ligand Docking
Int. J. Mol. Sci. 2018, 19(10), 3181; https://doi.org/10.3390/ijms19103181
Received: 12 September 2018 / Revised: 11 October 2018 / Accepted: 12 October 2018 / Published: 15 October 2018
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Abstract
Protein–ligand docking is a molecular modeling technique that is used to predict the conformation of a small molecular ligand at the binding pocket of a protein receptor. There are many protein–ligand docking tools, among which AutoDock Vina is the most popular open-source docking [...] Read more.
Protein–ligand docking is a molecular modeling technique that is used to predict the conformation of a small molecular ligand at the binding pocket of a protein receptor. There are many protein–ligand docking tools, among which AutoDock Vina is the most popular open-source docking software. In recent years, there have been numerous attempts to optimize the search process in AutoDock Vina by means of heuristic optimization methods, such as genetic and particle swarm optimization algorithms. This study, for the first time, explores the use of cuckoo search (CS) to solve the protein–ligand docking problem. The result of this study is CuckooVina, an enhanced conformational search algorithm that hybridizes cuckoo search with differential evolution (DE). Extensive tests using two benchmark datasets, PDBbind 2012 and Astex Diverse set, show that CuckooVina improves the docking performances in terms of RMSD, binding affinity, and success rate compared to Vina though it requires about 9–15% more time to complete a run than Vina. CuckooVina predicts more accurate docking poses with higher binding affinities than PSOVina with similar success rates. CuckooVina’s slower convergence but higher accuracy suggest that it is better able to escape from local energy minima and improves the problem of premature convergence. As a summary, our results assure that the hybrid CS–DE process to continuously generate diverse solutions is a good strategy to maintain the proper balance between global and local exploitation required for the ligand conformational search. Full article
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Open AccessArticle Insights into the Structural Requirements of 2(S)-Amino-6-Boronohexanoic Acid Derivatives as Arginase I Inhibitors: 3D-QSAR, Docking, and Interaction Fingerprint Studies
Int. J. Mol. Sci. 2018, 19(10), 2956; https://doi.org/10.3390/ijms19102956
Received: 24 August 2018 / Revised: 20 September 2018 / Accepted: 20 September 2018 / Published: 28 September 2018
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Abstract
Human arginase I (hARGI) is an important enzyme involved in the urea cycle; its overexpression has been associated to cardiovascular and cerebrovascular diseases. In the last years, several congeneric sets of hARGI inhibitors have been reported with possible beneficial roles for the cardiovascular [...] Read more.
Human arginase I (hARGI) is an important enzyme involved in the urea cycle; its overexpression has been associated to cardiovascular and cerebrovascular diseases. In the last years, several congeneric sets of hARGI inhibitors have been reported with possible beneficial roles for the cardiovascular system. At the same time, crystallographic data have been reported including hARGI–inhibitor complexes, which can be considered for the design of novel inhibitors. In this work, the structure–activity relationship (SAR) of Cα substituted 2(S)-amino-6-boronohexanoic acid (ABH) derivatives as hARGI inhibitors was studied by using a three-dimensional quantitative structure–activity relationships (3D-QSAR) method. The predictivity of the obtained 3D-QSAR model was demonstrated by using internal and external validation experiments. The best model revealed that the differential hARGI inhibitory activities of the ABH derivatives can be described by using steric and electrostatic fields; the local effects of these fields in the activity are presented. In addition, binding modes of the above-mentioned compounds inside the hARGI binding site were obtained by using molecular docking. It was found that ABH derivatives adopted the same orientation reported for ABH within the hARGI active site, with the substituents at Cα exposed to the solvent with interactions with residues at the entrance of the binding site. The hARGI residues involved in chemical interactions with inhibitors were identified by using an interaction fingerprints (IFPs) analysis. Full article
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Open AccessArticle Oxidative Alteration of Trp-214 and Lys-199 in Human Serum Albumin Increases Binding Affinity with Phenylbutazone: A Combined Experimental and Computational Investigation
Int. J. Mol. Sci. 2018, 19(10), 2868; https://doi.org/10.3390/ijms19102868
Received: 8 September 2018 / Revised: 17 September 2018 / Accepted: 19 September 2018 / Published: 21 September 2018
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Abstract
Human serum albumin (HSA) is a target for reactive oxygen species (ROS), and alterations of its physiological functions caused by oxidation is a current issue. In this work, the amino-acid residues Trp-214 and Lys-199, which are located at site I of HSA, were [...] Read more.
