Dabo Pan

Molecular modeling study on the resistance mechanism of HCV NS3/4A serine protease mutants R155K, A156V and D168A to TMC435

Hepatitis C virus (HCV) NS3/4A protease represents an attractive drug target for antiviral therapy. However, drug resistance often occurs, making many protease inhibitors ineffective and allowing viral replication to occur. Herein, based on the recently determined structure of NS3/4A-TMC435 complex, atomic-level models of the key residue mutated (R155K, A156V and D168A) NS3/4A-TMC435 complexes were constructed. Subsequently, by using molecular dynamics simulations, binding free energy calculation and substrate envelope analysis, the structural and energetic changes responsible for drug resistance were investigated. The values of the calculated binding free energy follow consistently the order of the experimental activities. More importantly, the computational results demonstrate that R155K and D168A mutations break the intermolecular salt bridges network at the extended S2 subsite and affect the TMC435 binding, while A156V mutation leads to a significant steric clash with TMC435 and further disrupts the two canonical substrate-like intermolecular hydrogen bond interactions (TMC435(N1-H46)⋯Arg155(O) and Ala157(N-H)⋯TMC435(O2)). In addition, by structural analysis, all the three key residue mutations occur outside the substrate envelope and selectively weaken TMC435s binding affinity without effect on its natural substrate peptide (4B5A). These findings could provide some insights into the resistance mechanism of NS3/4A protease mutants to TMC435 and would be critical for the development of novel inhibitors that are less susceptible to drug resistance.

Understanding the drug resistance mechanism of hepatitis C virus NS3/4A to ITMN-191 due to R155K, A156V, D168A/E mutations: A computational study

BACKGROUND ITMN-191 (RG7227, Danoprevir), as a potential inhibitor of the NS3/4A protease of hepatitis C virus, has been in phase 2 clinical trial. Unfortunately, several ITMN-191 resistance mutants including R155K, A156V, and D168A/E have been identified. METHODS Molecular dynamics simulation, binding free energy calculation and per-residue energy decomposition were employed to explore the binding and resistance mechanism of hepatitis C virus NS3/4A protease to ITMN-191. RESULTS Based on molecular dynamics simulation and per-residue energy decomposition, the nonpolar energy term was found to be the driving force for ITMN-191 binding. For the studied R155K, A156V, D168A/E mutants, the origin of resistance is mainly from the conformational changes of the S4 and extended S2 binding pocket induced by the studied mutants and further leading to the reduced binding ability to the extended P2 and P4 moieties of ITMN-191. CONCLUSIONS Further structural analysis indicates that the destruction of conservative salt bridges between residues 168 and 155 should be responsible for the large conformation changes of the binding pocket in R155K and D168A/E mutants. For A156V mutation, the occurrence of drug resistance is mainly from the changed binding pocket by a replacement of one bulky residue Val. GENERAL SIGNIFICANCE The obtained drug resistance mechanism of this study will provide useful guidance for the development of new and effective HCV NS3/4A inhibitors with low resistance.

Prediction of zanamivir efficiency over the possible 2009 Influenza A (H1N1) mutants by multiple molecular dynamics simulations and free energy calculations

AbstractAs one of the most important antiviral drugs against 2009 influenza A (H1N1), will zanamivir be effective for the possible drug resistant mutants? To answer this question, we combined multiple molecular dynamics simulations and molecular mechanics generalized Born surface area (MM-GBSA) calculations to study the efficiency of zanamivir over the most frequent drug-resistant strains of neuraminidase including R293K, R152K, E119A/D and H275Y mutants. The calculated results indicate that the modeled mutants of the 2009-H1N1 strains except H275Y will be significantly resistant to zanamivir. The resistance to zanamivir is mainly caused by the loss of polar interactions. The identified potential resistance sites in this study will be useful for the development of new effective anti-influenza drugs and to avoid the occurrence of the state without effective drugs to new mutant influenza strains. FigureThe studied mutations of neuraminidase and their influence to zanamivir binding

Molecular mechanism of the enhanced virulence of 2009 pandemic influenza A (H1N1) virus from D222G mutation in the hemagglutinin: a molecular modeling study.

