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

Pharmacophore-Assisted Covalent Docking Identifies a Potential Covalent Inhibitor for Drug-Resistant Genotype 3 Variants of Hepatitis C Viral NS3/4A Serine Protease

The emergence of drug-resistance-inducing mutations in Hepatitis C virus (HCV) coupled with genotypic heterogeneity has made targeting NS3/4A serine protease difficult. In this work, we investigated the mutagenic variations in the binding pocket of Genotype 3 (G3) HCV NS3/4A and evaluated ligands for efficacious inhibition. We report mutations at 14 positions within the ligand-binding residues of HCV NS3/4A, including H57R and S139P within the catalytic triad. We then modelled each mutational variant for pharmacophore-based virtual screening (PBVS) followed by covalent docking towards identifying a potential covalent inhibitor, i.e., cpd-217. The binding stability of cpd-217 was then supported by molecular dynamic simulation followed by MM/GBSA binding free energy calculation. The free energy decomposition analysis indicated that the resistant mutants alter the HCV NS3/4A-ligand interaction, resulting in unbalanced energy distribution within the binding site, leading to drug resistance. Cpd-217 was identified as interacting with all NS3/4A G3 variants with significant covalent docking scores. In conclusion, cpd-217 emerges as a potential inhibitor of HCV NS3/4A G3 variants that warrants further in vitro and in vivo studies. This study provides a theoretical foundation for drug design and development targeting HCV G3 NS3/4A.

Insight into the molecular recognition of human and polar bear pregnane X receptor by three organic pollutants using molecular docking and molecular dynamics simulations

Pregnane X receptor (PXR) is a heterologous biosensor that is involved in the metabolic pathway of environmental pollutants, regulating the transcription of genes involved in biotransformation. There are significant differences in the selectivity and specificity of organic pollutants (OPs) toward polar bear PXR (pbPXR) and human PXR (hPXR), but the detailed dynamical characteristics of their interactions are unclear. Homology Modeling, molecular docking, molecular dynamics simulation, and free energy calculation were used to analyze the recognition of pbPXR and hPXR by three OPs: BPA, chlordane and toxaphene. Comparing interaction patterns along with binding free energy of pbPXR and hPXR with these three OPs revealed that although pbPXR and hPXR interact similar with these three OPs, these OPs have different effects on the internal dynamics of pbPXR and hPXR. This results in significant alterations in the interaction of key residues near Leu209, Met243, Phe288, Met323, and His407 with OPs, thereby influencing their binding energy. Non-polar interactions, especially van der Waals interactions, were found to be the dominating factors in interacting of these OPs with PXRs. The region surrounding these key residues facilitates hydrophobic contacts with PXR, which are crucial for the selective activation of PXRs in different species by these three OPs. These findings are of significant guidance in understanding the impacts of environmental endocrine disruptors on different organisms.

Exploring theophylline-1,2,4-triazole tethered N-phenylacetamide derivatives as antimicrobial agents: unraveling mechanisms via structure-activity relationship, in vitro validation, and in silico insights

Theophylline, a nitrogen-containing heterocycle, serves as a promising focal point for medicinal researchers aiming to create derivatives with diverse pharmacological applications. In this work, we present an improved synthetic method for a range of theophylline-1,2,4-triazole-S-linked N-phenyl acetamides (4a‒g) utilizing ultrasound-assisted synthetic approach. The objective was to assess the effectiveness of synthesized theophylline-1,2,4-triazoles (4a‒g) as inhibitors of HCV serine protease and as antibacterial agents against B. subtilis QB-928 and E. coli AB-274. Theophylline-1,2,4-triazoles were obtained in good to excellent yields (69%-95%) in a shorter time than conventional approach. 4-Chlorophenyl moiety containing theophylline-1,2,4-triazole 4c displayed significantly higher inhibitory activity against HCV serine protease enzyme (IC50 = 0.015 ± 0.25 mg) in comparison to ribavirin (IC50 = 0.165 ± 0.053 mg), but showed excellent binding affinity (-7.55 kcal/mol) with the active site of serine protease, better than compound 4c (-6.90 kcal/mol) as well as indole-based control compound 5 (-7.42 kcal/mol). In terms of percentage inhibition of serine protease, 2-chlorophenyl compound 4b showed the maximum percentage inhibition (86%), more than that of the 3,4-dichlorophenyl compound 4c (76%) and ribavirin (81%). 3,4-Dimethylphenyl-based theophylline-1,2,4-triazole 4g showed the lowest minimum inhibitory concentration (MIC = 0.28 ± 0.50 μg/mL) against the B. subtilis bacterial strain as compared to the standard drug penicillin (MIC = 1 ± 1.50 μg/mL). The other 4-methylphenyl theophylline-1,2,4-triazole 4e (MIC = 0.20 ± 0.08 μg/mL) displayed the most potent antibacterial potential against E. coli in comparison to the standard drug penicillin (MIC = 2.4 ± 1.00 μg/mL). Molecular docking studies further helped in an extensive understanding of all of the interactions between compounds and the enzyme active site, and DFT studies were also employed to gain insights into the molecular structure of the synthesized compounds. The results indicated that theophylline-linked triazole derivatives 4b and 4c showed promise as leading contenders in the fight against the HCV virus. Moreover, compounds 4e and 4g demonstrated potential as effective chemotherapeutic agents against E. coli and B. subtilis, respectively. To substantiate these findings, additional in vivo studies and clinical trials are imperative, laying the groundwork for their integration into future drug design and development.

Discovery of Novel Inhibitors of BRD4 for Treating Prostate Cancer: A Comprehensive Case Study for Considering Water Networks in Virtual Screening and Drug Design

Androgen receptor (AR) is the primary target for treating prostate cancer (PCa), which inevitably progresses due to drug-resistant mutations. Bromodomain-containing protein 4 (BRD4) has been a new potential drug target for PCa treatment. Herein, we report the rational design and discovery of novel BRD4 inhibitors through computer-aided drug design (CADD), and a hit compound SQ-1 (IC50 = 676 nM) was identified by structure-based virtual screening (SBVS) with the conserved water network. To optimize the structure of SQ-1, the free energy landscape was constructed, and the binding mechanism was explored by characterizing the water profile and the dissociation mechanism. Finally, the compound SQ-17 with improved inhibitory activity (IC50 < 100 nM) was discovered, which showed potent antiproliferative activity against LNCaP. These data highlighted a successful attempt to identify and optimize a small molecule by comprehensive CADD application and provided essential clues for developing novel therapeutics for PCa treatment.

Artificial Intelligence in Drug Discovery: A Bibliometric Analysis and Literature Review

Drug discovery is a complex and iterative process, making it ideal for using artificial intelligence (AI). This paper uses a bibliometric approach to reveal AI's trend and underlying structure in drug discovery (AIDD). A total of 4310 journal articles and reviews indexed in Scopus were analyzed, revealing that AIDD has been rapidly growing over the past two decades, with a significant increase after 2017. The United States, China, and the United Kingdom were the leading countries in research output, with academic institutions, particularly the Chinese Academy of Sciences and the University of Cambridge, being the most productive. In addition, industrial companies, including both pharmaceutical and high-tech ones, also made significant contributions. Additionally, this paper thoroughly discussed the evolution and research frontiers of AIDD, which were uncovered through co-occurrence analyses of keywords using VOSviewer. Our findings highlight that AIDD is an interdisciplinary and promising research field that has the potential to revolutionize drug discovery. The comprehensive overview provided here will be of significant interest to researchers, practitioners, and policy-makers in related fields. The results emphasize the need for continued investment and collaboration in AIDD to accelerate drug discovery, reduce costs, and improve patient outcomes.