Human serum albumin (HSA) is a target for reactive oxygen species (ROS), and alterations of its physiological functions caused by oxidation is a current issue. In this work, the amino-acid residues Trp-214 and Lys-199, which are located at site I of HSA, were experimentally and computationally oxidized, and the effect on the binding constant with phenylbutazone was measured. HSA was submitted to two mild oxidizing reagents, taurine monochloramine (Tau-NHCl) and taurine dibromamine (Tau-NBr2). The oxidation of Trp-214 provoked spectroscopic alterations in the protein which were consistent with the formation of N′-formylkynurenine. It was found that the oxidation of HSA by Tau-NBr2, but not by Tau-NHCl, provoked a significant increase in the association constant with phenylbutazone. The alterations of Trp-214 and Lys-199 were modeled and simulated by changing these residues using the putative oxidation products. Based on the Amber score function, the interaction energy was measured, and it showed that, while native HSA presented an interaction energy of −21.3 kJ/mol, HSA with Trp-214 altered to N′-formylkynurenine resulted in an energy of −28.4 kJ/mol, and HSA with Lys-199 altered to its carbonylated form resulted in an energy of −33.9 kJ/mol. In summary, these experimental and theoretical findings show that oxidative alterations of amino-acid residues at site I of HSA affect its binding efficacy. Full article
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Open AccessArticle Biochemical Characterization and Structural Modeling of Fused Glucose-6-Phosphate Dehydrogenase-Phosphogluconolactonase from Giardia lamblia
Int. J. Mol. Sci. 2018, 19(9), 2518; https://doi.org/10.3390/ijms19092518
Received: 13 July 2018 / Revised: 18 August 2018 / Accepted: 22 August 2018 / Published: 25 August 2018
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Abstract
Glucose-6-phosphate dehydrogenase (G6PD) is the first enzyme in the pentose phosphate pathway and is highly relevant in the metabolism of Giardia lamblia. Previous reports suggested that the G6PD gene is fused with the 6-phosphogluconolactonase (6PGL) gene (6pgl). Therefore, in this work, [...] Read more.
Glucose-6-phosphate dehydrogenase (G6PD) is the first enzyme in the pentose phosphate pathway and is highly relevant in the metabolism of Giardia lamblia. Previous reports suggested that the G6PD gene is fused with the 6-phosphogluconolactonase (6PGL) gene (6pgl). Therefore, in this work, we decided to characterize the fused G6PD-6PGL protein in Giardia lamblia. First, the gene of g6pd fused with the 6pgl gene (6gpd::6pgl) was isolated from trophozoites of Giardia lamblia and the corresponding G6PD::6PGL protein was overexpressed and purified in Escherichia coli. Then, we characterized the native oligomeric state of the G6PD::6PGL protein in solution and we found a catalytic dimer with an optimum pH of 8.75. Furthermore, we determined the steady-state kinetic parameters for the G6PD domain and measured the thermal stability of the protein in both the presence and absence of guanidine hydrochloride (Gdn-HCl) and observed that the G6PD::6PGL protein showed alterations in the stability, secondary structure, and tertiary structure in the presence of Gdn-HCl. Finally, computer modeling studies revealed unique structural and functional features, which clearly established the differences between G6PD::6PGL protein from G. lamblia and the human G6PD enzyme, proving that the model can be used for the design of new drugs with antigiardiasic activity. These results broaden the perspective for future studies of the function of the protein and its effect on the metabolism of this parasite as a potential pharmacological target. Full article
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Open AccessArticle Amino-Acid Network Clique Analysis of Protein Mutation Non-Additive Effects: A Case Study of Lysozyme
Int. J. Mol. Sci. 2018, 19(5), 1427; https://doi.org/10.3390/ijms19051427
Received: 14 February 2018 / Revised: 28 April 2018 / Accepted: 7 May 2018 / Published: 10 May 2018
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Abstract
Optimizing amino-acid mutations in enzyme design has been a very challenging task in modern bio-industrial applications. It is well known that many successful designs often hinge on extensive correlations among mutations at different sites within the enzyme, however, the underpinning mechanism for these [...] Read more.
