Drug Resistance Mutation L76V Alters Nonpolar Interactions at the Flap-Core Interface of HIV-1 Protease

Prediction of Binding Pose and Affinity of Nelfinavir, a SARS-CoV-2 Main Protease Repositioned Drug, by Combining Docking, Molecular Dynamics, and Fragment Molecular Orbital Calculations

A novel in silico drug design procedure is described targeting the Main protease (Mpro) of the SARS-CoV-2 virus. The procedure combines molecular docking, molecular dynamics (MD), and fragment molecular orbital (FMO) calculations. The binding structure and properties of Mpro were predicted for Nelfinavir (NFV), which had been identified as a candidate compound through drug repositioning, targeting Mpro. Several poses of the Mpro and NFV complexes were generated by docking, from which four docking poses were selected by scoring with FMO energy. Then, each pose was subjected to MD simulation, 100 snapshot structures were sampled from each of the generated MD trajectories, and the structures were evaluated by FMO calculations to rank the pose based on binding energy. Several residues were found to be important in ligand recognition, including Glu47, Asp48, Glu166, Asp187, and Gln189, all of which interacted strongly with NFV. Asn142 is presumably regarded to form hydrogen bonds or CH/π interaction with NFV; however, in the present calculation, their interactions were transient. Moreover, the tert-butyl group of NFV had no interaction with Mpro. Identifying such strong and weak interactions provides candidates for maintaining and substituting ligand functional groups and important suggestions for drug discovery using drug repositioning. Besides the interaction between NFV and the amino acid residues of Mpro, the desolvation effect of the binding pocket also affected the ranking order. A similar procedure of drug design was applied to Lopinavir, and the calculated interaction energy and experimental inhibitory activity value trends were consistent. Our approach provides a new guideline for structure-based drug design starting from a candidate compound whose complex crystal structure has not been obtained.

Computer-Aided Prediction of the Interactions of Viral Proteases with Antiviral Drugs: Antiviral Potential of Broad-Spectrum Drugs

Human society is facing the threat of various viruses. Proteases are promising targets for the treatment of viral infections. In this study, we collected and profiled 170 protease sequences from 125 viruses that infect humans. Approximately 73 of them are viral 3-chymotrypsin-like proteases (3CLpro), and 11 are pepsin-like aspartic proteases (PAPs). Their sequences, structures, and substrate characteristics were carefully analyzed to identify their conserved nature for proposing a pan-3CLpro or pan-PAPs inhibitor design strategy. To achieve this, we used computational prediction and modeling methods to predict the binding complex structures for those 73 3CLpro with 4 protease inhibitors of SARS-CoV-2 and 11 protease inhibitors of HCV. Similarly, the complex structures for the 11 viral PAPs with 9 protease inhibitors of HIV were also obtained. The binding affinities between these compounds and proteins were also evaluated to assess their pan-protease inhibition via MM-GBSA. Based on the drugs targeting viral 3CLpro and PAPs, repositioning of the active compounds identified several potential uses for these drug molecules. As a result, Compounds 1-2, modified based on the structures of Ray1216 and Asunaprevir, indicate potential inhibition of DENV protease according to our computational simulation results. These studies offer ideas and insights for future research in the design of broad-spectrum antiviral drugs.

Comprehending the Structure, Dynamics, and Mechanism of Action of Drug-Resistant HIV Protease

Since the emergence of the Human Immunodeficiency Virus (HIV) in the 1980s, strategies to combat HIV-AIDS are continuously evolving. Among the many tested targets to tackle this virus, its protease enzyme (PR) was proven to be an attractive option that brought about numerous research publications and ten FDA-approved drugs to inhibit the PR activity. However, the drug-induced mutations in the enzyme made these small molecule inhibitors ineffective with prolonged usage. The research on HIV PR, therefore, remains a thrust area even today. Through this review, we reiterate the importance of understanding the various structural and functional components of HIV PR in redesigning the structure-based small molecule inhibitors. We also discuss at length the currently available FDA-approved drugs and how these drug molecules induced mutations in the enzyme structure. We then recapitulate the reported mechanisms on how these drug-resistant variants remain sufficiently active to cleave the natural substrates. We end with the future scope covering the recently proposed strategies that show promise to deal with the mutations.