Free energy landscape and thermodynamics properties of novel mutations in PncA of pyrazinamide resistance isolates of Mycobacterium tuberculosis

Pyrazinamide (PZA) is one of the first-line antituberculosis therapy, active against non-replicating Mycobacterium tuberculosis (Mtb). The conversion of PZA into pyrazinoic acid (POA), the active form, required the activity of pncA gene product pyrazinamidase (PZase) activity. Mutations occurred in pncA are the primary cause behind the PZA resistance. However, the resistance mechanism is important to explore using high throughput computational approaches. Here we aimed to explore the mechanism of PZA resistance behind novel P62T, L120R, and V130M mutations in PZase using 200 ns molecular dynamics (MD) simulations. MD simulations were performed to observe the structural changes for these three mutants (MTs) compared to the wild types (WT). Root means square fluctuation, the radius of gyration, free energy landscape, root means square deviation, dynamic cross-correlation motion, and pocket volume were found in variation between WT and MTs, revealing the effects of P62T, L120R, and V130M. The free energy conformational landscape of MTs differs significantly from the WT system, lowering the binding of PZA. The geometric shape complementarity of the drug (PZA) and target protein (PZase) further confirmed that P62T, L120R, and V130M affect the protein structure. These effects on PZase may cause vulnerability to convert PZA into POA.Communicated by Ramaswamy H. Sarma.

Electrostatics in Computational Biophysics and Its Implications for Disease Effects

This review outlines the role of electrostatics in computational molecular biophysics and its implication in altering wild-type characteristics of biological macromolecules, and thus the contribution of electrostatics to disease mechanisms. The work is not intended to review existing computational approaches or to propose further developments. Instead, it summarizes the outcomes of relevant studies and provides a generalized classification of major mechanisms that involve electrostatic effects in both wild-type and mutant biological macromolecules. It emphasizes the complex role of electrostatics in molecular biophysics, such that the long range of electrostatic interactions causes them to dominate all other forces at distances larger than several Angstroms, while at the same time, the alteration of short-range wild-type electrostatic pairwise interactions can have pronounced effects as well. Because of this dual nature of electrostatic interactions, being dominant at long-range and being very specific at short-range, their implications for wild-type structure and function are quite pronounced. Therefore, any disruption of the complex electrostatic network of interactions may abolish wild-type functionality and could be the dominant factor contributing to pathogenicity. However, we also outline that due to the plasticity of biological macromolecules, the effect of amino acid mutation may be reduced, and thus a charge deletion or insertion may not necessarily be deleterious.

Interdisciplinary in silico studies to understand in-depth molecular level mechanism of drug resistance involving NS3-4A protease of HCV

Hepatitis C virus (HCV) causes hepatitis, a life-threatening disease responsible for liver cirrhosis. Urgent measures have been taken to develop therapeutics against this deadly pathogen. NS3/4A protease is an extremely important target. A series of inhibitors have been developed against this viral protease including Faldaprevir. Unfortunately, the error-prone viral RNA polymerase causes the emergence of resistance, thereby causing reduced effectiveness of those peptidomimetic inhibitors. Among the drug resistant variants, three single amino acid residues (R155, A156 and D168) are notable for their presence in clinical isolates and also their effectivity against most of the known inhibitors in clinical development. Therefore, it is crucial to understand the mechanistic role of those drug resistant variants while designing potent novel inhibitors. In this communication, we have deeply analyzed through using in silico studies to understand the molecular mechanism of alteration of inhibitor binding between wild type and its R155K, A156V and D168V variants. Principal component analysis was carried to identify the backbone fluctuations of important residues in HCV NS3/4A responsible for the inhibitor binding and maintaining drug resistance. Free energy landscape as a function of the principal components has been used to identify the stability and conformation of the key residues that regulate inhibitor binding and their impact in developing drug resistance. Our findings are consistent with the trend of experimental results. The observations are also true in case of other Faldaprevir-like peptidomimetic inhibitors. Understanding this binding mechanism would be significant for the development of novel inhibitors with less susceptibility towards drug resistance.

Exploring of paritaprevir and glecaprevir resistance due to A156T mutation of HCV NS3/4A protease: molecular dynamics simulation study

Hepatitis C virus (HCV) NS3/4A serine protease is a promising drug target for the discovery of anti-HCV drugs. However, its amino acid mutations, particularly A156T, commonly lead to rapid emergence of drug resistance. Paritaprevir and glecaprevir, the newly FDA-approved HCV drugs, exhibit distinct resistance profiles against the A156T mutation of HCV NS3/4A serine protease. To illustrate their different molecular resistance mechanisms, molecular dynamics simulations and binding free energy calculations were carried out on the two compounds complexed with both wild-type (WT) and A156T variants of HCV NS3/4A protease. QM/MM-GBSA-based binding free energy calculations revealed that the binding affinities of paritaprevir and glecaprevir towards A156T NS3/4A were significantly reduced by ∼4 kcal/mol with respect to their WT complexes, which were in line with the experimental resistance folds. Moreover, the relatively weak intermolecular interactions with amino acids such as H57, R155, and T156 of NS3 protein, the steric effect and the destabilized protein binding surface, which is caused by the loss of salt bridge between R123 and D168, are the main contributions for the higher fold-loss in potency of glecaprevir due to A156T mutation. An insight into the difference of molecular mechanism of drug resistance against the A156T substitution among the two classes of serine protease inhibitors could be useful for further optimization of new generation HCV NS3/4A inhibitors with enhanced inhibitory potency.Communicated by Ramaswamy H. Sarma.

Mechanistic analysis of A46V, H57Y, and D129N in pyrazinamidase associated with pyrazinamide resistance

Pyrazinamide (PZA) is a component of first-line drugs, active against latent Mycobacterium tuberculosis (MTB) isolates. The prodrug is activated into the active form, pyrazinoic acid (POA) via pncA gene-encoded pyrazinamidase (PZase). Mutations in pncA have been reported, most commonly responsible for PZA-resistance in more than 70% of the resistant cases. In our previous study, we detected many mutations in PZase among PZA-resistance MTB isolates including A46V, H71Y, and D129N. The current study was aimed to investigate the molecular mechanism of PZA-resistance behind mutants (MTs) A46V, H71Y, and D129N in comparison with the wild type (WT) through molecular dynamic (MD) simulation. MTB positive samples were subjected to PZA drug susceptibility testing (DST) against critical concentration (100ug/ml). The resistant samples were subjected to pncA sequencing. Thirty-six various mutations have been observed in the coding region of pncA of PZA-resistant isolates (GenBank accession No. MH461111) including A46V, H71Y, and D129N. The post-simulation analysis revealed a significant variation in MTs structural dynamics as compared to the WT. Root means square deviations (RMSD) and Root means square fluctuation (RMSF) has been found in variation between WT and MTs. Folding effect and pocket volume were altered in MTs when compared with WT. Geometric matching supports the effect of mutation A46V, H71Y, and D129N on PZase structure that may have an insight effect on PZase dynamics, making them vulnerable to convert pro-PZA into active form, POA. In conclusion, the current analyses will provide useful information behind PZA-resistance for better management of drug-resistant TB.

Pyrazinamide resistance of novel mutations in pncA and their dynamic behavior

Pyrazinamide (PZA) is one of the essential anti-mycobacterium drugs, active against non-replicating Mycobacterium tuberculosis (MTB) isolates. PZA is converted into its active state, called pyrazinoic acid (POA), by action of pncA encoding pyrazinamidase (PZase). In the majority of PZA-resistance isolates, pncA harbored mutations in the coding region. In our recent report, we detected a number of novel variants in PZA-resistance (PZA^R) MTB isolates, whose resistance mechanisms were yet to be determined. Here we performed several analyses to unveil the PZA^R mechanism of R123P, T76P, G150A, and H71R mutants (MTs) through molecular dynamics (MD) simulations. In brief, culture positive MTB isolates were subjected to PZA susceptibility tests using the WHO recommended concentration of PZA (100 μg ml⁻¹). The PZA^R samples were screened for mutations in pncA along sensitive isolates through polymerase chain reactions and sequencing. A large number of variants (GeneBank accession no. MH461111), including R123P, T76P, G150A, and H71R, have been spotted in more than 70% of isolates. However, the mechanism of PZA^R for mutants (MTs) R123P, T76P, G150A, and H71R was unknown. For the MTs and native PZase structures (WT), thermodynamic properties were compared using molecular dynamics simulations for 100 ns. The MTs structural activity was compared to the WT. Folding effect and pocket volume variations have been detected when comparing between WT and MTs. Geometric matching further confirmed the effect of R123P, T76P, G150A, and H71R mutations on PZase dynamics, making them vulnerable for activating the pro-drug into POA. This study offers a better understanding for management of PZA^R TB. The results may be used as alternative diagnostic tools to infer PZA resistance at a structural dynamics level.

