Evaluating the substrate-envelope hypothesis: structural analysis of novel HIV-1 protease inhibitors designed to be robust against drug resistance

Machine learning-guided design of potent darunavir analogs targeting HIV-1 proteases: A computational approach for antiretroviral drug discovery

In the pursuit of novel antiretroviral therapies for human immunodeficiency virus type-1 (HIV-1) proteases (PRs), recent improvements in drug discovery have embraced machine learning (ML) techniques to guide the design process. This study employs ensemble learning models to identify crucial substructures as significant features for drug development. Using molecular docking techniques, a collection of 160 darunavir (DRV) analogs was designed based on these key substructures and subsequently screened using molecular docking techniques. Chemical structures with high fitness scores were selected, combined, and one-dimensional (1D) screening based on beyond Lipinski's rule of five (bRo5) and ADME (absorption, distribution, metabolism, and excretion) prediction implemented in the Combined Analog generator Tool (CAT) program. A total of 473 screened analogs were subjected to docking analysis through convolutional neural networks scoring function against both the wild-type (WT) and 12 major mutated PRs. DRV analogs with negative changes in binding free energy (ΔΔ G bind ) compared to DRV could be categorized into four attractive groups based on their interactions with the majority of vital PRs. The analysis of interaction profiles revealed that potent designed analogs, targeting both WT and mutant PRs, exhibited interactions with common key amino acid residues. This observation further confirms that the ML model-guided approach effectively identified the substructures that play a crucial role in potent analogs. It is expected to function as a powerful computational tool, offering valuable guidance in the identification of chemical substructures for synthesis and subsequent experimental testing.

Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors

We report the results of the COVID Moonshot, a fully open-science, crowdsourced, and structure-enabled drug discovery campaign targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease. We discovered a noncovalent, nonpeptidic inhibitor scaffold with lead-like properties that is differentiated from current main protease inhibitors. Our approach leveraged crowdsourcing, machine learning, exascale molecular simulations, and high-throughput structural biology and chemistry. We generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. All compound designs (>18,000 designs), crystallographic data (>490 ligand-bound x-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2400 compounds) for this campaign were shared rapidly and openly, creating a rich, open, and intellectual property-free knowledge base for future anticoronavirus drug discovery.

Systematic Analyses of the Resistance Potential of Drugs Targeting SARS-CoV-2 Main Protease

Drugs that target the main protease (Mpro) of SARS-CoV-2 are effective therapeutics that have entered clinical use. Wide-scale use of these drugs will apply selection pressure for the evolution of resistance mutations. To understand resistance potential in Mpro, we performed comprehensive surveys of amino acid changes that can cause resistance to nirmatrelvir (Pfizer), and ensitrelvir (Xocova) in a yeast screen. We identified 142 resistance mutations for nirmatrelvir and 177 for ensitrelvir, many of which have not been previously reported. Ninety-nine mutations caused apparent resistance to both inhibitors, suggesting likelihood for the evolution of cross-resistance. The mutation with the strongest drug resistance score against nirmatrelvir in our study (E166V) was the most impactful resistance mutation recently reported in multiple viral passaging studies. Many mutations that exhibited inhibitor-specific resistance were consistent with the distinct interactions of each inhibitor in the substrate binding site. In addition, mutants with strong drug resistance scores tended to have reduced function. Our results indicate that strong pressure from nirmatrelvir or ensitrelvir will select for multiple distinct-resistant lineages that will include both primary resistance mutations that weaken interactions with drug while decreasing enzyme function and compensatory mutations that increase enzyme activity. The comprehensive identification of resistance mutations enables the design of inhibitors with reduced potential of developing resistance and aids in the surveillance of drug resistance in circulating viral populations.

HIV-1 protease inhibitors with a P1 phosphonate modification maintain potency against drug-resistant variants by increased interactions with flap residues

Protease inhibitors are the most potent antivirals against HIV-1, but they still lose efficacy against resistant variants. Improving the resistance profile is key to developing more robust inhibitors, which may be promising candidates for simplified next-generation antiretroviral therapies. In this study, we explored analogs of darunavir with a P1 phosphonate modification in combination with increasing size of the P1' hydrophobic group and various P2' moieties to improve potency against resistant variants. The phosphonate moiety substantially improved potency against highly mutated and resistant HIV-1 protease variants, but only when combined with more hydrophobic moieties at the P1' and P2' positions. Phosphonate analogs with a larger hydrophobic P1' moiety maintained excellent antiviral potency against a panel of highly resistant HIV-1 variants, with significantly improved resistance profiles. The cocrystal structures indicate that the phosphonate moiety makes extensive hydrophobic interactions with the protease, especially with the flap residues. Many residues involved in these protease-inhibitor interactions are conserved, enabling the inhibitors to maintain potency against highly resistant variants. These results highlight the need to balance inhibitor physicochemical properties by simultaneous modification of chemical groups to further improve resistance profiles.

Design, synthesis, and biological evaluation of novel HIV-1 protease inhibitors containing pyrrolidine-derived P2 ligands to combat drug-resistant variant

The design, synthesis, and biological evaluation of a novel series of HIV-1 protease inhibitors containing pyrrolidines with diverse linkers as the P2 ligands and various aromatic derivatives as the P2' ligands were described. A number of inhibitors demonstrated potent efficacy in both enzyme and cellular assays, as well as relatively low cytotoxicity. In particular, inhibitor 34b with a (R)-pyrrolidine-3-carboxamide P2 ligand and a 4-hydroxyphenyl P2' ligand displayed exceptional enzyme inhibitory activity with an IC₅₀ value of 0.32 nM. Furthermore, 34b also exhibited robust antiviral activity against both wild-type HIV-1 and drug-resistant variant with low micromolar EC₅₀ values. In addition, the molecular modelling studies revealed the extensive interactions between inhibitor 34b and the backbone residues of both wild-type and drug-resistant HIV-1 protease. These results suggested the feasibility of utilizing pyrrolidine derivatives as the P2 ligands and provided valuable information for further design and optimization of highly potent HIV-1 protease inhibitors.

Viral proteases as therapeutic targets

Some medically important viruses-including retroviruses, flaviviruses, coronaviruses, and herpesviruses-code for a protease, which is indispensable for viral maturation and pathogenesis. Viral protease inhibitors have become an important class of antiviral drugs. Development of the first-in-class viral protease inhibitor saquinavir, which targets HIV protease, started a new era in the treatment of chronic viral diseases. Combining several drugs that target different steps of the viral life cycle enables use of lower doses of individual drugs (and thereby reduction of potential side effects, which frequently occur during long term therapy) and reduces drug-resistance development. Currently, several HIV and HCV protease inhibitors are routinely used in clinical practice. In addition, a drug including an inhibitor of SARS-CoV-2 main protease, nirmatrelvir (co-administered with a pharmacokinetic booster ritonavir as Paxlovid®), was recently authorized for emergency use. This review summarizes the basic features of the proteases of human immunodeficiency virus (HIV), hepatitis C virus (HCV), and SARS-CoV-2 and discusses the properties of their inhibitors in clinical use, as well as development of compounds in the pipeline.