Optimizing amino-acid mutations in enzyme design has been a very challenging task in modern bio-industrial applications. It is well known that many successful designs often hinge on extensive correlations among mutations at different sites within the enzyme, however, the underpinning mechanism for these correlations is far from clear. Here, we present a topology-based model to quantitively characterize non-additive effects between mutations. The method is based on the molecular dynamic simulations and the amino-acid network clique analysis. It examines if the two mutation sites of a double-site mutation fall into to a 3-clique structure, and associates such topological property of mutational site spatial distribution with mutation additivity features. We analyzed 13 dual mutations of T4 phage lysozyme and found that the clique-based model successfully distinguishes highly correlated or non-additive double-site mutations from those additive ones whose component mutations have less correlation. We also applied the model to protein Eglin c whose structural topology is significantly different from that of T4 phage lysozyme, and found that the model can, to some extension, still identify non-additive mutations from additive ones. Our calculations showed that mutation non-additive effects may heavily depend on a structural topology relationship between mutation sites, which can be quantitatively determined using amino-acid network k-cliques. We also showed that double-site mutation correlations can be significantly altered by exerting a third mutation, indicating that more detailed physicochemical interactions should be considered along with the network clique-based model for better understanding of this elusive mutation-correlation principle. Full article
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Open AccessArticle Theoretical Studies Applied to the Evaluation of the DFPase Bioremediation Potential against Chemical Warfare Agents Intoxication
Int. J. Mol. Sci. 2018, 19(4), 1257; https://doi.org/10.3390/ijms19041257
Received: 24 March 2018 / Revised: 16 April 2018 / Accepted: 19 April 2018 / Published: 23 April 2018
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Abstract
Organophosphorus compounds (OP) are part of a group of compounds that may be hazardous to health. They are called neurotoxic agents because of their action on the nervous system, inhibiting the acetylcholinesterase (AChE) enzyme and resulting in a cholinergic crisis. Their high toxicity [...] Read more.
Organophosphorus compounds (OP) are part of a group of compounds that may be hazardous to health. They are called neurotoxic agents because of their action on the nervous system, inhibiting the acetylcholinesterase (AChE) enzyme and resulting in a cholinergic crisis. Their high toxicity and rapid action lead to irreversible damage to the nervous system, drawing attention to developing new treatment methods. The diisopropyl fluorophosphatase (DFPase) enzyme has been considered as a potent biocatalyst for the hydrolysis of toxic OP and has potential for bioremediation of this kind of intoxication. In order to investigate the degradation process of the nerve agents Tabun, Cyclosarin and Soman through the wild-type DFPase, and taking into account their stereochemistry, theoretical studies were carried out. The intermolecular interaction energy and other parameters obtained from the molecular docking calculations were used to construct a data matrix, which were posteriorly treated by statistical analyzes of chemometrics, using the PCA (Principal Components Analysis) multivariate analysis. The analyzed parameters seem to be quite important for the reaction mechanisms simulation (QM/MM). Our findings showed that the wild-type DFPase enzyme is stereoselective in hydrolysis, showing promising results for the catalytic degradation of the neurotoxic agents under study, with the degradation mechanism performed through two proposed pathways. Full article
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Open AccessArticle Molecular Modeling Studies on Carbazole Carboxamide Based BTK Inhibitors Using Docking and Structure-Based 3D-QSAR
Int. J. Mol. Sci. 2018, 19(4), 1244; https://doi.org/10.3390/ijms19041244
Received: 19 March 2018 / Revised: 7 April 2018 / Accepted: 9 April 2018 / Published: 19 April 2018
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Abstract
Rheumatoid arthritis (RA) is the second common rheumatic immune disease with chronic, invasive inflammatory characteristics. Non-steroidal anti-inflammatory drugs (NSAIDs), slow-acting anti-rheumatic drugs (SAARDs), or glucocorticoid drugs can improve RA patients’ symptoms, but fail to cure. Broton’s tyrosine kinase (BTK) inhibitors have been proven [...] Read more.