We performed several analyses to unveil the pyrazinamide-resistance mechanism of R123P, T76P, G150A, and H71R mutants through molecular dynamics simulations.

Potent novel inhibitors against hepatitis C virus NS3 (HCV NS3 GT-3a) protease domain

HCV NS3, a non-structural hepatitis C viral protein is used as one of the potential targets for inhibition by direct-acting antivirals. It is known that the success rate for HCV genotype-1 treatment remained very high, however, treatment of genotype-3a (GT-3a), is still quite challenging. In the current study, the HCV GT-3a full-length NS3 gene was amplified and sequenced. The complete nucleotide sequence was translated into the amino acid sequence and homology models of HCV-NS3 GT-3a were generated by HCV-NS3 genotype-1b as a template. The objective of the study was to screen novel therapeutic hits from large databases. For this aim, various small molecule databases including, BindingDB (∼45.000 compounds), NCI (∼265.000 compounds), and Specs-SC (∼212.000 compounds) were used. Firstly, all of the compounds were screened using binary-QSAR models from the MetaCore/MetaDrug server, and compounds were filtered based on therapeutic activity predictions by the anti-viral QSAR model. Filtered molecules were used in 26 different toxicity QSAR models and active non-toxic compounds were identified. These selected molecules were then used in docking and molecular dynamics (MD) simulations studies at the binding cavities of the NS3 protease domain of the GT-3a. Results were compared with known inhibitors and novel molecules are proposed against HCV-NS3 GT-3a. These molecules have high ligand efficiencies as compared to the reference molecules suggesting a better alternate to the existing suite of inhibitors. Thus, this study will be a step ahead in the development of new potential compounds as antiviral drugs for the GT-3a target.

Gibbs Free Energy Calculation of Mutation in PncA and RpsA Associated With Pyrazinamide Resistance

A central approach for better understanding the forces involved in maintaining protein structures is to investigate the protein folding and thermodynamic properties. The effect of the folding process is often disturbed in mutated states. To explore the dynamic properties behind mutations, molecular dynamic (MD) simulations have been widely performed, especially in unveiling the mechanism of drug failure behind mutation. When comparing wild type (WT) and mutants (MTs), the structural changes along with solvation free energy (SFE), and Gibbs free energy (GFE) are calculated after the MD simulation, to measure the effect of mutations on protein structure. Pyrazinamide (PZA) is one of the first-line drugs, effective against latent Mycobacterium tuberculosis isolates, affecting the global TB control program 2030. Resistance to this drug emerges due to mutations in pncA and rpsA genes, encoding pyrazinamidase (PZase) and ribosomal protein S1 (RpsA) respectively. The question of how the GFE may be a measure of PZase and RpsA stabilities, has been addressed in the current review. The GFE and SFE of MTs have been compared with WT, which were already found to be PZA-resistant. WT structures attained a more stable state in comparison with MTs. The physiological effect of a mutation in PZase and RpsA may be due to the difference in energies. This difference between WT and MTs, depicted through GFE plots, might be useful in predicting the stability and PZA-resistance behind mutation. This study provides useful information for better management of drug resistance, to control the global TB problem.

Structural Dynamics Behind Clinical Mutants of PncA-Asp12Ala, Pro54Leu, and His57Pro of Mycobacterium tuberculosis Associated With Pyrazinamide Resistance

Pyrazinamide (PZA) is one of the main FDA approved drugs to be used as the first line of defense against Mycobacterium Tuberculosis (MTB). It is activated into pyrazinoic acid (POA) via MTB's pncA gene-encoded pyrazinamidase (PZase). Mutations are most commonly responsible for PZA-resistance in nearly 70% of the resistant samples. In the present work, MTB positive samples were chosen for PZA drug susceptibility testing (DST) against critical concentration (100 ug/ml) of PZA. The resistant samples were subjected to pncA sequencing. As a result, 36 various mutations have been observed in the PZA resistant samples, uploaded to the NCBI (GeneBank accession no. MH461111). Here we report the mechanism of PZA resistance behind the three mutants (MTs), Asp12Ala, Pro54Leu, and His57Pro in comparison with the wild type (WT) through molecular dynamics simulation to unveil how these mutations affect the overall conformational stability. The post-simulation analyses revealed notable deviations as compared to the WT structure. Molecular docking studies of PZA with MTs and WT, pocket volume inspection and overall shape complementarity analysis confirmed the deleterious nature of these mutations and gave an insight into the mechanism behind PZA-resistance. These analyses provide vital information regarding MTB drug resistance and could be extremely useful in therapy management and overcoming its global burden.

Understanding of the drug resistance mechanism of hepatitis C virus NS3/4A to paritaprevir due to D168N/Y mutations: A molecular dynamics simulation perspective

Hepatitis C virus (HCV) NS3/4A protease is an attractive target for the development of antiviral therapy. However, the evolution of antiviral drug resistance is a major problem for treatment of HCV infected patients. Understanding of drug-resistance mechanisms at molecular level is therefore very important for the guidance of further design of antiviral drugs with high efficiency and specificity. Paritaprevir is a potent inhibitor against HCV NS3/4A protease genotype 1a. Unfortunately, this compound is highly susceptible to the substitution at D168 in the protease. In this work, molecular dynamics simulations of paritaprevir complexed with wild-type (WT) and two mutated strains (D168 N and D168Y) were carried out. Due to such mutations, the inhibitor-protein hydrogen bonding between them was weakened and the salt-bridge network among residues R123, R155 and D168 responsible for inhibitor binding was disrupted. Moreover, the per-residue free energy decomposition suggested that the main contributions from key residues such as Q80, V132, K136, G137 and R155 were lost in the D168 N/Y mutations. These lead to a lower binding affinity of paritaprevir for D168 N/Y variants of the HCV NS3/4A protease, consistent with the experimental data. This detailed information could be useful for further design of high potency anti-HCV NS3/4A inhibitors.

Identification of potential inhibitors for HCV NS5b of genotype 4a by combining dynamic simulation, protein-ligand interaction fingerprint, 3D pharmacophore, docking and 3D QSAR

HCV NS5B polymerase has been one of the most attractive targets for developing new drugs for HCV infection and many drugs were successfully developed, but all of them were designed for targeting Hepatitis C Virus genotype 1 (HCV GT1). Hepatitis C virus genotype 4a (HCV GT4a) dominant in Egypt has paid less attention. Here, we describe our protocol of virtual screening in identification of novel potential potent inhibitors for HCV NS5B polymerase of GT4a using homology modeling, protein-ligand interaction fingerprint (PLIF), docking, pharmacophore, and 3D CoMFA quantitative structure activity relationship (QSAR). Firstly, a high-quality 3D model of HCV NS5B polymerase of GT4a was constructed using crystal structure of HCV NS5B polymerase of GT1 (PDB ID: 3hkw) as a template. Then, both the model and the template were simulated to compare conformational stability. PLIF was generated using five crystal structures of HCV NS5B (PDB ID: 4mia, 4mib, 4mk9, 4mka, and 4mkb), which revealed the most important residues and their interactions with the co-crystalized ligands. After that, a 3D pharmacophore model was developed from the generated PLIF data and then used as a screening filter for 17000328 drug-like zinc database compounds. 900 compounds passed the pharmacophore filter and entered the docking-based virtual screening stage. Finally, a 3D CoMFA QSAR was developed using 42 compounds as a training and 19 compounds as a test set. The 3D CoMFA QSAR was used to design and screen some potential inhibitors, these compounds were further evaluated by the docking stage. The highest ranked five hits from docking result (compounds (p1-p4) and compound q1) were selected for further analysis.Communicated by Ramaswamy H. Sarma.