MDO: A Computational Protocol for Prediction of Flexible Enzyme-Ligand Binding Mode

AIM

Developing a method for use in computer aided drug design Background: Predicting the structure of enzyme-ligand binding mode is essential for understanding the properties, functions, and mechanisms of the bio-complex, but is rather difficult due to the enormous sampling space involved.

OBJECTIVE

Accurate prediction of enzyme-ligand binding mode conformation.

METHOD

A new computational protocol, MDO, is proposed for finding the structure of ligand binding pose. MDO consists of sampling enzyme sidechain conformations via molecular dynamics simulation of enzyme-ligand system and clustering of the enzyme configurations, sampling ligand binding poses via molecular docking and clustering of the ligand conformations, and the optimal ligand binding pose prediction via geometry optimization and ranking by the ONIOM method. MDO is tested on 15 enzyme-ligand complexes with known accurate structures.

RESULTS

The success rate of MDO predictions, with RMSD < 2 Å, is 67%, substantially higher than the 40% success rate of conventional methods. The MDO success rate can be increased to 83% if the ONIOM calculations are applied only for the starting poses with ligands inside the binding cavities.

CONCLUSION

The MDO protocol provides high quality enzyme-ligand binding mode prediction with reasonable computational cost. The MDO protocol is recommended for use in the structure-based drug design.

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.

Defining the substrate envelope of SARS-CoV-2 main protease to predict and avoid drug resistance

Coronaviruses can evolve and spread rapidly to cause severe disease morbidity and mortality, as exemplified by SARS-CoV-2 variants of the COVID-19 pandemic. Although currently available vaccines remain mostly effective against SARS-CoV-2 variants, additional treatment strategies are needed. Inhibitors that target essential viral enzymes, such as proteases and polymerases, represent key classes of antivirals. However, clinical use of antiviral therapies inevitably leads to emergence of drug resistance. In this study we implemented a strategy to pre-emptively address drug resistance to protease inhibitors targeting the main protease (M^pro) of SARS-CoV-2, an essential enzyme that promotes viral maturation. We solved nine high-resolution cocrystal structures of SARS-CoV-2 M^pro bound to substrate peptides and six structures with cleavage products. These structures enabled us to define the substrate envelope of M^pro, map the critical recognition elements, and identify evolutionarily vulnerable sites that may be susceptible to resistance mutations that would compromise binding of the newly developed M^pro inhibitors. Our results suggest strategies for developing robust inhibitors against SARS-CoV-2 that will retain longer-lasting efficacy against this evolving viral pathogen.

Combining classical molecular docking with self-consistent charge density-functional tight-binding computations for the efficient and quality prediction of ligand binding structure

To improve the successful prediction rate of the existing molecular docking methods, a new docking approach is proposed that consists of three steps: generating an ensemble of docked poses with a conventional docking method, performing clustering analysis of the ensemble to select the representative poses, and optimizing the representative structures with a low-cost quantum mechanics method. Three quantum mechanics methods, self-consistent charge density-functional tight-binding, ONIOM(DFT:PM6), and ONIOM(SCC-DFTB:PM6), are tested on 18 ligand-receptor bio-complexes. The rate of successful binding pose predictions by the proposed self-consistent charge density-functional tight-binding docking method is the highest, at 67%. The self-consistent charge density-functional tight-binding docking method should be useful for the structure-based drug design.

Deciphering the Molecular Mechanism of HCV Protease Inhibitor Fluorination as a General Approach to Avoid Drug Resistance

Third generation Hepatitis C virus (HCV) NS3/4A protease inhibitors (PIs), glecaprevir and voxilaprevir, are highly effective across genotypes and against many resistant variants. Unlike earlier PIs, these compounds have fluorine substitutions on the P2-P4 macrocycle and P1 moieties. Fluorination has long been used in medicinal chemistry as a strategy to improve physicochemical properties and potency. However, the molecular basis by which fluorination improves potency and resistance profile of HCV NS3/4A PIs is not well understood. To systematically analyze the contribution of fluorine substitutions to inhibitor potency and resistance profile, we used a multi-disciplinary approach involving inhibitor design and synthesis, enzyme inhibition assays, co-crystallography, and structural analysis. A panel of inhibitors in matched pairs were designed with and without P4 cap fluorination, tested against WT protease and the D168A resistant variant, and a total of 22 high-resolution co-crystal structures were determined. While fluorination did not significantly improve potency against the WT protease, PIs with fluorinated P4 caps retained much better potency against the D168A protease variant. Detailed analysis of the co-crystal structures revealed that PIs with fluorinated P4 caps can sample alternate binding conformations that enable adapting to structural changes induced by the D168A substitution. Our results elucidate molecular mechanisms of fluorine-specific inhibitor interactions that can be leveraged in avoiding drug resistance.

Viral proteases: Structure, mechanism and inhibition

Viral proteases are diverse in structure, oligomeric state, catalytic mechanism, and substrate specificity. This chapter focuses on proteases from viruses that are relevant to human health: human immunodeficiency virus subtype 1 (HIV-1), hepatitis C (HCV), human T-cell leukemia virus type 1 (HTLV-1), flaviviruses, enteroviruses, and coronaviruses. The proteases of HIV-1 and HCV have been successfully targeted for therapeutics, with picomolar FDA-approved drugs currently used in the clinic. The proteases of HTLV-1 and the other virus families remain emerging therapeutic targets at different stages of the drug development process. This chapter provides an overview of the current knowledge on viral protease structure, mechanism, substrate recognition, and inhibition. Particular focus is placed on recent advances in understanding the molecular basis of diverse substrate recognition and resistance, which is essential toward designing novel protease inhibitors as antivirals.

Identification of a Chlorogenic Ester as a Monoamine Oxidase (MAO-B) Inhibitor by Integrating "Traditional and Machine Learning" Virtual Screening and In Vitro as well as In Vivo Validation: A Lead against Neurodegenerative Disorders?

