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

Designing new drug candidates as inhibitors against wild and mutant type neuraminidases: molecular docking, molecular dynamics and binding free energy calculations

Influenza virus is the cause of the death of millions of people with about 3-4 pandemics every hundred years in history. It also turns into a seasonal disease, bringing about approximately 5-15% of the population to be infected and 290,000-650,000 people to die every year. These numbers reveal that it is necessary to be on the alert to work towards influenza in order to protect public health. There are FDA-approved antiviral drugs such as oseltamivir and zanamivir recommended by the World Center for Disease Prevention. However, after the recent outbreaks such as bird flu and swine flu, increasing studies have shown that the flu virus has gained resistance to these drugs. So, there is an urgent need to find new drugs effective against this virus. This study aims to investigate new drug candidates targeting neuraminidase (NA) for the treatment of influenza by using computer aided drug design approaches. They involve virtual scanning, de novo design, rational design, docking, MD, MMGB/PBSA. The investigation includes H1N1, H5N1, H2N2 and H3N2 neuraminidase proteins and their mutant variants possessing resistance to FDA-approved drugs. Virtual screening consists of approximately 30 thousand molecules while de novo and rational designs produced over a hundred molecules. These approaches produced three lead molecules with binding energies for both non-mutant (-34.84, -59.99 and -60.66 kcal/mol) and mutant (-40.40, -58.93, -76.19 kcal/mol) H2N2 NA calculated by MM-PBSA compared with those of oseltamivir -25.64 and -18.40 respectively. The results offer new drug candidates against influenza infection.Communicated by Ramaswamy H. Sarma.

Uncovering the Resistance Mechanism of Mycobacterium tuberculosis to Rifampicin Due to RNA Polymerase H451D/Y/R Mutations From Computational Perspective

Tuberculosis is still one of the top 10 causes of deaths worldwide, especially with the emergence of multidrug-resistant tuberculosis. Rifampicin, as the most effective first-line antituberculosis drug, also develops resistance due to the mutation on Mycobacterium tuberculosis (Mtb) RNA polymerase. Among these mutations, three mutations at position 451 (H451D, H451Y, H451R) are associated with high-level resistance to rifampicin. However, the resistance mechanism of Mtb to rifampicin is still unclear. In this work, to explore the resistance mechanism of Mtb to rifampicin due to H451D/Y/R mutations, we combined the molecular dynamics simulation, molecular mechanics generalized-Born surface area calculation, dynamic network analysis, and residue interactions network analysis to compare the interaction change of rifampicin with wild-type RNA polymerase and three mutants. The results of molecular mechanics generalized-Born surface area calculations indicate that the binding free energy of rifampicin with three mutants decreases. In addition, the dynamic network analysis and residue interaction network analysis show that when H451 was mutated, the interactions of residue 451 with its adjacent residues such as Q438, F439, M440, D441, and S447 disappeared or weakened, increasing the flexibility of binding pocket. At the same time, the disappearance of hydrogen bonds between R613 and rifampicin caused by the flipping of R613 is another important reason for the reduction of binding ability of rifampicin in H451D/Y mutants. In H451R mutant, the mutation causes the binding pocket change too much so that the position of rifampicin has a large movement in the binding pocket. In this study, the resistance mechanism of rifampicin at the atomic level is proposed. The proposed drug-resistance mechanism will provide the valuable guidance for the design of antituberculosis drugs.