Characterization of HCV resistance from a 3-day monotherapy study of voxilaprevir, a novel pangenotypic NS3/4A protease inhibitor

BACKGROUND

Voxilaprevir (VOX; GS-9857) is a pangenotypic HCV NS3/4A protease inhibitor (PI) with potent antiviral activity against HCV genotypes (GTs) 1-6 and improved coverage of GT1 NS3 resistance-associated substitutions (RAS) associated with other HCV PIs. In a 3-day Phase Ib monotherapy study in patients infected with HCV GT1a, 1b, 2, 3 and 4, VOX was well-tolerated and resulted in maximal mean viral load reduction >3 log₁₀ IU/ml at the 100 mg dose across all genotypes evaluated. This report characterizes the HCV NS3 RAS in the study.

METHODS

The NS3 gene was amplified and successfully deep sequenced using MiSeq for 66 patients at baseline and 61 patients post-baseline using 15% and 1% assay cutoffs.

RESULTS

With a 15% assay cutoff, pretreatment HCV NS3 RAS were present in the HCV of 38% (9/24) of patients with GT1a and 5% (1/19) with GT3a; there were no pretreatment NS3 RAS present in patients with GT1b (n=6), GT2 (n=7) or GT4 (n=4). In patients with and without pretreatment NS3 RAS, ≥3.4 log₁₀ mean maximal viral load reductions over 3 days of VOX administration were observed. The majority of patients did not have detectable treatment-emergent NS3 RAS and only 12% (7/53) and 26% (14/53) had emergent NS3 RAS using 15% and 1% cutoffs, respectively. No NS3 RAS were detected in patients with GT2 or GT4. A156T or A156V were the most prevalent emergent NS3 RAS in patients with GT1a or GT1b infection, but were not observed in patients with GT3 infection.

CONCLUSIONS

The lack of selection of NS3 RAS in the majority of patients demonstrates a high resistance barrier for VOX. ClinicalTrails.gov identifier NCT02185794.

Computational analysis of naturally occurring resistance-associated substitutions in genes NS3, NS5A, and NS5B among 86 subtypes of hepatitis C virus worldwide

Background and objective

Direct-acting antivirals (DAA) facing resistance continue to be used in some areas worldwide. Thus, identifying hepatitis C virus (HCV) genotypes/subtypes and loci with certain prevalent resistance-associated substitutions (RASs) deserves attention. We investigated the global and regional frequencies of naturally occurring RASs among all confirmed HCV subtypes (n=86) and explored co-occurring and mutually exclusive RAS pairs within and between genes NS3, NS5A, and NS5B.

Methods

A total of 213,908 HCV sequences available as of July 10, 2019 were retrieved from the NCBI nucleotide database. After curation, 17,312 NS3, 8,478 NS5A, and 25,991 NS5B sequence fragments from DAA-naïve patients were screened for RASs. MEGA 6.0 was used to translate aligned nucleotide sequences into amino acid sequences, and RAS pairs were identified by hypergeometric analysis.

Results

RAS prevalence varied significantly among HCV subtypes. For example, D168E, highly resistanct to all protease inhibitors except voxilaprevir, was nearly absent in all subtypes except in 43.48% of GT5a sequences. RASs in NS3 exhibiting significantly different global distribution included Q80K in GT1a with the highest frequency in North America (54.49%), followed by in Europe (22.66%), Asia (6.98%), Oceania (6.62%), and South America (1.03%). The prevalence of NS3 S122G in GT1b was highest in Asia (26.6%) and lowest in Europe (2.64%). NS5A L28M, R30Q, and Y93H in GT1b, L31M in GT2b, and NS5B C316N in GT1b was most prevalent in Asia. A150V in GT3a, associated with sofosbuvir treatment failure, was most prevalent in Asia (44.09%), followed by Europe (31.19%), Oceania (24.29%), and North America (19.05%). Multiple mutually exclusive or co-occurring RAS pairs were identified, including Q80K+R155K and R155K+D168G in GT1a and L159F+C316N and R30Q (NS5A)+C316N (NS5B) in GT1b.

Conclusion

Our data may be of special relevance for those countries where highly effective antivirals might not be available. Considering the specific RASs prevalence will help the clinicians to make optimal treatment choices. The RASs pairs would benefit anti-HCV drug development.

Structural dynamics behind variants in pyrazinamidase and pyrazinamide resistance

Pyrazinamide (PZA) is an important component of first-line anti-tuberculosis (anti-TB) drugs. The anti-TB agent is activated into an active form, pyrazinoic acid (POA), by Mycobacterium tuberculosis (MTB) pncA gene encoding pyrazinamidase (PZase). The major cause of PZA-resistance has been associated with mutations in the pncA gene. We have detected several novel mutations including V131F, Q141P, R154T, A170P, and V180F (GeneBank Accession No. MH461111) in the pncA gene of PZA-resistant isolates during PZA drug susceptibility testing followed by pncA gene sequencing. Here, we investigated molecular mechanism of PZA-resistance by comparing the results of experimental and molecular dynamics. The mutants (MTs) and wild type (WT) PZase structures in apo and complex with PZA were subjected to molecular dynamic simulations (MD) at the 40 ns. Multiple factors, including root mean square deviations (RMSD), binding pocket, total energy, dynamic cross correlation, and root mean square fluctuations (RMSF) of MTs and WT were compared. The MTs attained a high deviation and fluctuation compared to WT. Binding pocket volumes of the MTs, were found, lower than the WT, and the docking scores were high than WT while shape complementarity scores were lower than that of the WT. Residual motion in MTs are seemed to be dominant in anti-correlated motion. Mutations at locations, V131F, Q141P, R154T, A170P, and V180F, might be involved in the structural changes, possibly affecting the catalytic property of PZase to convert PZA into POA. Our study provides useful information that will enhance the understanding for better management of TB. AbbreviationsDSTdrug susceptibility testingΔelecelectrostatic energyLJLowenstein-Jensen mediumMGITmycobacterium growth indicator tubesMTsmutantsMDmolecular dynamic simulationsMTBMycobacterium tuberculosisNALC-NaOHN-acetyl-l-cysteine-sodium hydroxideNIHNational Institutes of HealthNPTamount of substance (N), pressure (P) temperature (T)NVTmoles (N), volume (V) temperature (T)PZasepyrazinamidaseΔpspolar solvation energyPTRLProvincial Tuberculosis Reference LaboratoryRMSDroot mean square deviationsRMSFroot mean square fluctuationsΔSASAsolvent accessible surface area energyTBtuberculosisGTotaltotal binding free energyΔvdWVan der Waals energyWTwild typeCommunicated by Ramaswamy H. Sarma.

Structural and free energy landscape of novel mutations in ribosomal protein S1 (rpsA) associated with pyrazinamide resistance

Resistance to key first-line drugs is a major hurdle to achieve the global end tuberculosis (TB) targets. A prodrug, pyrazinamide (PZA) is the only drug, effective in latent TB, recommended in drug resistance and susceptible Mycobacterium tuberculosis (MTB) isolates. The prodrug conversion into active form, pyrazinoic acid (POA), required the activity of pncA gene encoded pyrazinamidase (PZase). Although pncA mutations have been commonly associated with PZA resistance but a small number of resistance cases have been associated with mutationss in RpsA protein. Here in this study a total of 69 PZA resistance isolates have been sequenced for pncA mutations. However, samples that were found PZA resistant but pncA wild type (pncAWT), have been sequenced for rpsA and panD genes mutation. We repeated a drug susceptibility testing according to the WHO guidelines on 18 pncAWT MTB isolates. The rpsA and panD genes were sequenced. Out of total 69 PZA resistant isolates, 51 harbored 36 mutations in pncA gene (GeneBank Accession No. MH46111) while, fifteen different mutations including seven novel, were detected in the fourth S1 domain of RpsA known as C-terminal (MtRpsACTD) end. We did not detect any mutations in panD gene. Among the rpsA mutations, we investigated the molecular mechanism of resistance behind mutations, D342N, D343N, A344P, and I351F, present in the MtRpsACTD through molecular dynamic simulations (MD). WT showed a good drug binding affinity as compared to mutants (MTs), D342N, D343N, A344P, and I351F. Binding pocket volume, stability, and fluctuations have been altered whereas the total energy, protein folding, and geometric shape analysis further explored a significant variation between WT and MTs. In conclusion, mutations in MtRpsACTD might be involved to alter the RpsA activity, resulting in drug resistance. Such molecular mechanism behind resistance may provide a better insight into the resistance mechanism to achieve the global TB control targets.