Parkinson's disease (PD) is the furthermost motor disorder of adult-onset dementia connected to memory and other cognitive abilities. Monoamine oxidases (MAOs) have gained significant attention in recent years owing to their possible therapeutic use against PD. Expression of MAO-B has been found to be elevated in PD patients for increased uptake of dopamine, producing hydrogen peroxide and finally causing neuronal injury. In this work, two new compounds have been identified as leads against MAO-B, and one of those compounds has been validated in vitro and in vivo. From the Protein Data Bank, MAO-B protein structures complexed with selegiline, 6-hydroxy-N-propargyl-1(R)-aminoindan, or a chromen derivative have been selected as templates for shape-based virtual screening (SB-VS) against the Traditional Chinese Medicinal (TCM) natural database. In parallel, using machine learning, a molecular-descriptor-based support vector model (SVM) was prepared and screened. For this purpose, naïve Bayesian, logistic regression, and random forest strategies were employed with the best specific molecular descriptor, which yielded a model with an overall accuracy (Q) of 0.81. Two common hit compounds lead-1 and lead-2 resulting from both shape and SVM screenings were analyzed through molecular docking and molecular dynamics (MD) simulation (200 ns). Also, from trajectory analysis such as molecular mechanics generalized Born surface area (MMGB/SA) and the residual interaction network (RIN) analyzer, both leads were found to bind at the active site with a favorable correlated motion, including domain movements. Lead-2, which is a chlorogenic ester, was synthesized and found to have no cytotoxic effect up to 50 μg/mL on Neuro-2A cells. The significant reactive oxygen species (ROS) scavenging activity by lead-2 could be correlated to its neuroprotective efficacy. Its capacity to inhibit human MAO-B through a competitive mode could be observed. An experimental zebra fish model confirms the neuroprotection by lead-2 by assessing the locomotor activities under malathion influence and treatment of lead-2. Also, histopathology analysis revealed that lead-2 could slow down degeneration in the brain. The present study emphasizes that integrating machine learning in parallel with traditional virtual screening may be useful to identify effective lead compounds for a given target.

Elasticity-Associated Functionality and Inhibition of the HIV Protease

HIV protease plays a critical role in the life cycle of the virus through the generation of mature and infectious virions. Detailed knowledge of the structure of the enzyme and its substrate has led to the development of protease inhibitors. However, the development of resistance to all currently available protease inhibitors has contributed greatly to the decreased success of antiretroviral therapy. When therapy failure occurs, multiple mutations are found within the protease sequence starting with primary mutations, which directly impact inhibitor binding, which can also negatively impact viral fitness and replicative capacity by decreasing the binding affinity of the natural substrates to the protease. As such, secondary mutations which are located outside of the active site region accumulate to compensate for the recurrently deleterious effects of primary mutations. However, the resistance mechanism of these secondary mutations is not well understood, but what is known is that these secondary mutations contribute to resistance in one of two ways, either through increasing the energetic penalty associated with bringing the protease into the closed conformation, or, through decreasing the stability of the protein/drug complex in a manner that increases the dissociation rate of the drug, leading to diminished inhibition. As a result, the elasticity of the enzyme-substrate complex has been implicated in the successful recognition and catalysis of the substrates which may be inferred to suggest that the elasticity of the enzyme/drug complex plays a role in resistance. A realistic representation of the dynamic nature of the protease may provide a more powerful tool in structure-based drug design algorithms.

Cantilever-centric mechanism of cooperative non-active site mutations in HIV protease: Implications for flap dynamics

The HIV-1 protease is an important drug target in antiretroviral therapy due to the crucial role it plays in viral maturation. A greater understanding of the dynamics of the protease as a result of drug-induced mutations has been successfully elucidated using computational models in the past. We performed induced-fit docking studies and molecular dynamics simulations on the wild-type South African HIV-1 subtype C protease and two non-active site mutation-containing protease variants; HP3 PR and HP4 PR. The HP3 PR contained the I13V, I62V, and V77I mutations while HP4 PR contained the same mutations with the addition of the L33F mutation. The simulations were initiated in a cubic cell universe containing explicit solvent, with the protease variants beginning in the fully closed conformation. The trajectory for each simulation totalled 50 ns. The results indicate that the mutations increase the dynamics of the flap, hinge, fulcrum and cantilever regions when compared to the wild-type protease while in complex with protease inhibitors. Specifically, these mutations result in the protease favouring the semi-open conformation when in complex with inhibitors. Moreover, the HP4 PR adopted curled flap tip conformers which coordinated several water molecules into the active site in a manner that may reduce inhibitor binding affinity. The mutations affected the thermodynamic landscape of inhibitor binding as there were fewer observable chemical contacts between the mutated variants and saquinavir, atazanavir and darunavir. These data help to elucidate the biophysical basis for the selection of cooperative non-active site mutations by the HI virus.

Deciphering Complex Mechanisms of Resistance and Loss of Potency through Coupled Molecular Dynamics and Machine Learning

Drug resistance threatens many critical therapeutics through mutations in the drug target. The molecular mechanisms by which combinations of mutations, especially those remote from the active site, alter drug binding to confer resistance are poorly understood and thus difficult to counteract. A machine learning strategy was developed that coupled parallel molecular dynamics simulations with experimental potency to identify specific conserved mechanisms underlying resistance. Physical features were extracted from the simulations, analyzed, and integrated into one consistent and interpretable elastic network model. To rigorously test this strategy, HIV-1 protease variants with diverse mutations were used, with potencies ranging from picomolar to micromolar to the drug darunavir. Feature reduction resulted in a model with four specific features that predicts for both the training and test sets inhibitor binding free energy within 1 kcal/mol of the experimental value over this entire range of potency. These predictive features are physically interpretable, as they vary specifically with affinity and diagonally transverse across the protease homodimer. This physics-based strategy of parallel molecular dynamics and machine learning captures mechanisms by which complex combinations of mutations confer resistance and identify critical features that serve as bellwethers of affinity, which will be critical in future drug design.

Inhibiting HTLV-1 Protease: A Viable Antiviral Target

Human T-cell lymphotropic virus type 1 (HTLV-1) is a retrovirus that can cause severe paralytic neurologic disease and immune disorders as well as cancer. An estimated 20 million people worldwide are infected with HTLV-1, with prevalence reaching 30% in some parts of the world. In stark contrast to HIV-1, no direct acting antivirals (DAAs) exist against HTLV-1. The aspartyl protease of HTLV-1 is a dimer similar to that of HIV-1 and processes the viral polyprotein to permit viral maturation. We report that the FDA-approved HIV-1 protease inhibitor darunavir (DRV) inhibits the enzyme with 0.8 μM potency and provides a scaffold for drug design against HTLV-1. Analogs of DRV that we designed and synthesized achieved submicromolar inhibition against HTLV-1 protease and inhibited Gag processing in viral maturation assays and in a chronically HTLV-1 infected cell line. Cocrystal structures of these inhibitors with HTLV-1 protease highlight opportunities for future inhibitor design. Our results show promise toward developing highly potent HTLV-1 protease inhibitors as therapeutic agents against HTLV-1 infections.

Avoiding Drug Resistance in HIV Reverse Transcriptase

HIV reverse transcriptase (RT) is an enzyme that plays a major role in the replication cycle of HIV and has been a key target of anti-HIV drug development efforts. Because of the high genetic diversity of the virus, mutations in RT can impart resistance to various RT inhibitors. As the prevalence of drug resistance mutations is on the rise, it is necessary to design strategies that will lead to drugs less susceptible to resistance. Here we provide an in-depth review of HIV reverse transcriptase, current RT inhibitors, novel RT inhibitors, and mechanisms of drug resistance. We also present novel strategies that can be useful to overcome RT's ability to escape therapies through drug resistance. While resistance may not be completely avoidable, designing drugs based on the strategies and principles discussed in this review could decrease the prevalence of drug resistance.