In vivo mallard experiments indicate that zanamivir has less potential for environmental influenza A virus resistance development than oseltamivir

Neuraminidase inhibitors are a cornerstone of influenza pandemic preparedness before vaccines can be mass-produced and thus a neuraminidase inhibitor-resistant pandemic is a serious threat to public health. Earlier work has demonstrated the potential for development and persistence of oseltamivir resistance in influenza A viruses exposed to environmentally relevant water concentrations of the drug when infecting mallards, the natural influenza reservoir that serves as the genetic base for human pandemics. As zanamivir is the major second-line neuraminidase inhibitor treatment, this study aimed to assess the potential for development and persistence of zanamivir resistance in an in vivo mallard model; especially important as zanamivir will probably be increasingly used. Our results indicate less potential for development and persistence of resistance due to zanamivir than oseltamivir in an environmental setting. This conclusion is based on: (1) the lower increase in zanamivir IC₅₀ conferred by the mutations caused by zanamivir exposure (2-17-fold); (2) the higher zanamivir water concentration needed to induce resistance (at least 10 µg l^-1); (3) the lack of zanamivir resistance persistence without drug pressure; and (4) the multiple resistance-related substitutions seen during zanamivir exposure (V116A, A138V, R152K, T157I and D199G) suggesting lack of one straight-forward evolutionary path to resistance. Our study also adds further evidence regarding the stability of the oseltamivir-induced substitution H275Y without drug pressure, and demonstrates the ability of a H275Y-carrying virus to acquire secondary mutations, further boosting oseltamivir resistance when exposed to zanamivir. Similar studies using influenza A viruses of the N2-phylogenetic group of neuraminidases are recommended.

Understanding the cross-resistance of oseltamivir to H1N1 and H5N1 influenza A neuraminidase mutations using multidimensional computational analyses

This study embarks on a comprehensive description of the conformational contributions to resistance of neuraminidase (N1) in H1N1 and H5N1 to oseltamivir, using comparative multiple molecular dynamic simulations. The available data with regard to elucidation of the mechanism of resistance as a result of mutations in H1N1 and H5N1 neuraminidases is not well established. Enhanced post-dynamic analysis, such as principal component analysis, solvent accessible surface area, free binding energy calculations, and radius of gyration were performed to gain a precise insight into the binding mode and origin of resistance of oseltamivir in H1N1 and H5N1 mutants. Three significant features reflecting resistance in the presence of mutations H274Y and I222K, of the protein complexed with the inhibitor are: reduced flexibility of the α-carbon backbone; an improved ΔE_ele of ~15 (kcal/mol) for H1N1 coupled with an increase in ΔG_sol (~13 kcal/mol) from wild-type to mutation; a low binding affinity in comparison with the wild-type of ~2 (kcal/mol) and ~7 (kcal/mol) with respect to each mutation for the H5N1 systems; and reduced hydrophobicity of the overall surface structure due to an impaired hydrogen bonding network. We believe the results of this study will ultimately provide a useful insight into the structural landscape of neuraminidase-associated binding of oseltamivir. Furthermore, the results can be used in the design and development of potent inhibitors of neuraminidases.

A 3D-RISM/RISM study of the oseltamivir binding efficiency with the wild-type and resistance-associated mutant forms of the viral influenza B neuraminidase

The binding affinity of oseltamivir to the influenza B neuraminidase and to its variants with three single substitutions, E119G, R152K, and D198N, is investigated by the MM/3D-RISM method. The binding affinity or the binding free energy of ligand to receptor was found to be determined by a subtle balance of two major contributions that largely cancel out each other: the ligand-receptor interactions and the dehydration free energy. The theoretical results of the binding affinity of the drug to the mutants reproduced the observed trend in the resistivity, measured by IC50 ; the high-level resistance of E119G and R152K, and the low-level resistance of D198N. For E119G and R152K, reduction of the direct drug-target interaction, especially at the mutated residue, is the main source of high-level oseltamivir resistance. This phenomenon, however, is not found in the D198N strain, which is located in the framework of the active-site.

Molecular dynamics, monte carlo simulations, and langevin dynamics: a computational review

Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods.

Molecular basis of R294K mutation effects of H7N9 neuraminidases with drugs and cyclic peptides: an in silico and experimental study

An overview of Shanghai N9/cyclic peptide I complex structure.