Rheumatoid arthritis (RA) is the second common rheumatic immune disease with chronic, invasive inflammatory characteristics. Non-steroidal anti-inflammatory drugs (NSAIDs), slow-acting anti-rheumatic drugs (SAARDs), or glucocorticoid drugs can improve RA patients’ symptoms, but fail to cure. Broton’s tyrosine kinase (BTK) inhibitors have been proven to be an efficacious target against autoimmune indications and B-cell malignancies. Among the current 11 clinical drugs, only BMS-986142, classified as a carbazole derivative, is used for treating RA. To design novel and highly potent carbazole inhibitors, molecular docking and three dimensional quantitative structure–activity relationship (3D-QSAR) were applied to explore a dataset of 132 new carbazole carboxamide derivatives. The established comparative molecular field analysis (CoMFA) (q2 = 0.761, r2 = 0.933) and comparative molecular similarity indices analysis (CoMSIA) (q2 = 0.891, r2 = 0.988) models obtained high predictive and satisfactory values. CoMFA/CoMSIA contour maps demonstrated that bulky substitutions and hydrogen-bond donors were preferred at R1 and 1-position, respectively, and introducing hydrophilic substitutions at R1 and R4 was important for improving BTK inhibitory activities. These results will contribute to the design of novel and highly potent BTK inhibitors. Full article
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Open AccessArticle Molecular Dynamics Simulations of Human Antimicrobial Peptide LL-37 in Model POPC and POPG Lipid Bilayers
Int. J. Mol. Sci. 2018, 19(4), 1186; https://doi.org/10.3390/ijms19041186
Received: 21 March 2018 / Revised: 10 April 2018 / Accepted: 11 April 2018 / Published: 13 April 2018
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Abstract
Cathelicidins are a large family of cationic antimicrobial peptides (AMPs) found in mammals with broad spectrum antimicrobial activity. LL-37 is the sole amphipathic α-helical AMP from human Cathelicidins family. In addition to its bactericidal capability, LL-37 has antiviral, anti-tumor, and immunoregulatory activity. Despite [...] Read more.
Cathelicidins are a large family of cationic antimicrobial peptides (AMPs) found in mammals with broad spectrum antimicrobial activity. LL-37 is the sole amphipathic α-helical AMP from human Cathelicidins family. In addition to its bactericidal capability, LL-37 has antiviral, anti-tumor, and immunoregulatory activity. Despite many experimental studies, its molecular mechanism of action is not yet fully understood. Here, we performed three independent molecular dynamics simulations (600 ns or more) of a LL-37 peptide in the presence of 256 lipid bilayers with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG) mimicking bacterial and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) mimicking mammalian membranes. We found that LL-37 can be quickly absorbed onto the POPG bilayer without loss of its helical conformation in the core region and with the helix lying in parallel to the bilayer. The POPG bilayer was deformed. In contrast, LL-37 is slower in reaching the POPC surface and loss much of its helical conformation during the interaction with the bilayer. LL-37 only partially entered the POPC bilayer without significant deformation of the membrane. The observed difference for different bilayers is largely due to the fact that LL-37 is positively charged, POPG is negatively charged, and POPC is neutral. Our simulation results demonstrated the initial stage of disruption of the bacterial membrane by LL-37 in atomic details. Comparison to experimental results on LL-37 and simulation studies in other systems was made. Full article
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Open AccessArticle Automated Exploration of Free Energy Landscapes Based on Umbrella Integration
Int. J. Mol. Sci. 2018, 19(4), 937; https://doi.org/10.3390/ijms19040937
Received: 28 February 2018 / Revised: 19 March 2018 / Accepted: 21 March 2018 / Published: 21 March 2018
Cited by 2 | PDF Full-text (6765 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
We present a new approach for automated exploration of free energy landscapes on the basis of the umbrella integration (UI) method. The method to search points in the landscape relies on the normal distributions and gradients of the potential of mean force (PMF) [...] Read more.
We present a new approach for automated exploration of free energy landscapes on the basis of the umbrella integration (UI) method. The method to search points in the landscape relies on the normal distributions and gradients of the potential of mean force (PMF) obtained from UI calculations. We applied this approach to the alanine dipeptide in solution and demonstrated that the equilibrium and the transition states were efficiently found in the ascending order of the PMF values. Full article
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Open AccessArticle Bias-Exchange Metadynamics Simulation of Membrane Permeation of 20 Amino Acids
Int. J. Mol. Sci. 2018, 19(3), 885; https://doi.org/10.3390/ijms19030885
Received: 13 February 2018 / Revised: 11 March 2018 / Accepted: 12 March 2018 / Published: 16 March 2018
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Abstract
Thermodynamics of the permeation of amino acids from water to lipid bilayers is an important first step for understanding the mechanism of cell-permeating peptides and the thermodynamics of membrane protein structure and stability. In this work, we employed bias-exchange metadynamics simulations to simulate [...] Read more.