Understanding the co-evolutionary molecular mechanisms of resistance in the HIV-1 Gag and protease

Due to high human immunodeficiency virus type 1 (HIV-1) subtype C infections coupled with increasing antiretroviral treatment failure, the elucidation of complex drug resistance mutational patterns arising through protein co-evolution is required. Despite the inclusion of potent protease inhibitors Lopinavir (LPV) and Darunavir (DRV) in second- and third-line therapies, many patients still fail treatment due to the accumulation of mutations in protease (PR) and recently, Gag. To understand the co-evolutionary molecular mechanisms of resistance in the HIV-1 PR and Gag, we performed 100 ns molecular dynamic simulations on multidrug resistant PR's when bound to LPV, DRV or a mutated A431V NC|p1 Gag cleavage site (CS). Here we showed that distinct changes in PR's active site, flap and elbow regions due to several PR resistance mutations (L10F, M46I, I54V, L76V, V82A) were found to alter LPV and DRV drug binding. However, binding was significantly exacerbated when the mutant PRs were bound to the NC|p1 Gag CS. Although A431V was shown to coordinate several residues in PR, the L76V PR mutation was found to have a significant role in substrate recognition. Consequently, a greater binding affinity was observed when the mutated substrate was bound to an L76V-inclusive PR mutant (G_bind: -62.46 ± 5.75 kcal/mol) than without (Gbind: -50.34 ± 6.28 kcal/mol). These data showed that the co-selection of resistance mutations in the enzyme and substrate can simultaneously constrict regions in PR's active site whilst flexing the flaps to allow flexible movement of the substrate and multiple, complex mechanisms of resistance to occur. Communicated by Ramaswamy H. Sarma.

HIV-1 protease with 10 lopinavir and darunavir resistance mutations exhibits altered inhibition, structural rearrangements and extreme dynamics

Antiretroviral drug resistance is a therapeutic obstacle for people with HIV. HIV protease inhibitors darunavir and lopinavir are recommended for resistant infections. We characterized a protease mutant (PR10x) derived from a highly resistant clinical isolate including 10 mutations associated with resistance to lopinavir and darunavir. Compared to the wild-type protease, PR10x exhibits ∼3-fold decrease in catalytic efficiency and Ki values of 2-3 orders of magnitude worse for darunavir, lopinavir, and potent investigational inhibitor GRL-519. Crystal structures of the mutant were solved in a ligand-free form and in complex with GRL-519. The structures show altered interactions in the active site, flap-core interface, hydrophobic core, hinge region, and 80s loop compared to the corresponding wild-type protease structures. The ligand-free crystal structure exhibits a highly curled flap conformation which may amplify drug resistance. Molecular dynamics simulations performed for 1 μs on ligand-free dimers showed extremely large fluctuations in the flaps for PR10x compared to equivalent simulations on PR with a single L76V mutation or wild-type protease. This analysis offers insight about the synergistic effects of mutations in highly resistant variants.

Exploring the Binding Mechanism of PF-07321332 SARS-CoV-2 Protease Inhibitor through Molecular Dynamics and Binding Free Energy Simulations