Insights from QM/MM Modeling the 3D Structure of the 2009 H1N1 Influenza A Virus Neuraminidase and Its Binding Interactions with Antiviral Drugs

Control of drug release through the inhibition of neuraminidase-1 has been identified as a potential target for the treatment of H1N1 influenza; however, the drug binding mode of neuraminidase is not yet completely understood. In this work, we propose a model for a neuraminidase-1 complex based on four known X-ray structures of drug/neuraminidase-1 complexes. Specifically, H1N1 neuraminidase-1 complexed with 4 drugs (zanamivir, laninamivir, laninamivir octanoate and oseltamivir) was first investigated using a combined quantum mechanical and molecular mechanical (QM/MM) approach. Based on these structures, a model for the H1N1 neuraminidase-1 complex was proposed and simulated using the same computational protocol. Implications to drug/H1N1 neuraminidase-1 binding modes are discussed. From our simulations, the predicted binding free energies of the four drugs are in good agreement with the experimental results, with the correlation coefficient being 0.84.

Molecular modeling and residue interaction network studies on the mechanism of binding and resistance of the HCV NS5B polymerase mutants to VX-222 and ANA598

Hepatitis C virus (HCV) NS5B protein is an RNA-dependent RNA polymerase (RdRp) with essential functions in viral genome replication and represents a promising therapeutic target to develop direct-acting antivirals (DAAs). Multiple nonnucleoside inhibitors (NNIs) binding sites have been identified within the polymerase. VX-222 and ANA598 are two NNIs targeting thumb II site and palm I site of HCV NS5B polymerase, respectively. These two molecules have been shown to be very effective in phase II clinical trials. However, the emergence of resistant HCV replicon variants (L419M, M423T, I482L mutants to VX-222 and M414T, M414L, G554D mutants to ANA598) has significantly decreased their efficacy. To elucidate the molecular mechanism about how these mutations influenced the drug binding mode and decreased drug efficacy, we studied the binding modes of VX-222 and ANA598 to wild-type and mutant polymerase by molecular modeling approach. Molecular dynamics (MD) simulations results combined with binding free energy calculations indicated that the mutations significantly altered the binding free energy and the interaction for the drugs to polymerase. The further per-residue binding free energy decomposition analysis revealed that the mutations decreased the interactions with several key residues, such as L419, M423, L474, S476, I482, L497, for VX-222 and L384, N411, M414, Y415, Q446, S556, G557 for ANA598. These were the major origins for the resistance to these two drugs. In addition, by analyzing the residue interaction network (RIN) of the complexes between the drugs with wild-type and the mutant polymerase, we found that the mutation residues in the networks involved in the drug resistance possessed a relatively lower size of topology centralities. The shift of betweenness and closeness values of binding site residues in the mutant polymerase is relevant to the mechanism of drug resistance of VX-222 and ANA598. These results can provide an atomic-level understanding about the mechanisms of drug resistance conferred by the studied mutations and will be helpful to design more potent inhibitors which could effectively overcome drug resistance of antivirus agents.

Computational study on the drug resistance mechanism against HCV NS3/4A protease inhibitors vaniprevir and MK-5172 by the combination use of molecular dynamics simulation, residue interaction network, and substrate envelope analysis

