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21 pages, 7378 KiB

Open AccessArticle

Towards A Molecular Understanding of The Cannabinoid Related Orphan Receptor GPR18: A Focus on Its Constitutive Activity

by Noori Sotudeh, Paula Morales, Dow P. Hurst, Diane L. Lynch and Patricia H. Reggio

Int. J. Mol. Sci. 2019, 20(9), 2300; https://doi.org/10.3390/ijms20092300 - 9 May 2019

Cited by 10 | Viewed by 4292

Abstract

The orphan G-protein coupled receptor (GPCR), GPR18, has been recently proposed as a potential member of the cannabinoid family as it recognizes several endogenous, phytogenic, and synthetic cannabinoids. Potential therapeutic applications for GPR18 include intraocular pressure, metabolic disorders, and cancer. GPR18 has been [...] Read more.

The orphan G-protein coupled receptor (GPCR), GPR18, has been recently proposed as a potential member of the cannabinoid family as it recognizes several endogenous, phytogenic, and synthetic cannabinoids. Potential therapeutic applications for GPR18 include intraocular pressure, metabolic disorders, and cancer. GPR18 has been reported to have high constitutive activity, i.e., activation/signaling occurs in the absence of an agonist. This activity can be reduced significantly by the A3.39N mutation. At the intracellular (IC) ends of (transmembrane helices) TMH3 and TMH6 in GPCRs, typically, a pair of oppositely charged amino acids form a salt bridge called the “ionic lock”. Breaking of this salt bridge creates an IC opening for coupling with G protein. The GPR18 “ionic lock” residues (R3.50/S6.33) can form only a hydrogen bond. In this paper, we test the hypothesis that the high constitutive activity of GPR18 is due to the weakness of its “ionic lock” and that the A3.39N mutation strengthens this lock. To this end, we report molecular dynamics simulations of wild-type (WT) GPR18 and the A3.39N mutant in fully hydrated (POPC) phophatidylcholine lipid bilayers. Results suggest that in the A3.39N mutant, TMH6 rotates and brings R3.50 and S6.33 closer together, thus strengthening the GPR18 “ionic lock”. Full article

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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14 pages, 5498 KiB

Open AccessArticle

Computational Study for the Unbinding Routes of β-N-Acetyl-d-Hexosaminidase Inhibitor: Insight from Steered Molecular Dynamics Simulations

by Song Hu, Xiao Zhao and Li Zhang

Int. J. Mol. Sci. 2019, 20(6), 1516; https://doi.org/10.3390/ijms20061516 - 26 Mar 2019

Cited by 5 | Viewed by 4451

Abstract

β-N-Acetyl-d-hexosaminidase from Ostrinia furnacalis (OfHex1) is a new target for the design of insecticides. Although some of its inhibitors have been found, there is still no commercial drug available at present. The residence time of the ligand [...] Read more.

β-N-Acetyl-d-hexosaminidase from Ostrinia furnacalis (OfHex1) is a new target for the design of insecticides. Although some of its inhibitors have been found, there is still no commercial drug available at present. The residence time of the ligand may be important for its pharmacodynamic effect. However, the unbinding routes of ligands from OfHex1 still remain largely unexplored. In the present study, we first simulated the six dissociation routes of N,N,N-trimethyl-d-glucosamine-chitotriomycin (TMG-chitotriomycin, a highly selective inhibitor of OfHex1) from the active pocket of OfHex1 by steered molecular dynamics simulations. By comparing the potential of mean forces (PMFs) of six routes, Route 1 was considered as the most possible route with the lowest energy barrier. Furthermore, the structures of six different states for Route 1 were snapshotted, and the key amino acid residues affecting the dissociated time were analyzed in the unbinding pathway. Moreover, we also analyzed the “open–close” mechanism of Glu368 and Trp448 and found that their conformational changes directly affected the dissociation of TMG-chitotriomycin. Our findings would be helpful to understanding and identifying novel inhibitors against OfHex1 from virtual screening or lead-optimization. Full article

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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24 pages, 5533 KiB

Open AccessArticle

Effects of Selective Substitution of Cysteine Residues on the Conformational Properties of Chlorotoxin Explored by Molecular Dynamics Simulations

by Andrew J. Gregory, Leah Voit-Ostricki, Sándor Lovas and Charles R. Watts

Int. J. Mol. Sci. 2019, 20(6), 1261; https://doi.org/10.3390/ijms20061261 - 13 Mar 2019

Cited by 5 | Viewed by 3412

Abstract

Chlorotoxin (CTX) is a 36–amino acid peptide with eight Cys residues that forms four disulfide bonds. It has high affinity for the glioma-specific chloride channel and matrix metalloprotease-2. Structural and binding properties of CTX analogs with various Cys residue substitutions with l-α-aminobutyric [...] Read more.