The novel coronavirus disease, caused by severe acute respiratory coronavirus 2 (SARS-CoV-2), rapidly spreading around the world, poses a major threat to the global public health. Herein, we demonstrated the binding mechanism of PF-07321332, α-ketoamide, lopinavir, and ritonavir to the coronavirus 3-chymotrypsin-like-protease (3CLpro) by means of docking and molecular dynamic (MD) simulations. The analysis of MD trajectories of 3CLpro with PF-07321332, α-ketoamide, lopinavir, and ritonavir revealed that 3CLpro-PF-07321332 and 3CLpro-α-ketoamide complexes remained stable compared with 3CLpro-ritonavir and 3CLpro-lopinavir. Investigating the dynamic behavior of ligand-protein interaction, ligands PF-07321332 and α-ketoamide showed stronger bonding via making interactions with catalytic dyad residues His41-Cys145 of 3CLpro. Lopinavir and ritonavir were unable to disrupt the catalytic dyad, as illustrated by increased bond length during the MD simulation. To decipher the ligand binding mode and affinity, ligand interactions with SARS-CoV-2 proteases and binding energy were calculated. The binding energy of the bespoke antiviral PF-07321332 clinical candidate was two times higher than that of α-ketoamide and three times than that of lopinavir and ritonavir. Our study elucidated in detail the binding mechanism of the potent PF-07321332 to 3CLpro along with the low potency of lopinavir and ritonavir due to weak binding affinity demonstrated by the binding energy data. This study will be helpful for the development and optimization of more specific compounds to combat coronavirus disease.

Prediction of HIV drug resistance based on the 3D protein structure: Proposal of molecular field mapping

A method for predicting HIV drug resistance by using genotypes would greatly assist in selecting appropriate combinations of antiviral drugs. Models reported previously have had two major problems: lack of information on the 3D protein structure and processing of incomplete sequencing data in the modeling procedure. We propose obtaining the 3D structural information of viral proteins by using homology modeling and molecular field mapping, instead of just their primary amino acid sequences. The molecular field potential parameters reflect the physicochemical characteristics associated with the 3D structure of the proteins. We also introduce the Bayesian conditional mutual information theory to estimate the probabilities of occurrence of all possible protein candidates from an incomplete sequencing sample. This approach allows for the effective use of uncertain information for the modeling process. We applied these data analysis techniques to the HIV-1 protease inhibitor dataset and developed drug resistance prediction models with reasonable performance.

Acquired HIV-1 Protease Conformational Flexibility Associated with Lopinavir Failure May Shape the Outcome of Darunavir Therapy after Antiretroviral Therapy Switch

Understanding the underlying molecular interaction during a therapy switch from lopinavir (LPV) to darunavir (DRV) is essential to achieve long-term virological suppression. We investigated the kinetic and structural characteristics of multidrug-resistant South African HIV-1 subtype C protease (HIV-1 PR) during therapy switch from LPV to DRV using enzyme activity and inhibition assay, fluorescence spectroscopy, and molecular dynamic simulation. The HIV-1 protease variants were from clinical isolates with a combination of drug resistance mutations; MUT-1 (M46I, I54V, V82A, and L10F), MUT-2 (M46I, I54V, L76V, V82A, L10F, and L33F), and MUT-3 (M46I, I54V, L76V, V82A, L90M, and F53L). Enzyme kinetics analysis shows an association between increased relative resistance to LPV and DRV with the progressive decrease in the mutant HIV-1 PR variants' catalytic efficiency. A direct relationship between high-level resistance to LPV and intermediate resistance to DRV with intrinsic changes in the three-dimensional structure of the mutant HIV-1 PR as a function of the multidrug-resistance mutation was observed. In silico analysis attributed these structural adjustments to the multidrug-resistance mutations affecting the LPV and DRV binding landscape. Though DRV showed superiority to LPV, as a lower concentration was needed to inhibit the HIV-1 PR variants, the inherent structural changes resulting from mutations selected during LPV therapy may dynamically shape the DRV treatment outcome after the therapy switch.