Hepatitis C virus (HCV) NS3/4A protease is an important and attractive target for anti-HCV drug development and discovery. Vaniprevir (phase III clinical trials) and MK-5172 (phase II clinical trials) are two potent antiviral compounds that target NS3/4A protease. However, the emergence of resistance to these two inhibitors reduced the effectiveness of vaniprevir and MK-5172 against viral replication. Among the drug resistance mutations, three single-site mutations at residues Arg155, Ala156, and Asp168 in NS3/4A protease are especially important due to their resistance to nearly all inhibitors in clinical development. A detailed understanding of drug resistance mechanism to vaniprevir and MK-5172 is therefore very crucial for the design of novel potent agents targeting viral variants. In this work, molecular dynamics (MD) simulation, binding free energy calculation, free energy decomposition, residue interaction network (RIN), and substrate envelope analysis were used to study the detailed drug resistance mechanism of the three mutants R155K, A156T, and D168A to vaniprevir and MK-5172. MD simulation was used to investigate the binding mode for these two inhibitors to wild-type and resistant mutants of HCV NS3/4A protease. Binding free energy calculation and free energy decomposition analysis reveal that drug resistance mutations reduced the interactions between the active site residues and substituent in the P2 to P4 linker of vaniprevir and MK-5172. Furthermore, RIN and substrate envelope analysis indicate that the studied mutations of the residues are located outside the substrate (4B5A) binding site and selectively decrease the affinity of inhibitors but not the activity of the enzyme and consequently help NS3/4A protease escape from the effect of the inhibitors without influencing the affinity of substrate binding. These findings can provide useful information for understanding the drug resistance mechanism against vaniprevir and MK-5172. The results can also provide some potential clues for further design of novel inhibitors that are less susceptible to drug resistance.

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

D222G 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.

Quantitative predictions of binding free energy changes in drug-resistant influenza neuraminidase

Quantitatively predicting changes in drug sensitivity associated with residue mutations is a major challenge in structural biology. By expanding the limits of free energy calculations, we successfully identified mutations in influenza neuraminidase (NA) that confer drug resistance to two antiviral drugs, zanamivir and oseltamivir. We augmented molecular dynamics (MD) with Hamiltonian Replica Exchange and calculated binding free energy changes for H274Y, N294S, and Y252H mutants. Based on experimental data, our calculations achieved high accuracy and precision compared with results from established computational methods. Analysis of 15 µs of aggregated MD trajectories provided insights into the molecular mechanisms underlying drug resistance that are at odds with current interpretations of the crystallographic data. Contrary to the notion that resistance is caused by mutant-induced changes in hydrophobicity of the binding pocket, our simulations showed that drug resistance mutations in NA led to subtle rearrangements in the protein structure and its dynamics that together alter the active-site electrostatic environment and modulate inhibitor binding. Importantly, different mutations confer resistance through different conformational changes, suggesting that a generalized mechanism for NA drug resistance is unlikely.

The capacity of the influenza virus to rapidly mutate and render resistance to a handful of FDA approved neuraminidase (NA) inhibitors represents a significant human health concern. To gain an atomic-level understanding of the mechanisms behind drug resistance, we applied a novel computational approach to characterize resistant NA mutations. These results are comparable in accuracy and precision with the best experimental measurements presently available. To the best of our knowledge, this is the first time that a rigorous computational method has attained the level of certainty needed to predict subtle changes in binding free energies conferred by mutations. Analysis of our simulation data provided a thorough description of the thermodynamics of the binding process for different NA-inhibitor complexes, with findings that in some cases challenge current views based on interpretations of the crystallographic data. While we did not find a generalized mechanism of NA resistance, we identified key differences between oseltamivir and zanamivir that discriminate their responses to the three mutations we considered, namely H274Y, N294S and Y252H. It is worth noting that our approach can be broadly applied to predict resistant mutations to existing and newly developed drugs in other important drug targets.

Combining molecular docking and molecular dynamics to predict the binding modes of flavonoid derivatives with the neuraminidase of the 2009 H1N1 influenza A virus

Control of flavonoid derivatives inhibitors release through the inhibition of neuraminidase has been identified as a potential target for the treatment of H1N1 influenza disease. We have employed molecular dynamics simulation techniques to optimize the 2009 H1N1 influenza neuraminidase X-ray crystal structure. Molecular docking of the compounds revealed the possible binding mode. Our molecular dynamics simulations combined with the solvated interaction energies technique was applied to predict the docking models of the inhibitors in the binding pocket of the H1N1 influenza neuraminidase. In the simulations, the correlation of the predicted and experimental binding free energies of all 20 flavonoid derivatives inhibitors is satisfactory, as indicated by R² = 0.75.