AbstractD222G mutation of the hemagglutinin (HA) is of special interest because of its close association with the enhanced virulence of 2009 pandemic influenza A (H1N1) virus through the increased binding affinity to α2,3-linked sialylated glycan receptors. However, there is still a lack of detailed understanding about the molecular mechanism of this enhanced virulence. Here, molecular dynamics simulation and binding free energy calculation were performed to explore the altered glycan receptor binding mechanism of HA upon the D222G mutation by studying the interaction of one α2,3-linked sialylglycan (sequence: SIA-GAL-NAG) with the wild type and D222G mutated HA. The binding free energy calculation based on the molecular mechanics generalized Born surface area (MM-GBSA) method indicates that the D222G mutated HA has a much stronger binding affinity with the studied α2,3-linked glycan than the wild type. This is consistent with the experimental result. The increased binding free energy of D222G mutant mainly comes from the increased energy contribution of Gln223. The structural analysis proves that the altered electrostatic potential of receptor binding domain (RBD) and the increased flexibility of 220-loop are the essential reasons leading to the increased affinity of HA to α2,3-linked sialic acid glycans. The obtained results of this study have allowed a deeper understanding of the receptor recognition mechanism and the pathogenicity of influenza virus, which will be valuable to the structure-based inhibitors design targeting influenza virus entry process. FigureThe altered α-2,3 linked glycan binding to hemagglutinin upon D222G mutation

Influence of Chirality of Crizotinib on Its MTH1 Protein Inhibitory Activity: Insight from Molecular Dynamics Simulations and Binding Free Energy Calculations

As a promising target for the treatment of lung cancer, the MutT Homolog 1 (MTH1) protein can be inhibited by crizotinib. A recent work shows that the inhibitory potency of (S)-crizotinib against MTH1 is about 20 times over that of (R)-crizotinib. But the detailed molecular mechanism remains unclear. In this study, molecular dynamics (MD) simulations and free energy calculations were used to elucidate the mechanism about the effect of chirality of crizotinib on the inhibitory activity against MTH1. The binding free energy of (S)-crizotinib predicted by the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and Adaptive biasing force (ABF) methodologies is much lower than that of (R)-crizotinib, which is consistent with the experimental data. The analysis of the individual energy terms suggests that the van der Waals interactions are important for distinguishing the binding of (S)-crizotinib and (R)-crizotinib. The binding free energy decomposition analysis illustrated that residues Tyr7, Phe27, Phe72 and Trp117 were important for the selective binding of (S)-crizotinib to MTH1. The adaptive biasing force (ABF) method was further employed to elucidate the unbinding process of (S)-crizotinib and (R)-crizotinib from the binding pocket of MTH1. ABF simulation results suggest that the reaction coordinates of the (S)-crizotinib from the binding pocket is different from (R)-crizotinib. The results from our study can reveal the details about the effect of chirality on the inhibition activity of crizotinib to MTH1 and provide valuable information for the design of more potent inhibitors.

Computational study on the unbinding pathways of B-RAF inhibitors and its implication for the difference of residence time: insight from random acceleration and steered molecular dynamics simulations

B-RAF kinase is a clinically validated target implicated in melanoma and advanced renal cell carcinoma (RCC). PLX4720 and TAK-632 are promising inhibitors against B-RAF with different dissociation rate constants (k(off)), but the specific mechanism that determines the difference of their dissociation rates remains unclear. In order to understand the kinetically different behaviors of these two inhibitors, their unbinding pathways were explored by random acceleration and steered molecular dynamics simulations. The random acceleration molecular dynamics (RAMD) simulations show that PLX4720 dissociates along the ATP-channel, while TAK-632 dissociates along either the ATP-channel or the allosteric-channel. The steered molecular dynamics (SMD) simulations reveal that TAK-632 is more favorable to escape from the binding pocket through the ATP-channel rather than the allosteric-channel. The PMF calculations suggest that TAK-632 presents longer residence time, which is in qualitative agreement with the experimental k(off)(k(off) = 3.3 × 10(-2) s(-1) and ΔG(off) = -82.17 ± 0.29 kcal mol(-1) for PLX4720; k(off) = 1.9 × 10(-5) s(-1) and ΔG(off) = -39.73 ± 0.79 kcal mol(-1) for PLX4720). Furthermore, the binding free decomposition by MM/GBSA illustrates that the residues K36, E54, V57, L58, L120, I125, H127, G146 and D147 located around the allosteric binding pocket play important roles in determining the longer residence time of TAK-632 by forming stronger hydrogen bond and hydrophobic interactions. Our simulations provide valuable information to design selective B-RAF inhibitors with long residence time in the future.