Crystal Structure of SARS-CoV-2 Main Protease in Complex with the Non-Covalent Inhibitor ML188

Viral proteases are critical enzymes for the maturation of many human pathogenic viruses and thus are key targets for direct acting antivirals (DAAs). The current viral pandemic caused by SARS-CoV-2 is in dire need of DAAs. The Main protease (Mpro) is the focus of extensive structure-based drug design efforts which are mostly covalent inhibitors targeting the catalytic cysteine. ML188 is a non-covalent inhibitor designed to target SARS-CoV-1 Mpro, and provides an initial scaffold for the creation of effective pan-coronavirus inhibitors. In the current study, we found that ML188 inhibits SARS-CoV-2 Mpro at 2.5 µM, which is more potent than against SAR-CoV-1 Mpro. We determined the crystal structure of ML188 in complex with SARS-CoV-2 Mpro to 2.39 Å resolution. Sharing 96% sequence identity, structural comparison of the two complexes only shows subtle differences. Non-covalent protease inhibitors complement the design of covalent inhibitors against SARS-CoV-2 main protease and are critical initial steps in the design of DAAs to treat CoVID 19.

A synergy of activity, stability, and inhibitor-interaction of HIV-1 protease mutants evolved under drug-pressure

A clinically-relevant, drug-resistant mutant of HIV-1 protease (PR), termed Flap+_(I54V) and containing L10I, G48V, I54V and V82A mutations, is known to produce significant changes in the entropy and enthalpy balance of drug-PR interactions, compared to wild-type PR. A similar mutant, Flap+_(I54A) , which evolves from Flap+_(I54V) and contains the single change at residue 54 relative to Flap+_(I54V) , does not. Yet, how Flap+_(I54A) behaves in solution is not known. To understand the molecular basis of V54A evolution, we compared nuclear magnetic resonance (NMR) spectroscopy, fluorescence spectroscopy, isothermal titration calorimetry, and enzymatic assay data from four PR proteins: PR (pWT), Flap+_(I54V) , Flap+_(I54A) , and Flap+_(I54) , a control mutant that contains only L10I, G48V and V82A mutations. Our data consistently show that selection to the smaller side chain at residue 54, not only decreases inhibitor affinity, but also restores the catalytic activity.

Incorporating the Coevolving Information of Substrates in Predicting HIV-1 Protease Cleavage Sites

Human immunodeficiency virus 1 (HIV-1) protease (PR) plays a crucial role in the maturation of the virus. The study of substrate specificity of HIV-1 PR as a new endeavor strives to increase our ability to understand how HIV-1 PR recognizes its various cleavage sites. To predict HIV-1 PR cleavage sites, most of the existing approaches have been developed solely based on the homogeneity of substrate sequence information with supervised classification techniques. Although efficient, these approaches are found to be restricted to the ability of explaining their results and probably provide few insights into the mechanisms by which HIV-1 PR cleaves the substrates in a site-specific manner. In this work, a coevolutionary pattern-based prediction model for HIV-1 PR cleavage sites, namely EvoCleave, is proposed by integrating the coevolving information obtained from substrate sequences with a linear SVM classifier. The experiment results showed that EvoCleave yielded a very promising performance in terms of ROC analysis and f-measure. We also prospectively assessed the biological significance of coevolutionary patterns by applying them to study three fundamental issues of HIV-1 PR cleavage site. The analysis results demonstrated that the coevolutionary patterns offered valuable insights into the understanding of substrate specificity of HIV-1 PR.

Electrostatics Plays a Crucial Role in HIV-1 Protease Substrate Binding, Drugs Fail to Take Advantage

HIV-1 protease (HIVPR) is an important drug target for combating AIDS. This enzyme is an aspartyl protease that is functionally active in its dimeric form. Nuclear magnetic resonance reports have convincingly shown that a pseudosymmetry exists at the HIVPR active site, where only one of the two aspartates remains protonated over the pH range of 2.5-7.0. To date, all HIVPR-targeted drug design strategies focused on maximizing the size-shape complementarity and van der Waals interactions of the small molecule drugs with the deprotonated, symmetric active site envelope of crystallized HIVPR. However, these strategies were ineffective with the emergence of drug resistant protease variants, primarily due to the steric clashes at the active site. In this study, we traced a specificity in the substrate binding motif that emerges primarily from the asymmetrical electrostatic potential present in the protease active site due to the uneven protonation. Our detailed results from atomistic molecular dynamics simulations show that while such a specific mode of substrate binding involves significant electrostatic interactions, none of the existing drugs or inhibitors could utilize this electrostatic hot spot. As the electrostatic is long-range interaction, it can provide sufficient binding strength without the necessity of increasing the bulkiness of the inhibitors. We propose that introducing the electrostatic component along with optimal fitting at the binding pocket could pave the way for promising designs that might be more effective against both wild type and HIVPR resistant variants.

HIV-1 Gag mutations alone are sufficient to reduce darunavir susceptibility during virological failure to boosted PI therapy

BACKGROUND

Virological failure (VF) to boosted PIs with a high genetic barrier is not usually linked to the development of resistance-associated mutations in the protease gene.

METHODS

From a cohort of 520 HIV-infected subjects treated with lopinavir/ritonavir or darunavir/ritonavir monotherapy, we retrospectively identified nine patients with VF. We sequenced the HIV-1 Gag-protease region and generated clonal virus from plasma samples. We characterized phenotypically clonal variants in terms of replicative capacity and susceptibility to PIs. Also, we used VESPA to identify signature mutations and 3D molecular modelling information to detect conformational changes in the Gag region.

RESULTS

All subjects analysed harboured Gag-associated polymorphisms in the absence of resistance mutations in the protease gene. Most Gag changes occurred outside Gag cleavage sites. VESPA analyses identified K95R and R286K (P < 0.01) as signature mutations in Gag present at VF. In one out of four patients with clonal analysis available, we identified clonal variants with high replicative capacity and 8- to 13-fold reduction in darunavir susceptibility. These clonal variants harboured K95R, R286K and additional mutations in Gag. Low susceptibility to darunavir was dependent on the Gag sequence context. All other clonal variants analysed preserved drug susceptibility and virus replicative capacity.

CONCLUSIONS

Gag mutations may reduce darunavir susceptibility in the absence of protease mutations while preserving viral fitness. This effect is Gag-sequence context dependent and may occur during boosted PI failure.

Structural Analysis of Potent Hybrid HIV-1 Protease Inhibitors Containing Bis-tetrahydrofuran in a Pseudosymmetric Dipeptide Isostere

The design, synthesis, and X-ray structural analysis of hybrid HIV-1 protease inhibitors (PIs) containing bis-tetrahydrofuran (bis-THF) in a pseudo-C₂-symmetric dipeptide isostere are described. A series of PIs were synthesized by incorporating bis-THF of darunavir on either side of the Phe-Phe isostere of lopinavir in combination with hydrophobic amino acids on the opposite P2/P2' position. Structure-activity relationship studies indicated that the bis-THF moiety can be attached at either the P2 or P2' position without significantly affecting potency. However, the group on the opposite P2/P2' position had a dramatic effect on potency depending on the size and shape of the side chain. Cocrystal structures of inhibitors with wild-type HIV-1 protease revealed that the bis-THF moiety retained similar interactions as observed in the darunavir-protease complex regardless of the position on the Phe-Phe isostere. Analyses of cocrystal structures and molecular dynamics simulations provide insights into optimizing HIV-1 PIs containing bis-THF in non-sulfonamide dipeptide isosteres.