Prediction of the binding mode and resistance profile for a dual-target pyrrolyl diketo acid scaffold against HIV-1 integrase and reverse-transcriptase-associated ribonuclease H

The rapid emergence of drug-resistant variants is one of the most common causes of highly active antiretroviral therapeutic (HAART) failure in patients infected with HIV-1. Compared with the existing HAART, the recently developed pyrrolyl diketo acid scaffold targeting both HIV-1 integrase (IN) and reverse transcriptase-associated ribonuclease H (RNase H) is an efficient approach to counteract the failure of anti-HIV treatment due to drug resistance. However, the binding mode and potential resistance profile of these inhibitors with important mechanistic principles remain poorly understood. To address this issue, an integrated computational method was employed to investigate the binding mode of inhibitor JMC6F with HIV-1 IN and RNase H. By using per-residue binding free energy decomposition analysis, the following residues: Asp64, Thr66, Leu68, Asp116, Tyr143, Gln148 and Glu152 in IN, Asp443, Glu478, Trp536, Lys541 and Asp549 in RNase H were identified as key residues for JMC6F binding. And then computational alanine scanning was carried to further verify the key residues. Moreover, the resistance profile of the currently known major mutations in HIV-1 IN and 2 mutations in RNase H against JMC6F was predicted by in silico mutagenesis studies. The results demonstrated that only three mutations in HIV-1 IN (Y143C, Q148R and N155H) and two mutations in HIV-1 RNase H (Y501R and Y501W) resulted in a reduction of JMC6F potency, thus indicating their potential role in providing resistance to JMC6F. These data provided important insights into the binding mode and resistance profile of the inhibitors with a pyrrolyl diketo acid scaffold in HIV-1 IN and RNase H, which would be helpful for the development of more effective dual HIV-1 IN and RNase H inhibitors.

Low susceptibility of asunaprevir towards R155K and D168A point mutations in HCV NS3/4A protease: A molecular dynamics simulation

Hepatitis C has become an important health problem that requires expensive treatment and leads to liver tumorigenesis. Hepatitis C virus (HCV), which is the main cause of hepatitis C, has a high mutation rate due to the lack of proofreading activity of the RNA polymerase enzyme. The NS3/4A serine protease is an important target for anti-HCV drug discovery and development because of its crucial role in the cleavage of the polypeptides involved in viral replication. In the present study, all-atom molecular dynamics simulation was performed to elucidate the effect of the single point mutations R155K and D168A in the HCV genotype 1 NS3/4A protease on the structural dynamics, molecular interactions and susceptibility of asunaprevir (ASV), a second-generation NS3/4A protease inhibitor. Principal component analysis indicated that these two mutations converted the direction of motion of residues 123, 155 and 168 in the binding pocket to significantly point outwards from ASV, resulting in a loss of the hydrogen bond network of residues R123···R155···D168. The free energy calculations based on different semiempirical QM/MM-GBSA methods revealed that the binding affinity of ASV with the two mutant forms of the NS3/4A protease was significantly decreased in the order of wild-type < R155K < D168A. This work provided useful structural information regarding the atomistic understanding of acquired drug resistance against ASV caused by the R155K and D168A mutations.

A comparative study of the efficiency of HCV NS3/4A protease drugs against different HCV genotypes using in silico approaches

AIMS

To investigate the efficacy of Direct Acting Antivirals (DAAs) in the treatment of different Hepatitis C Virus (HCV) genotypes.

MAIN METHODS

Homology modeling is used to predict the 3D structures of different genotypes while molecular docking is employed to predict genotype - drug interactions (Binding Mode) and binding free energy (Docking Score).

KEY FINDINGS

Simeprevir (TMC435) and to a lesser degree MK6325 are the best drugs among the studied drugs. The predicted affinity of drugs against genotype 1a is always better than other genotypes. P2-P4 macrocyclic drugs show better performance against genotypes 2, 3 and 5. Macrocyclic drugs are better than linear drugs.

SIGNIFICANCE

HCV is one of the major health problems worldwide. Until the discovery of DAAs, HCV treatment faced many failures. DAAs target key functional machines of the virus life cycle and shut it down. NS3/4A protease is an important target and several drugs have been designed to inhibit its functions. There are several NS3/4A protease drugs approved by Food and Drug Administration (FDA). Unfortunately, the virus exhibits resistance against these drugs. This study is significant in elucidating that no one drug is able to treat different genotypes with the same efficiency. Therefore, treatment should be prescribed based on the HCV genotype.

Evolution of efficacious pangenotypic hepatitis C virus therapies

Hepatitis C compromises the quality of life of more than 350 million individuals worldwide. Over the last decade, therapeutic regimens for treating hepatitis C virus (HCV) infections have undergone rapid advancements. Initially, structure-based drug design was used to develop molecules that inhibit viral enzymes. Subsequently, establishment of cell-based replicon systems enabled investigations into various stages of HCV life cycle including its entry, replication, translation, and assembly, as well as role of host proteins. Collectively, these approaches have facilitated identification of important molecules that are deemed essential for HCV life cycle. The expanded set of putative virus and host-encoded targets has brought us one step closer to developing robust strategies for efficacious, pangenotypic, and well-tolerated medicines against HCV. Herein, we provide an overview of the development of various classes of virus and host-directed therapies that are currently in use along with others that are undergoing clinical evaluation.

No impact of resistance-associated substitutions on the efficacy of sofosbuvir, velpatasvir, and voxilaprevir for 12 weeks in HCV DAA-experienced patients

BACKGROUND & AIMS

In phase III studies, the fixed dose combination of sofosbuvir/velpatasvir/voxilaprevir (SOF/VEL/VOX) administered for 12 weeks led to a sustained virologic response at 12 weeks (SVR12) in 96% of NS5A inhibitor-experienced patients, and an SVR12 rate of 98% in DAA-experienced patients who had not previously received an NS5A inhibitor. Herein, we evaluate the relationship between the presence of detectable resistance-associated substitutions (RASs) at baseline and treatment outcome, and whether RASs were selected for in cases of virologic failure.

METHODS

NS3, NS5A, and NS5B deep sequencing analyses were performed at baseline for all patients and at the time of virologic failure. Results are reported using a 15% cut-off.

RESULTS

A total of 82.7% of NS5A inhibitor-experienced patients (205/248) had baseline NS3 and/or NS5A RASs; 79% had baseline NS5A RASs. SVR12 rates were similar in patients with or without NS3 and/or NS5A RASs, and with or without VOX- or VEL-specific RASs. RASs at NS5A position Y93 were present in 37.3% of patients and 95% achieved SVR12. All patients with ≥2 NS5A RASs achieved SVR12. Baseline NS3 and/or NS5A RASs were present in 46.6% (83/178) of non-NS5A inhibitor DAA-experienced patients, all of whom achieved SVR12. All patients with baseline NS5B nucleoside inhibitor RASs, including two patients with S282T, achieved SVR12. Treatment-selected resistance was seen in one of seven patients who relapsed.

CONCLUSIONS

Baseline RASs had no impact on virologic response in DAA-experienced patients following treatment with SOF/VEL/VOX for 12 weeks. Selection of viral resistance with virologic relapse was uncommon.

LAY SUMMARY

In phase III studies, 12 weeks of treatment with the combination of sofosbuvir, velpatasvir and voxilaprevir (SOF/VEL/VOX) cured 97% of patients with hepatitis C virus who failed prior treatment with direct-acting antiviral drugs. Herein, we show that the presence of pretreatment drug resistance did not affect treatment outcome in these patients who had previously received direct-acting antivirals. We also showed that new drug resistance was rare in patients who failed treatment with SOF/VEL/VOX for 12 weeks. This has important implications for the selection of best retreatment strategies for these patients.