Thermodynamics of the permeation of amino acids from water to lipid bilayers is an important first step for understanding the mechanism of cell-permeating peptides and the thermodynamics of membrane protein structure and stability. In this work, we employed bias-exchange metadynamics simulations to simulate the membrane permeation of all 20 amino acids from water to the center of a dipalmitoylphosphatidylcholine (DPPC) membrane (consists of 256 lipids) by using both directional and torsion angles for conformational sampling. The overall accuracy for the free energy profiles obtained is supported by significant correlation coefficients (correlation coefficient at 0.5–0.6) between our results and previous experimental or computational studies. The free energy profiles indicated that (1) polar amino acids have larger free energy barriers than nonpolar amino acids; (2) negatively charged amino acids are the most difficult to enter into the membrane; and (3) conformational transitions for many amino acids during membrane crossing is the key for reduced free energy barriers. These results represent the first set of simulated free energy profiles of membrane crossing for all 20 amino acids. Full article
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Review

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Open AccessReview Designed Elastic Networks: Models of Complex Protein Machinery
Int. J. Mol. Sci. 2018, 19(10), 3152; https://doi.org/10.3390/ijms19103152
Received: 20 July 2018 / Revised: 4 October 2018 / Accepted: 11 October 2018 / Published: 13 October 2018
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Abstract
Recently, the design of mechanical networks with protein-inspired responses has become increasingly popular. Here, we review contributions which were motivated by studies of protein dynamics employing coarse-grained elastic network models. First, the concept of evolutionary optimization that we developed to design network structures [...] Read more.
Recently, the design of mechanical networks with protein-inspired responses has become increasingly popular. Here, we review contributions which were motivated by studies of protein dynamics employing coarse-grained elastic network models. First, the concept of evolutionary optimization that we developed to design network structures which execute prescribed tasks is explained. We then review what presumably marks the origin of the idea to design complex functional networks which encode protein-inspired behavior, namely the design of an elastic network structure which emulates the cycles of ATP-powered conformational motion in protein machines. Two recent applications are reviewed. First, the construction of a model molecular motor, whose operation incorporates both the tight coupling power stroke as well as the loose coupling Brownian ratchet mechanism, is discussed. Second, the evolutionary design of network structures which encode optimal long-range communication between remote sites and represent mechanical models of allosteric proteins is presented. We discuss the prospects of designed protein-mimicking elastic networks as model systems to elucidate the design principles and functional signatures underlying the operation of complex protein machinery. Full article
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Open AccessReview Recent Trends and Applications of Molecular Modeling in GPCR–Ligand Recognition and Structure-Based Drug Design
Int. J. Mol. Sci. 2018, 19(7), 2105; https://doi.org/10.3390/ijms19072105
Received: 29 June 2018 / Revised: 12 July 2018 / Accepted: 12 July 2018 / Published: 20 July 2018
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Abstract
G protein-coupled receptors represent the largest family of human membrane proteins and are modulated by a variety of drugs and endogenous ligands. Molecular modeling techniques, especially enhanced sampling methods, have provided significant insight into the mechanism of GPCR–ligand recognition. Notably, the crucial role [...] Read more.
G protein-coupled receptors represent the largest family of human membrane proteins and are modulated by a variety of drugs and endogenous ligands. Molecular modeling techniques, especially enhanced sampling methods, have provided significant insight into the mechanism of GPCR–ligand recognition. Notably, the crucial role of the membrane in the ligand-receptor association process has earned much attention. Additionally, docking, together with more accurate free energy calculation methods, is playing an important role in the design of novel compounds targeting GPCRs. Here, we summarize the recent progress in the computational studies focusing on the above issues. In the future, with continuous improvement in both computational hardware and algorithms, molecular modeling would serve as an indispensable tool in a wider scope of the research concerning GPCR–ligand recognition as well as drug design targeting GPCRs. Full article
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