Molecular and Structural Mechanism of Pan-Genotypic HCV NS3/4A Protease Inhibition by Glecaprevir

Hepatitis C virus, causative agent of chronic viral hepatitis, infects 71 million people worldwide and is divided into seven genotypes and multiple subtypes with sequence identities between 68 to 82%. While older generation direct-acting antivirals had varying effectiveness against different genotypes, the newest NS3/4A protease inhibitors including glecaprevir (GLE) have pan-genotypic activity. The structural basis for pan-genotypic inhibition and effects of polymorphisms on inhibitor potency were not well-known due to lack of crystal structures of GLE-bound NS3/4A or genotypes other than 1. In this study, we determined the crystal structures of NS3/4A from genotypes 1a, 3a, 4a, and 5a in complex with GLE. Comparison with the highly similar grazoprevir indicated the mechanism of GLE's drastic improvement in potency. We found that, while GLE is highly potent against wild-type NS3/4A of all genotypes, specific resistance-associated substitutions (RASs) confer orders of magnitude loss in inhibition. Our crystal structures reveal molecular mechanisms behind pan-genotypic activity of GLE, including potency loss due to RASs at D168. Our structures permit for the first time analysis of changes due to polymorphisms among genotypes, providing insights into design principles that can aid future drug development and potentially can be extended to other proteins.

Picomolar to Micromolar: Elucidating the Role of Distal Mutations in HIV-1 Protease in Conferring Drug Resistance

Drug resistance continues to be a growing global problem. The efficacy of small molecule inhibitors is threatened by pools of genetic diversity in all systems, including antibacterials, antifungals, cancer therapeutics, and antivirals. Resistant variants often include combinations of active site mutations and distal "secondary" mutations, which are thought to compensate for losses in enzymatic activity. HIV-1 protease is the ideal model system to investigate these combinations and underlying molecular mechanisms of resistance. Darunavir (DRV) binds wild-type (WT) HIV-1 protease with a potency of <5 pM, but we have identified a protease variant that loses potency to DRV 150 000-fold, with 11 mutations in and outside the active site. To elucidate the roles of these mutations in DRV resistance, we used a multidisciplinary approach, combining enzymatic assays, crystallography, and molecular dynamics simulations. Analysis of protease variants with 1, 2, 4, 8, 9, 10, and 11 mutations showed that the primary active site mutations caused ∼50-fold loss in potency (2 mutations), while distal mutations outside the active site further decreased DRV potency from 13 nM (8 mutations) to 0.76 μM (11 mutations). Crystal structures and simulations revealed that distal mutations induce subtle changes that are dynamically propagated through the protease. Our results reveal that changes remote from the active site directly and dramatically impact the potency of the inhibitor. Moreover, we find interdependent effects of mutations in conferring high levels of resistance. These mechanisms of resistance are likely applicable to many other quickly evolving drug targets, and the insights may have implications for the design of more robust inhibitors.

Target-Specific Prediction of Ligand Affinity with Structure-Based Interaction Fingerprints

Discovery and optimization of small molecule inhibitors as therapeutic drugs have immensely benefited from rational structure-based drug design. With recent advances in high-resolution structure determination, computational power, and machine learning methodology, it is becoming more tractable to elucidate the structural basis of drug potency. However, the applicability of machine learning models to drug design is limited by the interpretability of the resulting models in terms of feature importance. Here, we take advantage of the large number of available inhibitor-bound HIV-1 protease structures and associated potencies to evaluate inhibitor diversity and machine learning models to predict ligand affinity. First, using a hierarchical clustering approach, we grouped HIV-1 protease inhibitors and identified distinct core structures. Explicit features including protein-ligand interactions were extracted from high-resolution cocrystal structures as 3D-based fingerprints. We found that a gradient boosting machine learning model with this explicit feature attribution can predict binding affinity with high accuracy. Finally, Shapley values were derived to explain local feature importance. We found specific van der Waals (vdW) interactions of key protein residues are pivotal for the predicted potency. Protein-specific and interpretable prediction models can guide the optimization of many small molecule drugs for improved potency.

NMR and MD studies combined to elucidate inhibitor and water interactions of HIV-1 protease and their modulations with resistance mutations

Over the last two decades, both the sensitivity of NMR and the time scale of molecular dynamics (MD) simulation have increased tremendously and have advanced the field of protein dynamics. HIV-1 protease has been extensively studied using these two methods, and has presented a framework for cross-evaluation of structural ensembles and internal dynamics by integrating the two methods. Here, we review studies from our laboratories over the last several years, to understand the mechanistic basis of protease drug-resistance mutations and inhibitor responses, using NMR and crystal structure-based parallel MD simulations. Our studies demonstrate that NMR relaxation experiments, together with crystal structures and MD simulations, significantly contributed to the current understanding of structural/dynamic changes due to HIV-1 protease drug resistance mutations.

Resistance outside the substrate envelope: hepatitis C NS3/4A protease inhibitors

Direct acting antivirals have dramatically increased the efficacy and tolerability of hepatitis C treatment, but drug resistance has emerged with some of these inhibitors, including nonstructural protein 3/4 A protease inhibitors (PIs). Although many co-crystal structures of PIs with the NS3/4A protease have been reported, a systematic review of these crystal structures in the context of the rapidly emerging drug resistance especially for early PIs has not been performed. To provide a framework for designing better inhibitors with higher barriers to resistance, we performed a quantitative structural analysis using co-crystal structures and models of HCV NS3/4A protease in complex with natural substrates and inhibitors. By comparing substrate structural motifs and active site interactions with inhibitor recognition, we observed that the selection of drug resistance mutations correlates with how inhibitors deviate from viral substrates in molecular recognition. Based on this observation, we conclude that guiding the design process with native substrate recognition features is likely to lead to more robust small molecule inhibitors with decreased susceptibility to resistance.