Chlorotoxin (CTX) is a 36–amino acid peptide with eight Cys residues that forms four disulfide bonds. It has high affinity for the glioma-specific chloride channel and matrix metalloprotease-2. Structural and binding properties of CTX analogs with various Cys residue substitutions with l-α-aminobutyric acid (Abu) have been previously reported. Using 4.2 µs molecular dynamics, we compared the conformational and essential space sampling of CTX and analogs with selective substitution of the Cys residues and associated disulfide bonds with either Abu or Ser. The native and substituted peptides maintained a high degree of α-helix propensity from residues 8 through 21, with the exception of substitution of the Cys⁵–Cys²⁸ residues with Ser and the Cys¹⁶–Cys³³ residues with Abu. In agreement with previous circular dichroism spectropolarimetry results, the C-terminal β-sheet content varied less from residues 25 through 29 and 32 through 36 and was well conserved in most analogs. The Cys¹⁶–Cys³³ and Cys²⁰–Cys³⁵ disulfide-bonded residues appear to be required to maintain the αβ motif of CTX. Selective substitution with the hydrophilic Ser, may mitigate the destabilizing effect of Cys¹⁶–Cys³³ substitution through the formation of an inter residue H-bond from Ser¹⁶:OγH to Ser³³:OγH bridged by a water molecule. All peptides shared considerable sampled conformational space, which explains the retained receptor binding of the non-native analogs. Full article

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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12 pages, 1735 KiB

Open AccessArticle

In Silico Molecular Docking and In Vivo Validation with Caenorhabditis elegans to Discover Molecular Initiating Events in Adverse Outcome Pathway Framework: Case Study on Endocrine-Disrupting Chemicals with Estrogen and Androgen Receptors

by Jaeseong Jeong, Hunbeen Kim and Jinhee Choi

Int. J. Mol. Sci. 2019, 20(5), 1209; https://doi.org/10.3390/ijms20051209 - 10 Mar 2019

Cited by 28 | Viewed by 6359

Abstract

Molecular docking is used to analyze structural complexes of a target with its ligand for understanding the chemical and structural basis of target specificity. This method has the potential to be applied for discovering molecular initiating events (MIEs) in the Adverse Outcome Pathway [...] Read more.

Molecular docking is used to analyze structural complexes of a target with its ligand for understanding the chemical and structural basis of target specificity. This method has the potential to be applied for discovering molecular initiating events (MIEs) in the Adverse Outcome Pathway framework. In this study, we aimed to develop in silico–in vivo combined approach as a tool for identifying potential MIEs. We used environmental chemicals from Tox21 database to identify potential endocrine-disrupting chemicals (EDCs) through molecular docking simulation, using estrogen receptor (ER), androgen receptor (AR) and their homology models in the nematode Caenorhabditis elegans (NHR-14 and NHR-69, respectively). In vivo validation was conducted on the selected EDCs with C. elegans reproductive toxicity assay using wildtype N2, nhr-14, and nhr-69 loss-of-function mutant strains. The chemicals showed high binding affinity to tested receptors and showed the high in vivo reproductive toxicity, and this was further confirmed using the mutant strains. The present study demonstrates that the binding affinity from the molecular docking potentially correlates with in vivo toxicity. These results prove that our in silico–in vivo combined approach has the potential to be applied for identifying MIEs. This study also suggests the potential of C. elegans as useful in the in vivo model for validating the in silico approach. Full article

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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16 pages, 22734 KiB

Open AccessArticle

Atomistic Analysis of ToxN and ToxI Complex Unbinding Mechanism

by Guodong Hu, Xiu Yu, Yunqiang Bian, Zanxia Cao, Shicai Xu, Liling Zhao, Baohua Ji, Wei Wang and Jihua Wang