Exploring the molecular basis of dsRNA recognition by NS1 protein of influenza A virus using molecular dynamics simulation and free energy calculation

The frequent outbreak of influenza pandemic and the limited available anti-influenza drugs highlight the urgent need for the development of new antiviral drugs. The dsRNA-binding surface of nonstructural protein 1 of influenza A virus (NS1A) is a promising target. The detailed understanding of NS1A-dsRNA interaction will be valuable for structure-based anti-influenza drug discovery. To characterize and explore the key interaction features between dsRNA and NS1A, molecular dynamics simulation combined with MM-GBSA calculations were performed. Based on the MM-GBSA calculations, we find that the intermolecular van der Waals interaction and the nonpolar solvation term provide the main driving force for the binding process. Meanwhile, 17 key residues from NS1A were identified to be responsible for the dsRNA binding. Compared with the wild type NS1A, all the studied mutants S42A, T49A, R38A, R35AR46A have obvious reduced binding free energies with dsRNA reflecting in the reduction of the polar and/or nonpolar interactions. In addition, the structural and energy analysis indicate the mutations have a small effect to the backbone structures but the loss of side chain interactions is responsible for the decrease of the binding affinity. The uncovering of NS1A-dsRNA recognition mechanism will provide some useful insights and new chances for the development of anti-influenza drugs.

Search for β2 adrenergic receptor ligands by virtual screening via grid computing and investigation of binding modes by docking and molecular dynamics simulations.

We designed a program called MolGridCal that can be used to screen small molecule database in grid computing on basis of JPPF grid environment. Based on MolGridCal program, we proposed an integrated strategy for virtual screening and binding mode investigation by combining molecular docking, molecular dynamics (MD) simulations and free energy calculations. To test the effectiveness of MolGridCal, we screened potential ligands for β2 adrenergic receptor (β2AR) from a database containing 50,000 small molecules. MolGridCal can not only send tasks to the grid server automatically, but also can distribute tasks using the screensaver function. As for the results of virtual screening, the known agonist BI-167107 of β2AR is ranked among the top 2% of the screened candidates, indicating MolGridCal program can give reasonable results. To further study the binding mode and refine the results of MolGridCal, more accurate docking and scoring methods are used to estimate the binding affinity for the top three molecules (agonist BI-167107, neutral antagonist alprenolol and inverse agonist ICI 118,551). The results indicate agonist BI-167107 has the best binding affinity. MD simulation and free energy calculation are employed to investigate the dynamic interaction mechanism between the ligands and β2AR. The results show that the agonist BI-167107 also has the lowest binding free energy. This study can provide a new way to perform virtual screening effectively through integrating molecular docking based on grid computing, MD simulations and free energy calculations. The source codes of MolGridCal are freely available at http://molgridcal.codeplex.com.

Effects of the Pathogenic Mutation A117V and the Protective Mutation H111S on the Folding and Aggregation of PrP106-126: Insights from Replica Exchange Molecular Dynamics Simulations

The fragment 106-126 of prion protein exhibits similar properties to full-length prion. Experiments have shown that the A117V mutation enhances the aggregation of PrP106-126, while the H111S mutation abolishes the assembly. However, the mechanism of the change in the aggregation behavior of PrP106-126 upon the two mutations is not fully understood. In this study, replica exchange molecular dynamics simulations were performed to investigate the conformational ensemble of the WT PrP106-126 and its two mutants A117V and H111S. The obtained results indicate that the three species are all intrinsically disordered but they have distinct morphological differences. The A117V mutant has a higher propensity to form β-hairpin structures than the WT, while the H111S mutant has a higher population of helical structures. Furthermore, the A117V mutation increases the hydrophobic solvent accessible surface areas of PrP106-126 and the H111S mutation reduces the exposure of hydrophobic residues. It can be concluded that the difference in populations of β-hairpin structures and the change of hydrophobic solvent accessible areas may induce the different aggregation behaviors of the A117V and the H111S mutated PrP106-126. Understanding why the two mutations have contrary effects on the aggregation of PrP106-126 is very meaningful for further elucidation of the mechanism underlying aggregation and design of inhibitor against aggregation process.