Structural Adaptation of Darunavir Analogues against Primary Mutations in HIV-1 Protease

HIV-1 protease is one of the prime targets of agents used in antiretroviral therapy against HIV. However, under selective pressure of protease inhibitors, primary mutations at the active site weaken inhibitor binding to confer resistance. Darunavir (DRV) is the most potent HIV-1 protease inhibitor in clinic; resistance is limited, as DRV fits well within the substrate envelope. Nevertheless, resistance is observed due to hydrophobic changes at residues including I50, V82, and I84 that line the S1/S1' pocket within the active site. Through enzyme inhibition assays and a series of 12 crystal structures, we interrogated susceptibility of DRV and two potent analogues to primary S1' mutations. The analogues had modifications at the hydrophobic P1' moiety compared to DRV to better occupy the unexploited space in the S1' pocket where the primary mutations were located. Considerable losses of potency were observed against protease variants with I84V and I50V mutations for all three inhibitors. The crystal structures revealed an unexpected conformational change in the flap region of I50V protease bound to the analogue with the largest P1' moiety, indicating interdependency between the S1' subsite and the flap region. Collective analysis of protease-inhibitor interactions in the crystal structures using principle component analysis was able to distinguish inhibitor identity and relative potency solely based on van der Waals contacts. Our results reveal the complexity of the interplay between inhibitor P1' moiety and S1' mutations and validate principle component analyses as a useful tool for distinguishing resistance and inhibitor potency.

Structure of 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase-dihydropteroate synthase from Plasmodium vivax sheds light on drug resistance

The genomes of the malaria-causing Plasmodium parasites encode a protein fused of 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase (HPPK) and dihydropteroate synthase (DHPS) domains that catalyze sequential reactions in the folate biosynthetic pathway. Whereas higher organisms derive folate from their diet and lack the enzymes for its synthesis, most eubacteria and a number of lower eukaryotes including malaria parasites synthesize tetrahydrofolate via DHPS. Plasmodium falciparum (Pf) and Plasmodium vivax (Pv) HPPK-DHPSs are currently targets of drugs like sulfadoxine (SDX). The SDX effectiveness as an antimalarial drug is increasingly diminished by the rise and spread of drug-resistant mutations. Here, we present the crystal structure of PvHPPK-DHPS in complex with four substrates/analogs, revealing the bifunctional PvHPPK-DHPS architecture in an unprecedented state of enzymatic activation. SDX's effect on HPPK-DHPS is due to 4-amino benzoic acid (pABA) mimicry, and the PvHPPK-DHPS structure sheds light on the SDX-binding cavity, as well as on mutations that effect SDX potency. We mapped five dominant drug resistance mutations in PvHPPK-DHPS: S382A, A383G, K512E/D, A553G, and V585A, most of which occur individually or in clusters proximal to the pABA-binding site. We found that these resistance mutations subtly alter the intricate enzyme/pABA/SDX interactions such that DHPS affinity for pABA is diminished only moderately, but its affinity for SDX is changed substantially. In conclusion, the PvHPPK-DHPS structure rationalizes and unravels the structural bases for SDX resistance mutations and highlights architectural features in HPPK-DHPSs from malaria parasites that can form the basis for developing next-generation anti-folate agents to combat malaria parasites.

The Molecular Origin of Enthalpy/Entropy Compensation in Biomolecular Recognition

Biomolecular recognition can be stubborn; changes in the structures of associating molecules, or the environments in which they associate, often yield compensating changes in enthalpies and entropies of binding and no net change in affinities. This phenomenon—termed enthalpy/entropy (H/S) compensation—hinders efforts in biomolecular design, and its incidence—often a surprise to experimentalists—makes interactions between biomolecules difficult to predict. Although characterizing H/S compensation requires experimental care, it is unquestionably a real phenomenon that has, from an engineering perspective, useful physical origins. Studying H/S compensation can help illuminate the still-murky roles of water and dynamics in biomolecular recognition and self-assembly. This review summarizes known sources of H/ S compensation (real and perceived) and lays out a conceptual framework for understanding and dissecting—and, perhaps, avoiding or exploiting—this phenomenon in biophysical systems.

Elucidating the Interdependence of Drug Resistance from Combinations of Mutations

HIV-1 protease is responsible for the cleavage of 12 nonhomologous sites within the Gag and Gag-Pro-Pol polyproteins in the viral genome. Under the selective pressure of protease inhibition, the virus evolves mutations within (primary) and outside of (secondary) the active site, allowing the protease to process substrates while simultaneously countering inhibition. The primary protease mutations impede inhibitor binding directly, while the secondary mutations are considered accessory mutations that compensate for a loss in fitness. However, the role of secondary mutations in conferring drug resistance remains a largely unresolved topic. We have shown previously that mutations distal to the active site are able to perturb binding of darunavir (DRV) via the protein's internal hydrogen-bonding network. In this study, we show that mutations distal to the active site, regardless of context, can play an interdependent role in drug resistance. Applying eigenvalue decomposition to collections of hydrogen bonding and van der Waals interactions from a series of molecular dynamics simulations of 15 diverse HIV-1 protease variants, we identify sites in the protease where amino acid substitutions lead to perturbations in nonbonded interactions with DRV and/or the hydrogen-bonding network of the protease itself. While primary mutations are known to drive resistance in HIV-1 protease, these findings delineate the significant contributions of accessory mutations to resistance. Identifying the variable positions in the protease that have the greatest impact on drug resistance may aid in future structure-based design of inhibitors.

Interdependence of Inhibitor Recognition in HIV-1 Protease

Molecular recognition is a highly interdependent process. Subsite couplings within the active site of proteases are most often revealed through conditional amino acid preferences in substrate recognition. However, the potential effect of these couplings on inhibition and thus inhibitor design is largely unexplored. The present study examines the interdependency of subsites in HIV-1 protease using a focused library of protease inhibitors, to aid in future inhibitor design. Previously a series of darunavir (DRV) analogs was designed to systematically probe the S1′ and S2′ subsites. Co-crystal structures of these analogs with HIV-1 protease provide the ideal opportunity to probe subsite interdependency. All-atom molecular dynamics simulations starting from these structures were performed and systematically analyzed in terms of atomic fluctuations, intermolecular interactions, and water structure. These analyses reveal that the S1′ subsite highly influences other subsites: the extension of the hydrophobic P1′ moiety results in 1) reduced van der Waals contacts in the P2′ subsite, 2) more variability in the hydrogen bond frequencies with catalytic residues and the flap water, and 3) changes in the occupancy of conserved water sites both proximal and distal to the active site. In addition, one of the monomers in this homodimeric enzyme has atomic fluctuations more highly correlated with DRV than the other monomer. These relationships intricately link the HIV-1 protease subsites and are critical to understanding molecular recognition and inhibitor binding. More broadly, the interdependency of subsite recognition within an active site requires consideration in the selection of chemical moieties in drug design; this strategy is in contrast to what is traditionally done with independent optimization of chemical moieties of an inhibitor.

Effect of polarization on HIV-1protease and fluoro-substituted inhibitors binding energies by large scale molecular dynamics simulations

Molecular dynamics simulations in explicit water are carried out to study the binding of six inhibitors to HIV-1 protease (PR) for up to 700 ns using the standard AMBER force field and polarized protein-specific charge (PPC). PPC is derived from quantum mechanical calculation for protein in solution and therefore it includes electronic polarization effect. Our results show that in all six systems, the bridging water W301 drifts away from the binding pocket in AMBER simulation. However, it is very stable in all six complexes systems using PPC. Especially, intra-protease, protease-inhibitor hydrogen bonds are dynamic stabilized in MD simulation. The computed binding free energies of six complexes have a significantly linear correlation with those experiment values and the correlation coefficient is found to be 0.91 in PPC simulation. However, the result from AMBER simulation shows a weaker correlation with the correlation coefficient of −0.51 due to the lack of polarization effect. Detailed binding interactions of W301, inhibitors with PR are further analyzed and discussed. The present study provides important information to quantitative understanding the interaction mechanism of PR-inhibitor and PR-W301 and these data also emphasizes the importance of both the electronic polarization and the bridging water molecule in predicting precisely binding affinities.