Int. J. Mol. Sci. 2018, 19(11), 3524; https://doi.org/10.3390/ijms19113524 - 9 Nov 2018

Cited by 10 | Viewed by 3934

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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18 pages, 9154 KiB

Open AccessArticle

Prediction of Novel Anoctamin1 (ANO1) Inhibitors Using 3D-QSAR Pharmacophore Modeling and Molecular Docking

by Yoon Hyeok Lee and Gwan-Su Yi

Int. J. Mol. Sci. 2018, 19(10), 3204; https://doi.org/10.3390/ijms19103204 - 17 Oct 2018

Cited by 15 | Viewed by 5947

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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13 pages, 1747 KiB

Open AccessArticle

A Hybrid Cuckoo Search and Differential Evolution Approach to Protein–Ligand Docking

by Hang Lin and Shirley W. I. Siu

Int. J. Mol. Sci. 2018, 19(10), 3181; https://doi.org/10.3390/ijms19103181 - 15 Oct 2018

Cited by 13 | Viewed by 3736

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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19 pages, 14151 KiB

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

by José Luis Velázquez-Libera, Carlos Navarro-Retamal and Julio Caballero

Int. J. Mol. Sci. 2018, 19(10), 2956; https://doi.org/10.3390/ijms19102956 - 28 Sep 2018

Cited by 6 | Viewed by 3900

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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17 pages, 3310 KiB

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

by Luiza De Carvalho Bertozo, Ernesto Tavares Neto, Leandro Cristante de Oliveira and Valdecir Farias Ximenes

Int. J. Mol. Sci. 2018, 19(10), 2868; https://doi.org/10.3390/ijms19102868 - 21 Sep 2018

Cited by 10 | Viewed by 4844

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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23 pages, 2900 KiB

Open AccessArticle

Biochemical Characterization and Structural Modeling of Fused Glucose-6-Phosphate Dehydrogenase-Phosphogluconolactonase from Giardia lamblia

by Laura Morales-Luna, Hugo Serrano-Posada, Abigail González-Valdez, Daniel Ortega-Cuellar, America Vanoye-Carlo, Beatriz Hernández-Ochoa, Edgar Sierra-Palacios, Yadira Rufino-González, Rosa Angélica Castillo-Rodríguez, Verónica Pérez de la Cruz, Liliana Moreno-Vargas, Diego Prada-Gracia, Jaime Marcial-Quino and Saúl Gómez-Manzo

Int. J. Mol. Sci. 2018, 19(9), 2518; https://doi.org/10.3390/ijms19092518 - 25 Aug 2018

Cited by 12 | Viewed by 5212

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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12 pages, 1331 KiB

Open AccessArticle

Amino-Acid Network Clique Analysis of Protein Mutation Non-Additive Effects: A Case Study of Lysozyme

by Dengming Ming, Rui Chen and He Huang

Int. J. Mol. Sci. 2018, 19(5), 1427; https://doi.org/10.3390/ijms19051427 - 10 May 2018

Cited by 11 | Viewed by 3819

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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18 pages, 4373 KiB

Open AccessArticle

Theoretical Studies Applied to the Evaluation of the DFPase Bioremediation Potential against Chemical Warfare Agents Intoxication

by Flávia V. Soares, Alexandre A. De Castro, Ander F. Pereira, Daniel H. S. Leal, Daiana T. Mancini, Ondrej Krejcar, Teodorico C. Ramalho, Elaine F. F. Da Cunha and Kamil Kuca

Int. J. Mol. Sci. 2018, 19(4), 1257; https://doi.org/10.3390/ijms19041257 - 23 Apr 2018

Cited by 21 | Viewed by 4854

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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24 pages, 41100 KiB

Open AccessArticle

Molecular Modeling Studies on Carbazole Carboxamide Based BTK Inhibitors Using Docking and Structure-Based 3D-QSAR

by Rui Li, Yongli Du, Zhipei Gao and Jingkang Shen

Int. J. Mol. Sci. 2018, 19(4), 1244; https://doi.org/10.3390/ijms19041244 - 19 Apr 2018