Darunavir-Resistant HIV-1 Protease Constructs Uphold a Conformational Selection Hypothesis for Drug Resistance

Multidrug resistance continues to be a barrier to the effectiveness of highly active antiretroviral therapy in the treatment of human immunodeficiency virus 1 (HIV-1) infection. Darunavir (DRV) is a highly potent protease inhibitor (PI) that is oftentimes effective when drug resistance has emerged against first-generation inhibitors. Resistance to darunavir does evolve and requires 10–20 amino acid substitutions. The conformational landscapes of six highly characterized HIV-1 protease (PR) constructs that harbor up to 19 DRV-associated mutations were characterized by distance measurements with pulsed electron double resonance (PELDOR) paramagnetic resonance spectroscopy, namely double electron–electron resonance (DEER). The results show that the accumulated substitutions alter the conformational landscape compared to PI-naïve protease where the semi-open conformation is destabilized as the dominant population with open-like states becoming prevalent in many cases. A linear correlation is found between values of the DRV inhibition parameter K_i and the open-like to closed-state population ratio determined from DEER. The nearly 50% decrease in occupancy of the semi-open conformation is associated with reduced enzymatic activity, characterized previously in the literature.

Highly drug-resistant HIV-1 protease reveals decreased intra-subunit interactions due to clusters of mutations

Drug-resistance is a serious problem for treatment of the HIV/AIDS pandemic. Potent clinical inhibitors of HIV-1 protease show several orders of magnitude worse inhibition of highly drug-resistant variants. Hence, the structure and enzyme activities were analyzed for HIV protease mutant HIV-1 protease (EC 3.4.23.16) (PR) with 22 mutations (PRS5B) from a clinical isolate that was selected by machine learning to represent high-level drug-resistance. PRS5B has 22 mutations including only one (I84V) in the inhibitor binding site; however, clinical inhibitors had poor inhibition of PRS5B activity with kinetic inhibition value (K_i ) values of 4-1000 nm or 18- to 8000-fold worse than for wild-type PR. High-resolution crystal structures of PRS5B complexes with the best inhibitors, amprenavir (APV) and darunavir (DRV) (K_i ~ 4 nm), revealed only minor changes in protease-inhibitor interactions. Instead, two distinct clusters of mutations in distal regions induce coordinated conformational changes that decrease favorable internal interactions across the entire protein subunit. The largest structural rearrangements are described and compared to other characterized resistant mutants. In the protease hinge region, the N83D mutation eliminates a hydrogen bond connecting the hinge and core of the protease and increases disorder compared to highly resistant mutants PR with 17 mutations and PR with 20 mutations with similar hinge mutations. In a distal β-sheet, mutations G73T and A71V coordinate with accessory mutations to bring about shifts that propagate throughout the subunit. Molecular dynamics simulations of ligand-free dimers show differences consistent with loss of interactions in mutant compared to wild-type PR. Clusters of mutations exhibit both coordinated and antagonistic effects, suggesting PRS5B may represent an intermediate stage in the evolution of more highly resistant variants. DATABASES: Structural data are available in Protein Data Bank under the accession codes 6P9A and 6P9B for PRS5B/DRV and PRS5B/APV, respectively.

Gag-protease coevolution shapes the outcome of lopinavir-inclusive treatment regimens in chronically infected HIV-1 subtype C patients

MOTIVATION

Commonly, protease inhibitor failure is characterized by the development of multiple protease resistance mutations (PRMs). While the impact of PRMs on therapy failure are understood, the introduction of Gag mutations with protease remains largely unclear.

RESULTS

Here, we utilized phylogenetic analyses and Bayesian network learning as tools to understand Gag-protease coevolution and elucidate the pathways leading to Lopinavir failure in HIV-1 subtype C infected patients. Our analyses indicate that while PRMs coevolve in response to drug selection pressure within protease, the Gag mutations added to the existing network while specifically interacting with known Lopinavir failure PRMs. Additionally, the selection of mutations at specific positions in Gag-protease suggests that these coevolving mutational changes occurs to maintain structural integrity during Gag cleavage.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Non-active site mutants of HIV-1 protease influence resistance and sensitisation towards protease inhibitors