Molecular and Dynamic Mechanism Underlying Drug Resistance in Genotype 3 Hepatitis C NS3/4A Protease

Hepatitis C virus (HCV), affecting an estimated 150 million people worldwide, is the leading cause of viral hepatitis, cirrhosis and hepatocellular carcinoma. HCV is genetically diverse with six genotypes (GTs) and multiple subtypes of different global distribution and prevalence. Recent development of direct-acting antivirals against HCV including NS3/4A protease inhibitors (PIs) has greatly improved treatment outcomes for GT-1. However, all current PIs exhibit significantly lower potency against GT-3. Lack of structural data on GT-3 protease has limited our ability to understand PI failure in GT-3. In this study the molecular basis for reduced potency of current inhibitors against GT-3 NS3/4A protease is elucidated with structure determination, molecular dynamics simulations and inhibition assays. A chimeric GT-1a3a NS3/4A protease amenable to crystallization was engineered to recapitulate decreased sensitivity of GT-3 protease to PIs. High-resolution crystal structures of this GT-1a3a bound to 3 PIs, asunaprevir, danoprevir and vaniprevir, had only subtle differences relative to GT-1 despite orders of magnitude loss in affinity. In contrast, hydrogen-bonding interactions within and with the protease active site and dynamic fluctuations of the PIs were drastically altered. The correlation between loss of intermolecular dynamics and inhibitor potency suggests a mechanism where polymorphisms between genotypes (or selected mutations) in the drug target confer resistance through altering the intermolecular dynamics of the protein-inhibitor complex.

Recent Progress in the Development of HIV-1 Protease Inhibitors for the Treatment of HIV/AIDS

HIV-1 protease inhibitors continue to play an important role in the treatment of HIV/AIDS, transforming this deadly ailment into a more manageable chronic infection. Over the years, intensive research has led to a variety of approved protease inhibitors for the treatment of HIV/AIDS. In this review, we outline current drug design and medicinal chemistry efforts toward the development of next-generation protease inhibitors beyond the currently approved drugs.

Kinetic, thermodynamic and structural analysis of tamiphosphor binding to neuraminidase of H1N1 (2009) pandemic influenza

Influenza virus causes severe respiratory infections that are responsible for up to half a million deaths worldwide each year. Two inhibitors targeting viral neuraminidase have been approved to date (oseltamivir, zanamivir). However, the rapid development of antiviral drug resistance and the efficient transmission of resistant viruses among humans represent serious threats to public health. The approved influenza neuraminidase inhibitors have (oxa)cyclohexene scaffolds designed to mimic the oxonium transition state during enzymatic cleavage of sialic acid. Their active forms contain a carboxylate that interacts with three arginine residues in the enzyme active site. Recently, the phosphonate group was successfully used as an isostere of the carboxylate in oseltamivir, and the resulting compound, tamiphosphor, was identified as a highly active neuraminidase inhibitor. However, the structure of the complex of this promising inhibitor with neuraminidase has not yet been reported. Here, we analyzed the interaction of a set of oseltamivir and tamiphosphor derivatives with neuraminidase from the A/California/07/2009 (H1N1) influenza virus. We thermodynamically characterized the binding of oseltamivir carboxylate or tamiphosphor to the neuraminidase catalytic domain by protein microcalorimetry, and we determined crystal structure of the catalytic domain in complex with tamiphosphor at 1.8 Å resolution. This structural information should aid rational design of the next generation of neuraminidase inhibitors.

Improving Viral Protease Inhibitors to Counter Drug Resistance

Drug resistance is a major problem in health care, undermining therapy outcomes and necessitating novel approaches to drug design. Extensive studies on resistance to viral protease inhibitors, particularly those of HIV-1 and hepatitis C virus (HCV) protease, revealed a plethora of information on the structural and molecular mechanisms underlying resistance. These insights led to several strategies to improve viral protease inhibitors to counter resistance, such as exploiting the essential biological function and leveraging evolutionary constraints. Incorporation of these strategies into structure-based drug design can minimize vulnerability to resistance, not only for viral proteases but for other quickly evolving drug targets as well, toward designing inhibitors one step ahead of evolution to counter resistance with more intelligent and rational design.

Structural and Thermodynamic Effects of Macrocyclization in HCV NS3/4A Inhibitor MK-5172

Recent advances in direct-acting antivirals against Hepatitis C Virus (HCV) have led to the development of potent inhibitors, including MK-5172, that target the viral NS3/4A protease with relatively low susceptibility to resistance. MK-5172 has a P2-P4 macrocycle and a unique binding mode among current protease inhibitors where the P2 quinoxaline packs against the catalytic residues H57 and D81. However, the effect of macrocyclization on this binding mode is not clear, as is the relation between macrocyclization, thermodynamic stabilization, and susceptibility to the resistance mutation A156T. We have determined high-resolution crystal structures of linear and P1-P3 macrocyclic analogs of MK-5172 bound to WT and A156T protease and compared these structures, their molecular dynamics, and experimental binding thermodynamics to the parent compound. We find that the "unique" binding mode of MK-5172 is conserved even when the P2-P4 macrocycle is removed or replaced with a P1-P3 macrocycle. While beneficial to decreasing the entropic penalty associated with binding, the constraint exerted by the P2-P4 macrocycle prevents efficient rearrangement to accommodate the A156T mutation, a deficit alleviated in the linear and P1-P3 analogs. Design of macrocyclic inhibitors against NS3/4A needs to achieve the best balance between exerting optimal conformational constraint for enhancing potency, fitting within the substrate envelope and allowing adaptability to be robust against resistance mutations.

Anti-HIV Drug Discovery and Development: Current Innovations and Future Trends

The early effectiveness of combinatorial antiretroviral therapy (cART) in the treatment of HIV infection has been compromised to some extent by rapid development of multidrug-resistant HIV strains, poor bioavailability, and cumulative toxicities, and so there is a need for alternative strategies of antiretroviral drug discovery and additional therapeutic agents with novel action modes or targets. From this perspective, we first review current strategies of antiretroviral drug discovery and optimization, with the aid of selected examples from the recent literature. We highlight the development of phosphate ester-based prodrugs as a means to improve the aqueous solubility of HIV inhibitors, and the introduction of the substrate envelope hypothesis as a new approach for overcoming HIV drug resistance. Finally, we discuss future directions for research, including opportunities for exploitation of novel antiretroviral targets, and the strategy of activation of latent HIV reservoirs as a means to eradicate the virus.