Cited by 8 | Viewed by 5160

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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13 pages, 8126 KiB

Open AccessArticle

Molecular Dynamics Simulations of Human Antimicrobial Peptide LL-37 in Model POPC and POPG Lipid Bilayers

by Liling Zhao, Zanxia Cao, Yunqiang Bian, Guodong Hu, Jihua Wang and Yaoqi Zhou

Int. J. Mol. Sci. 2018, 19(4), 1186; https://doi.org/10.3390/ijms19041186 - 13 Apr 2018

Cited by 52 | Viewed by 7800

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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15 pages, 6765 KiB

Open AccessArticle

Automated Exploration of Free Energy Landscapes Based on Umbrella Integration

by Yuki Mitsuta, Takashi Kawakami, Mitsutaka Okumura and Shusuke Yamanaka

Int. J. Mol. Sci. 2018, 19(4), 937; https://doi.org/10.3390/ijms19040937 - 21 Mar 2018

Cited by 10 | Viewed by 4037

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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15 pages, 12139 KiB

Open AccessArticle

Bias-Exchange Metadynamics Simulation of Membrane Permeation of 20 Amino Acids

by Zanxia Cao, Yunqiang Bian, Guodong Hu, Liling Zhao, Zhenzhen Kong, Yuedong Yang, Jihua Wang and Yaoqi Zhou

Int. J. Mol. Sci. 2018, 19(3), 885; https://doi.org/10.3390/ijms19030885 - 16 Mar 2018

Cited by 15 | Viewed by 4889

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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21 pages, 1303 KiB

Open AccessReview

A Comprehensive Review on Current Advances in Peptide Drug Development and Design

by Andy Chi-Lung Lee, Janelle Louise Harris, Kum Kum Khanna and Ji-Hong Hong

Int. J. Mol. Sci. 2019, 20(10), 2383; https://doi.org/10.3390/ijms20102383 - 14 May 2019

Cited by 482 | Viewed by 24603

Abstract

Protein–protein interactions (PPIs) execute many fundamental cellular functions and have served as prime drug targets over the last two decades. Interfering intracellular PPIs with small molecules has been extremely difficult for larger or flat binding sites, as antibodies cannot cross the cell membrane [...] Read more.

Protein–protein interactions (PPIs) execute many fundamental cellular functions and have served as prime drug targets over the last two decades. Interfering intracellular PPIs with small molecules has been extremely difficult for larger or flat binding sites, as antibodies cannot cross the cell membrane to reach such target sites. In recent years, peptides smaller size and balance of conformational rigidity and flexibility have made them promising candidates for targeting challenging binding interfaces with satisfactory binding affinity and specificity. Deciphering and characterizing peptide–protein recognition mechanisms is thus central for the invention of peptide-based strategies to interfere with endogenous protein interactions, or improvement of the binding affinity and specificity of existing approaches. Importantly, a variety of computation-aided rational designs for peptide therapeutics have been developed, which aim to deliver comprehensive docking for peptide–protein interaction interfaces. Over 60 peptides have been approved and administrated globally in clinics. Despite this, advances in various docking models are only on the merge of making their contribution to peptide drug development. In this review, we provide (i) a holistic overview of peptide drug development and the fundamental technologies utilized to date, and (ii) an updated review on key developments of computational modeling of peptide–protein interactions (PepPIs) with an aim to assist experimental biologists exploit suitable docking methods to advance peptide interfering strategies against PPIs. Full article

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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18 pages, 7565 KiB

Open AccessReview

Designed Elastic Networks: Models of Complex Protein Machinery

by Holger Flechsig and Yuichi Togashi

Int. J. Mol. Sci. 2018, 19(10), 3152; https://doi.org/10.3390/ijms19103152 - 13 Oct 2018

Cited by 14 | Viewed by 4265

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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16 pages, 1402 KiB

Open AccessReview

Recent Trends and Applications of Molecular Modeling in GPCR–Ligand Recognition and Structure-Based Drug Design

by Xiaojing Yuan and Yechun Xu

Int. J. Mol. Sci. 2018, 19(7), 2105; https://doi.org/10.3390/ijms19072105 - 20 Jul 2018

Cited by 22 | Viewed by 5949

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

(This article belongs to the Special Issue Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules)

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