Background

HIV-1 can develop resistance to antiretroviral drugs, mainly through mutations within the target regions of the drugs. In HIV-1 protease, a majority of resistance-associated mutations that develop in response to therapy with protease inhibitors are found in the protease’s active site that serves also as a binding pocket for the protease inhibitors, thus directly impacting the protease-inhibitor interactions. Some resistance-associated mutations, however, are found in more distant regions, and the exact mechanisms how these mutations affect protease-inhibitor interactions are unclear. Furthermore, some of these mutations, e.g. N88S and L76V, do not only induce resistance to the currently administered drugs, but contrarily induce sensitivity towards other drugs. In this study, mutations N88S and L76V, along with three other resistance-associated mutations, M46I, I50L, and I84V, are analysed by means of molecular dynamics simulations to investigate their role in complexes of the protease with different inhibitors and in different background sequence contexts.

Results

Using these simulations for alchemical calculations to estimate the effects of mutations M46I, I50L, I84V, N88S, and L76V on binding free energies shows they are in general in line with the mutations’ effect on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$IC_{50}$$\end{document}IC50 values. For the primary mutation L76V, however, the presence of a background mutation M46I in our analysis influences whether the unfavourable effect of L76V on inhibitor binding is sufficient to outweigh the accompanying reduction in catalytic activity of the protease. Finally, we show that L76V and N88S changes the hydrogen bond stability of these residues with residues D30/K45 and D30/T31/T74, respectively.

Conclusions

We demonstrate that estimating the effect of both binding pocket and distant mutations on inhibitor binding free energy using alchemical calculations can reproduce their effect on the experimentally measured \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$IC_{50}$$\end{document}IC50 values. We show that distant site mutations L76V and N88S affect the hydrogen bond network in the protease’s active site, which offers an explanation for the indirect effect of these mutations on inhibitor binding. This work thus provides valuable insights on interplay between primary and background mutations and mechanisms how they affect inhibitor binding.

FDA-Approved Drugs Efavirenz, Tipranavir, and Dasabuvir Inhibit Replication of Multiple Flaviviruses in Vero Cells

Vector-borne flaviviruses (VBFs) affect human health worldwide, but no approved drugs are available specifically to treat VBF-associated infections. Here, we performed in silico screening of a library of U.S. Food and Drug Administration-approved antiviral drugs for their interaction with Zika virus proteins. Twelve hit drugs were identified by the docking experiments and tested in cell-based antiviral assay systems. Efavirenz, tipranavir, and dasabuvir at micromolar concentrations were identified to inhibit all VBFs tested; i.e., two representatives of mosquito-borne flaviviruses (Zika and West Nile viruses) and one representative of flaviviruses transmitted by ticks (tick-borne encephalitis virus). The results warrant further research into these drugs, either individually or in combination, as possible pan-flavivirus inhibitors.

Structural studies of antiviral inhibitor with HIV-1 protease bearing drug resistant substitutions of V32I, I47V and V82I

HIV-1 protease inhibitors are effective in HIV/AIDS therapy, although drug resistance is a severe problem. This study examines the effects of four investigational inhibitors against HIV-1 protease with drug resistant mutations of V32I, I47V and V82I (PR_Tri) that model the inhibitor-binding site of HIV-2 protease. These inhibitors contain diverse chemical modifications on the darunavir scaffold and form new interactions with wild type protease, however, the measured inhibition constants for PR_Tri mutant range from 17 to 40 nM or significantly worse than picomolar values reported for wild type enzyme. The X-ray crystal structure of PR_Tri mutant in complex with inhibitor 1 at 1.5 Å resolution shows minor changes in interactions with inhibitor compared with the corresponding wild type PR complex. Instead, the basic amine at P2 of inhibitor together with mutation V82I induces two alternate conformations for the side chain of Arg8 with new interactions with inhibitor and Leu10. Hence, inhibition is influenced by small coordinated changes in hydrophobic interactions.