Molecular mechanisms and design principles for promiscuous inhibitors to avoid drug resistance: lessons learned from HIV-1 protease inhibition

Molecular recognition is central to biology and ranges from highly selective to broadly promiscuous. The ability to modulate specificity at will is particularly important for drug development, and discovery of mechanisms contributing to binding specificity is crucial for our basic understanding of biology and for applications in health care. In this study, we used computational molecular design to create a large dataset of diverse small molecules with a range of binding specificities. We then performed structural, energetic, and statistical analysis on the dataset to study molecular mechanisms of achieving specificity goals. The work was done in the context of HIV‐1 protease inhibition and the molecular designs targeted a panel of wild‐type and drug‐resistant mutant HIV‐1 protease structures. The analysis focused on mechanisms for promiscuous binding to bind robustly even to resistance mutants. Broadly binding inhibitors tended to be smaller in size, more flexible in chemical structure, and more hydrophobic in nature compared to highly selective ones. Furthermore, structural and energetic analyses illustrated mechanisms by which flexible inhibitors achieved binding; we found ligand conformational adaptation near mutation sites and structural plasticity in targets through torsional flips of asymmetric functional groups to form alternative, compensatory packing interactions or hydrogen bonds. As no inhibitor bound to all variants, we designed small cocktails of inhibitors to do so and discovered that they often jointly covered the target set through mechanistic complementarity. Furthermore, using structural plasticity observed in experiments, and potentially in simulations, is suggested to be a viable means of designing adaptive inhibitors that are promiscuous binders. Proteins 2015; 83:351–372. © 2014 Wiley Periodicals, Inc.

Multistage virtual screening and identification of novel HIV-1 protease inhibitors by integrating SVM, shape, pharmacophore and docking methods

The HIV-1 protease has proven to be a crucial component of the HIV replication machinery and a reliable target for anti-HIV drug discovery. In this study, we applied an optimized hierarchical multistage virtual screening method targeting HIV-1 protease. The method sequentially applied SVM (Support Vector Machine), shape similarity, pharmacophore modeling and molecular docking. Using a validation set (270 positives, 155,996 negatives), the multistage virtual screening method showed a high hit rate and high enrichment factor of 80.47% and 465.75, respectively. Furthermore, this approach was applied to screen the National Cancer Institute database (NCI), which contains 260,000 molecules. From the final hit list, 6 molecules were selected for further testing in an in vitro HIV-1 protease inhibitory assay, and 2 molecules (NSC111887 and NSC121217) showed inhibitory potency against HIV-1 protease, with IC50 values of 62 μM and 162 μM, respectively. With further chemical development, these 2 molecules could potentially serve as HIV-1 protease inhibitors.

Effects of drug-resistant mutations on the dynamic properties of HIV-1 protease and inhibition by Amprenavir and Darunavir

Molecular dynamics simulations are performed to investigate the dynamic properties of wild-type HIV-1 protease and its two multi-drug-resistant variants (Flap + (L10I/G48V/I54V/V82A) and Act (V82T/I84V)) as well as their binding with APV and DRV inhibitors. The hydrophobic interactions between flap and 80 s (80’s) loop residues (mainly I50-I84’ and I50’-I84) play an important role in maintaining the closed conformation of HIV-1 protease. The double mutation in Act variant weakens the hydrophobic interactions, leading to the transition from closed to semi-open conformation of apo Act. APV or DRV binds with HIV-1 protease via both hydrophobic and hydrogen bonding interactions. The hydrophobic interactions from the inhibitor is aimed to the residues of I50 (I50’), I84 (I84’), and V82 (V82’) which create hydrophobic core clusters to further stabilize the closed conformation of flaps, and the hydrogen bonding interactions are mainly focused with the active site of HIV-1 protease. The combined change in the two kinds of protease-inhibitor interactions is correlated with the observed resistance mutations. The present study sheds light on the microscopic mechanism underlying the mutation effects on the dynamics of HIV-1 protease and the inhibition by APV and DRV, providing useful information to the design of more potent and effective HIV-1 protease inhibitors.

A virtual screen discovers novel, fragment-sized inhibitors of Mycobacterium tuberculosis InhA

Isoniazid (INH) is usually administered to treat latent Mycobacterium tuberculosis (Mtb) infections and is used in combination therapy to treat active tuberculosis (TB). Unfortunately, resistance to this drug is hampering its clinical effectiveness. INH is a prodrug that must be activated by Mtb catalase-peroxidase (KatG) before it can inhibit InhA (Mtb enoyl-acyl-carrier-protein reductase). Isoniazid-resistant cases of TB found in clinical settings usually involve mutations in or deletion of katG, which abrogate INH activation. Compounds that inhibit InhA without requiring prior activation by KatG would not be affected by this resistance mechanism and hence would display continued potency against these drug-resistant isolates of Mtb. Virtual screening experiments versus InhA in the GO Fight Against Malaria (GO FAM) project were designed to discover new scaffolds that display base-stacking interactions with the NAD cofactor. GO FAM experiments included targets from other pathogens, including Mtb, when they had structural similarity to a malaria target. Eight of the 16 soluble compounds identified by docking against InhA plus visual inspection were modest inhibitors and did not require prior activation by KatG. The best two inhibitors discovered are both fragment-sized compounds and displayed Ki values of 54 and 59 μM, respectively. Importantly, the novel inhibitors discovered have low structural similarity to known InhA inhibitors and thus help expand the number of chemotypes on which future medicinal chemistry efforts can be focused. These new fragment hits could eventually help advance the fight against INH-resistant Mtb strains, which pose a significant global health threat.

Exploring the drug resistance of V32I and M46L mutant HIV-1 protease to inhibitor TMC114: flap dynamics and binding mechanism

Inhibitors of HIV-1 protease (HIV-1-pr) generally only bind to the active site of the protease. However, for some mutants such as V32I and M46L the TMC114 can bind not only to the active cavity but also to the groove of the flexible flaps. Although the second binding site suggests the higher efficiency of the drug against HIV-1-pr, the drug resistance in HIV-1-pr due to mutations cannot be ignored, which prompts us to investigate the molecular mechanisms of drug resistance and behavior of double bound TMC114 (2T) to HIV-1-pr. The conformational dynamics of HIV-1-pr and the binding of TMC114 to the WT, V32I and M46L mutants were investigated with all-atom molecular dynamic (MD) simulation. The 20 ns MD simulation shows many fascinating effects of the inhibitor binding to the WT and mutant proteases. MM-PBSA calculations explain the binding free energies unfavorable for the M46L and V32I mutants as compared to the WT. For the single binding (1T) the less binding affinity can be attributed to the entropic loss for both V32I-1T and M46L-1T. Although the second binding of TMC114 with flap does increase binding energy for the mutants (V32I-2T and M46L-2T), the considerable entropy loss results in the lower binding Gibbs free energies. Thus, binding of TMC114 in the flap region does not help much in the total gain in binding affinity of the system, which was verified from this study and thereby validating experiments.