Assessing the performance of MM/PBSA and MM/GBSA methods. 7. Entropy effects on the performance of end-point binding free energy calculation approaches

Entropy effects play an important role in drug-target interactions, but the entropic contribution to ligand-binding affinity is often neglected by end-point binding free energy calculation methods, such as MM/GBSA and MM/PBSA, due to the expensive computational cost of normal mode analysis (NMA). Here, we systematically investigated entropy effects on the prediction power of MM/GBSA and MM/PBSA using >1500 protein-ligand systems and six representative AMBER force fields. Two computationally efficient methods, including NMA based on truncated structures and the interaction entropy approach, were used to estimate the entropic contributions to ligand-target binding free energies. In terms of the overall accuracy, we found that, for the minimized structures, in most cases the inclusion of the conformational entropies predicted by truncated NMA (enthalpynmode_min_9Å) compromises the overall accuracy of MM/GBSA and MM/PBSA compared with the enthalpies calculated based on the minimized structures (enthalpymin). However, for the MD trajectories, the binding free energies can be improved by the inclusion of the conformation entropies predicted by either truncated-NMA for a relatively high dielectric constant (εin = 4) or the interaction entropy method for εin = 1-4. In terms of reproducing the absolute binding free energies, the binding free energies estimated by including the truncated-NMA entropies based on the MD trajectories (ΔGnmode_md_9Å) give the lowest average absolute deviations against the experimental data among all the tested strategies for both MM/GBSA and MM/PBSA. Although the inclusion of the truncated NMA based on the MD trajectories (ΔGnmode_md_9Å) for a relatively high dielectric constant gave the overall best result and the lowest average absolute deviations against the experimental data (for the ff03 force field), it needs too much computational time. Alternatively, considering that the interaction entropy method does not incur any additional computational cost and can give comparable (at high dielectric constant, εin = 4) or even better (at low dielectric constant, εin = 1-2) results than the truncated-NMA entropy (ΔGnmode_md_9Å), the interaction entropy approach is recommended to estimate the entropic component for MM/GBSA and MM/PBSA based on MD trajectories, especially for a diverse dataset. Furthermore, we compared the predictions of MM/GBSA with six different AMBER force fields. The results show that the ff03 force field (ff03 for proteins and gaff with AM1-BCC charges for ligands) performs the best, but the predictions given by the tested force fields are comparable, implying that the MM/GBSA predictions are not very sensitive to force fields.

Insight into resistance mechanism of anaplastic lymphoma kinase to alectinib and JH-VIII-157-02 caused by G1202R solvent front mutation

BACKGROUND

Mutated anaplastic lymphoma kinase (ALK) drives the development of advanced non-small cell lung cancer (NSCLC). Most reported small-molecule inhibitors targeting the ALK domain do not display good inhibition of the G1202R solvent front mutation. The solvent front mutation was assumed to hinder drug binding. However, a different fact could be uncovered by the simulations reported in this study through a structural analog of alectinib (JH-VIII-157-02), which demonstrated potent effects against the G1202R mutation.

METHODS

Molecular docking, conventional molecular dynamics (MD) simulations, free energy calculations, and umbrella sampling (US) simulations were carried out to make clear the principles of the binding preferences of alectinib and JH-VIII-157-02 toward ALKWT and the ALK G1202R (ALKG1202R) mutation.

RESULTS

JH-VIII-157-02 has similar binding affinities to both ALKWT and ALKG1202R whereas it has has a much lower binding affinity for alectinib to ALKG1202R. Analysis of individual energy terms indicate the major variation involves the van der Waals and entropy terms. Structural analysis reveals that the conformational change of the ATP-binding glycine-rich loop was primarily responsible for the alectinib resistance, not JH-VIII-157-02. In addition, US simulations prove JH-VIII-157-02 has similar dissociative processes from both ALKWT and ALKG1202R, while alectinib is more easily dissociated from ALKG1202R than from ALKWT, thus indicating lesser residence time.

CONCLUSION

Both the binding affinity and the drug residence time should be emphasized in rational drug design to overcome the G1202R solvent front mutation in ALK resistance.

Sofosbuvir-Daclatasvir-Simeprevir Plus Ribavirin in Direct-Acting Antiviral-Experienced Patients With Hepatitis C

We assessed the broadly used, off-label combination of sofosbuvir, daclatasvir, simeprevir, and ribavirin in direct-acting antiviral-experienced patients, as recommended in current guidelines despite scarce data. After 24 weeks' treatment, sustained virological response 12 weeks after the end of treatment was achieved in 6 patients (60%). Two cirrhotic patients relapsed and 2 discontinued treatment due to serious adverse events.

Discovery of small molecules binding to the normal conformation of prion by combining virtual screening and multiple biological activity evaluation methods

Conformational conversion of the normal cellular prion protein, PrP^C, into the misfolded isoform, PrP^Sc, is considered to be a central event in the development of fatal neurodegenerative diseases. Stabilization of prion protein at the normal cellular form (PrP^C) with small molecules is a rational and efficient strategy for treatment of prion related diseases. However, few compounds have been identified as potent prion inhibitors by binding to the normal conformation of prion. In this work, to rational screening of inhibitors capable of stabilizing cellular form of prion protein, multiple approaches combining docking-based virtual screening, steady-state fluorescence quenching, surface plasmon resonance and thioflavin T fluorescence assay were used to discover new compounds interrupting PrP^C to PrP^Sc conversion. Compound 3253-0207 that can bind to PrP^C with micromolar affinity and inhibit prion fibrillation was identified from small molecule databases. Molecular dynamics simulation indicated that compound 3253-0207 can bind to the hotspot residues in the binding pocket composed by β1, β2 and α2, which are significant structure moieties in conversion from PrP^C to PrP^Sc.

Molecular dynamics simulation, binding free energy calculation and unbinding pathway analysis on selectivity difference between FKBP51 and FKBP52: Insight into the molecular mechanism of isoform selectivity

As co-chaperones of the 90-kDa heat shock protein(HSP90), FK506 binding protein 51 (FKBP51) and FK506 binding protein 52 (FKBP52) modulate the maturation of steroid hormone receptor through their specific FK1 domains (FKBP12-like domain 1). The inhibitors targeting FK1 domains are potential therapies for endocrine-related physiological disorders. However, the structural conservation of the FK1 domains between FKBP51 and FKBP52 make it difficult to obtain satisfactory selectivity in FK506-based drug design. Fortunately, a series of iFit ligands synthesized by Hausch et al exhibited excellent selectivity for FKBP51, providing new opportunity for design selective inhibitors. We performed molecular dynamics simulation, binding free energy calculation and unbinding pathway analysis to reveal selective mechanism for the inhibitor iFit4 binding with FKBP51 and FKBP52. The conformational stability evaluation of the "Phe67-in" and "Phe67-out" states implies that FKBP51 and FKBP52 have different preferences for "Phe67-in" and "Phe67-out" states, which we suggest as the determinant factor for the selectivity for FKBP51. The binding free energy calculations demonstrate that nonpolar interaction is favorable for the inhibitors binding, while the polar interaction and entropy contribution are adverse for the inhibitors binding. According to the results from binding free energy decomposition, the electrostatic difference of residue 85 causes the most significant thermodynamics effects on the binding of iFit4 to FKBP51 and FKBP52. Furthermore, the importance of substructure units on iFit4 were further evaluated by unbinding pathway analysis and residue-residue contact analysis between iFit4 and the proteins. The results will provide new clues for the design of selective inhibitors for FKBP51.

Effect of D168V mutation in NS3/4A HCV protease on susceptibilities of faldaprevir and danoprevir

Hepatitis C virus (HCV) is a serious cause of liver inflammation, cirrhosis and the development of hepatocellular carcinoma. Its NS3/4A serine protease functions to cleave a specific peptide bond, which is an important step in HCV replication. Thus the NS3/4A protease has become one of the main drug-targets in the design and development of anti-HCV agents. Unfortunately, high mutation rates in HCV have been reported due to the lack of RNA proofreading activity resulting in drug resistance. Herein, all-atom molecular dynamics simulations were employed to understand and illustrate the effects of the NS3/4A D168V mutation on faldaprevir (FDV) and danoprevir (DNV) binding efficiency. The D168V mutation was shown to interrupt the hydrogen bonding network of Q80R155D168R123 embedded in the extended S2 and partial S4 subsites of the NS3 protein and as a result the R123 side chain was displaced and moved out from the binding pocket. By means of MM/PBSA and MM/GBSA binding free energy calculations, the FDV and DNV binding affinities were shown to be significantly reduced by ∼10-15 kcal mol^-1 and ∼4-9 kcal mol^-1 relative to the wild-type complexes, respectively, which somewhat agrees with the experimental resistance folds.

Resistance Mechanisms in Hepatitis C Virus: implications for Direct-Acting Antiviral Use

Multiple direct-acting antiviral (DAA)-based regimens are currently approved that provide one or more interferon-free treatment options for hepatitis C virus (HCV) genotypes (G) 1-6. The choice of a DAA regimen, duration of therapy, and use of ribavirin depends on multiple viral and host factors, including HCV genotype, the detection of resistance-associated amino acid (aa) substitutions (RASs), prior treatment experience, and presence of cirrhosis. In regard to viral factors that may guide the treatment choice, the most important is the infecting genotype because a number of DAAs are genotype-designed. The potency and the genetic barrier may also impact the choice of treatment. One important and debated possible virologic factor that may negatively influence the response to DAAs is the presence of baseline RASs. Baseline resistance testing is currently not routinely considered or recommended for initiating HCV treatment, due to the overall high response rates (sustained virological response >90%) obtained. Exceptions are patients infected by HCV G1a when initiating treatment with simeprevir and elbasvir/grazoprevir or in those with cirrhosis prior to daclatasvir/sofosbuvir treatment because of natural polymorphisms demonstrated in sites of resistance. On the basis of these observations, first-line strategies should be optimized to overcome treatment failure due to HCV resistance.

Applications of computer-aided approaches in the development of hepatitis C antiviral agents

INTRODUCTION

Hepatitis C virus (HCV) is a global health problem that causes several chronic life-threatening liver diseases. The numbers of people affected by HCV are rising annually. Since 2011, the FDA has approved several anti-HCV drugs; while many other promising HCV drugs are currently in late clinical trials. Areas covered: This review discusses the applications of different computational approaches in HCV drug design. Expert opinion: Molecular docking and virtual screening approaches have emerged as a low-cost tool to screen large databases and identify potential small-molecule hits against HCV targets. Ligand-based approaches are useful for filtering-out compounds with rich physicochemical properties to inhibit HCV targets. Molecular dynamics (MD) remains a useful tool in optimizing the ligand-protein complexes and understand the ligand binding modes and drug resistance mechanisms in HCV. Despite their varied roles, the application of in-silico approaches in HCV drug design is still in its infancy. A more mature application should aim at modelling the whole HCV replicon in its active form and help to identify new effective druggable sites within the replicon system. With more technological advancements, the roles of computer-aided methods are only going to increase several folds in the development of next-generation HCV drugs.

Computational study on the drug resistance mechanism of HCV NS3 protease to BMS-605339

NS3 protease plays a vital role in the replication of the hepatitis C virus (HCV). BMS-605339 is a novel linear tetra-peptide α-ketoamide inhibitor of NS3 protease and shows specificity for HCV NS3 protease genotype 1a and genotype 1b. Mutation at the key site 168 of the HCV NS3 protease can induce resistance to BMS-605339, which greatly affects the antiviral therapy efficacy to hepatitis C. In the present study, we employed molecular dynamics simulations, free energy calculations, and free energy decomposition to explore the drug resistance mechanism of BMS-605339 due to the three representative mutations D168C/Y/V. The free energy decomposition analysis indicates that the decrease in the binding affinity is mainly attributed to the decrease in both van der Waals and electrostatic interactions. After detailed analysis of our calculated results, we observed that the break of the salt bridge between residues 155 and 168 caused by the mutations D168C/Y/V is the original reason for the decrease in the binding ability between BMS-605339 and the mutant NS3 proteases. The obtained results will reveal the drug resistance mechanism between BMS-605339 and the mutant NS3 proteases, and provide valuable clue for designing novel and more potent drugs to HCV NS3 protease.

Identification of potential quinoxalinone-based aldose reductase inhibitors by 3D-QSAR, molecular docking and molecular dynamics

The 3D-QSAR model of aldose reductase (ARIs) inhibitors is built to gain insights into the key structural factors affecting the inhibitory activity. Based on the model, six new potential ARIs were designed.

Molecular dynamics simulations provide insights into the substrate specificity of FAOX family members

Enzymatic assays based on Fructosyl Amino Acid Oxidases (FAOX) represent a potential, rapid and economical strategy to measure glycated hemoglobin (HbA1c), which is in turn a reliable method to monitor the insurgence and the development of diabetes mellitus.

Assessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set

By using different evaluation strategies, we systemically evaluated the performance of Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodologies based on more than 1800 protein-ligand crystal structures in the PDBbind database. The results can be summarized as follows: (1) for the one-protein-family/one-binding-ligand case which represents the unbiased protein-ligand complex sampling, both MM/GBSA and MM/PBSA methodologies achieve approximately equal accuracies at the interior dielectric constant of 4 (with rp = 0.408 ± 0.006 of MM/GBSA and rp = 0.388 ± 0.006 of MM/PBSA based on the minimized structures); while for the total dataset (1864 crystal structures), the overall best Pearson correlation coefficient (rp = 0.579 ± 0.002) based on MM/GBSA is better than that of MM/PBSA (rp = 0.491 ± 0.003), indicating that biased sampling may significantly affect the accuracy of the predicted result (some protein families contain too many instances and can bias the overall predicted accuracy). Therefore, family based classification is needed to evaluate the two methodologies; (2) the prediction accuracies of MM/GBSA and MM/PBSA for different protein families are quite different with rp ranging from 0 to 0.9, whereas the correlation and ranking scores (an averaged rp/rs over a list of protein folds and also representing the unbiased sampling) given by MM/PBSA (rp-score = 0.506 ± 0.050 and rs-score = 0.481 ± 0.052) are comparable to those given by MM/GBSA (rp-score = 0.516 ± 0.047 and rs-score = 0.463 ± 0.047) at the fold family level; (3) for the overall prediction accuracies, molecular dynamics (MD) simulation may not be quite necessary for MM/GBSA (rp-minimized = 0.579 ± 0.002 and rp-1ns = 0.564 ± 0.002), but is needed for MM/PBSA (rp-minimized = 0.412 ± 0.003 and rp-1ns = 0.491 ± 0.003). However, for the individual systems, whether to use MD simulation is depended. (4) both MM/GBSA and MM/PBSA may be unable to give successful predictions for the ligands with high formal charges, with the Pearson correlation coefficient ranging from 0.621 ± 0.003 (neutral ligands) to 0.125 ± 0.142 (ligands with a formal charge of 5). Therefore, it can be summarized that, although MM/GBSA and MM/PBSA perform similarly in the unbiased dataset, for the currently available crystal structures in the PDBbind database, compared with MM/GBSA, which may be used in multi-target comparisons, MM/PBSA is more sensitive to the investigated systems, and may be more suitable for individual-target-level binding free energy ranking. This study may provide useful guidance for the post-processing of docking based studies.

The molecular mechanism of bisphenol A (BPA) as an endocrine disruptor by interacting with nuclear receptors: insights from molecular dynamics (MD) simulations

Bisphenol A (BPA) can interact with nuclear receptors and affect the normal function of nuclear receptors in very low doses, which causes BPA to be one of the most controversial endocrine disruptors. However, the detailed molecular mechanism about how BPA interferes the normal function of nuclear receptors is still undiscovered. Herein, molecular dynamics simulations were performed to explore the detailed interaction mechanism between BPA with three typical nuclear receptors, including hERα, hERRγ and hPPARγ. The simulation results and calculated binding free energies indicate that BPA can bind to these three nuclear receptors. The binding affinities of BPA were slightly lower than that of E2 to these three receptors. The simulation results proved that the binding process was mainly driven by direct hydrogen bond and hydrophobic interactions. In addition, structural analysis suggested that BPA could interact with these nuclear receptors by mimicking the action of natural hormone and keeping the nuclear receptors in active conformations. The present work provided the structural evidence to recognize BPA as an endocrine disruptor and would be important guidance for seeking safer substitutions of BPA.

Revealing the favorable dissociation pathway of type II kinase inhibitors via enhanced sampling simulations and two-end-state calculations

How does a type II inhibitor bind to/unbind from a kinase target is still a confusing question because the small molecule occupies both the ATP pocket and the allosteric pocket of the kinase binding site. Here, by using enhanced sampling simulations (umbrella sampling, US) and two-end-state free energy calculations (MM/GSBA), we systemically studied the dissociation processes of two distinct small molecules escaping from the binding pocket of p38 MAP kinase through the allosteric channel and the ATP channel. The results show that the unbinding pathways along the allosteric channel have much lower PMF depths than those along the ATP channel, suggesting that the allosteric channel is more favorable for the dissociations of the two inhibitors and thereby supporting the general understanding that the largest channel of a target is usually the entry/exit pathway for the binding/dissociation of small molecules. Interestingly, the MM/GBSA approach yielded similar PMF profiles compared with those based on US, a much time consuming approach, indicating that for a general study, such as detecting the important transition state of a ligand binding/unbinding process, MM/GBSA may be a feasible choice.

Exploring resistance mechanisms of HCV NS3/4A protease mutations to MK5172: insight from molecular dynamics simulations and free energy calculations

Mutations at a number of key positions (Ala156, Asp168 and Arg155) of the HCV NS3/4A protease can induce medium to high resistance to MK5172.

Importance of protein flexibility in ranking inhibitor affinities: modeling the binding mechanisms of piperidine carboxamides as Type I1/2 ALK inhibitors

Anaplastic lymphoma kinase (ALK) has gained increased attention as an attractive therapeutic target for the treatment of various cancers, especially non-small-cell lung cancer (NSCLC).

Exploring the prominent performance of CX-4945 derivatives as protein kinase CK2 inhibitors by a combined computational study

Protein kinase CK2, also known as casein kinase II, is related to various cellular events and is a potential target for numerous cancers. In this study, we attempted to gain more insight into the inhibition process of CK2 by a series of CX-4945 derivatives through an integrated computational study that combines molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations. Based on the binding poses predicted by molecular docking, the MD simulations were performed to explore the dynamic binding processes for ten selected inhibitors. Then, both Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) techniques were employed to predict the binding affinities of the studied systems. The predicted binding energies of the selected inhibitors correlate well with their experimental activities (r(2) = 0.78). The van der Waals term is the most favorable component for the total energies. The free energy decomposition on a per residue basis reveals that the residue K68 is essential for the electrostatic interactions between CK2 and the studied inhibitors and numerous residues, including L45, V53, V66, F113, M163 and I174, play critical roles in forming van der Waals interactions with the inhibitors. Finally, a number of new derivatives were designed and the binding affinity and the predicted binding free energies of each designed molecule were obtained on the basis of molecular docking and MM/PBSA. It is expected that our research will benefit the future rational design of novel and potent inhibitors of CK2.

Computational study on the drug resistance mechanism of HCV NS5B RNA-dependent RNA polymerase mutants V494I, V494A, M426A, and M423T to Filibuvir

Filibuvir, a potent non-nucleoside inhibitor of the hepatitis C virus (HCV) NS5B RNA-dependent RNA polymerase (RdRp), has shown great promise in phase IIb clinical trial. However, drug resistant mutations towards Filibuvir have been identified. In the present study, the drug resistance mechanism of wild-type (WT) and mutant NS5B polymerases (including V494I, V494A, M426A, and M423T) toward Filibuvir was investigated by molecular modeling methods. The predicted binding free energy of these five complexes is highly consistent with the experimental EC50 values of Filibuvir to the wild-type and mutant NS5B RdRps, V494I<WT<V494A<M426A<M423T. Analysis of the individual energy terms indicates that the loss of binding affinity is mainly attributed to the decrease in the van der Waals interaction contribution. Through detailed analysis of the interaction between FBV and RdRp(V494I), RdRp(WT), RdRp(V494A), RdRp(M426A), and RdRp(M423T), several conclusions are made. Firstly, the smaller size of residue 494 side chain results in the smaller binding affinity between FBV and RdRp. Secondly, the poor inhibition capacity of Filibuvir toward RdRp(M426A) is mainly due to the decrease in the van der Walls interaction between Filibuvir and residue Leu-497(M426A) caused by the spatial structure change of Ala-426(M426A). Thirdly, the decrease in the binding affinity in mutation M423T is attributed to the smaller binding cave and the cyclopentyl group of Filibuvir exposing outside the cave. Our computational results will provide valuable information for developing more potent and selective inhibitors toward HCV NS5B polymerase.

Computational studies on the binding mechanism between triazolone inhibitors and Chk1 by molecular docking and molecular dynamics

Chk1, a serine/threonine protein kinase that participates in transducing DNA damage signals, is an attractive target due to its involvement in tumor initiation and progression. As a novel Chk1 inhibitor, the triazolone's bioactivity mechanism is not clear. In this study, we carried out an integrated computational study that combines molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations to identify the key factors necessary for the bioactivities. With the aim of discerning the structural features that affect the inhibitory activity of triazolones, MK-8776, a Chk1 inhibitor that reached the clinical stage, was also used as a reference for simulations. A comparative analysis of the triazolone inhibitors at the molecular level offers valuable insight into the structural and energetic properties. A general feature is that all the studied inhibitors bind in the pocket characterized by residues Leu14, Val22, Ala35, Glu84, Tyr85, Cys86, and Leu136 of Chk1. Moreover, introducing hydrophobic groups into triazolone inhibitors is favorable for binding to Chk1, which is corroborated by residue Leu136 with a relatively large difference in the contribution between MK-8776 and five triazolones to the total binding free energies. A hydrogen bond between the polar hydrogen atoms at R1 and Cys86 can facilitate proper placement of the inhibitor in the binding pocket of Chk1 that favors binding. However, the introduction of hydrophilic groups into the R2 position diminishes binding affinity. The information provided by this research is of benefit for further rational design of novel promising inhibitors of Chk1.

Understanding the effects on constitutive activation and drug binding of a D130N mutation in the β2 adrenergic receptor via molecular dynamics simulation

G-protein-coupled receptors (GPCRs) are currently one of the largest families of drug targets. The constitutive activation induced by mutation of key GPCR residues is associated closely with various diseases. However, the structural basis underlying such activation and its role in drug binding has remained unclear. Herein, we used all-atom molecular dynamics simulations and free energy calculations to study the effects of a D130N mutation on the structure of β2 adrenergic receptor (β2AR) and its binding of the agonist salbutamol. The results indicate that the mutation caused significant changes in some key helices. In particular, the mutation leads to the departure of transmembrane 3 (TM3) from transmembrane 6 (TM6) and marked changes in the NPxxY region as well as the complete disruption of a key ionic lock, all of which contribute to the observed constitutive activation. In addition, the D130N mutation weakens some important H-bonds, leading to structural changes in these regions. Binding free energy calculations indicate that van der Waals and electrostatic interactions are the main driving forces in binding salbutamol; however, binding strength in the mutant β2AR is significantly enhanced mainly through modifying electrostatic interactions. Further analysis revealed that the increase in binding energy upon mutation stems mainly from the H-bonds formed between the hydroxyl group of salbutamol and the serine residues of TM5. This observation suggests that modifications of the H-bond groups of this drug could significantly influence drug efficacy in the treatment of diseases associated with this mutation.