HIV-1 protease inhibitors from inverse design in the substrate envelope exhibit subnanomolar binding to drug-resistant variants

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.

Structure based design and evaluation of benzoheterocycle derivatives as potential dual HIV-1 protease and reverse transcriptase inhibitors

The development of dual inhibitors of HIV-1 protease and reverse transcriptase is an attractive strategy for multi-target therapeutic of AIDS, which may be privileged in delaying the occurrence of drug resistance. We herein designed a novel kind of dual inhibitors with benzofuran or indole cores. Biological results showed that a number of inhibitors displayed significant activity against both HIV-1 protease and reverse transcriptase. Among which, inhibitor 10f exhibited a good correlation with an approximate ratio of 1: 2 between the two enzymes. Furthermore, the dual inhibitors illustrated similar potency against both the wild-type virus and drug-resistant mutant. In addition, the molecular dynamic simulation studies verified the dual actions of such inhibitors.

Resistor: An algorithm for predicting resistance mutations via Pareto optimization over multistate protein design and mutational signatures

Resistance to pharmacological treatments is a major public health challenge. Here, we introduce Resistor-a structure- and sequence-based algorithm that prospectively predicts resistance mutations for drug design. Resistor computes the Pareto frontier of four resistance-causing criteria: the change in binding affinity (ΔKa) of the (1) drug and (2) endogenous ligand upon a protein's mutation; (3) the probability a mutation will occur based on empirically derived mutational signatures; and (4) the cardinality of mutations comprising a hotspot. For validation, we applied Resistor to EGFR and BRAF kinase inhibitors treating lung adenocarcinoma and melanoma. Resistor correctly identified eight clinically significant EGFR resistance mutations, including the erlotinib and gefitinib "gatekeeper" T790M mutation and five known osimertinib resistance mutations. Furthermore, Resistor predictions are consistent with BRAF inhibitor sensitivity data from both retrospective and prospective experiments using KinCon biosensors. Resistor is available in the open-source protein design software OSPREY.

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.

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.

Decoding molecular mechanism underlying binding of drugs to HIV-1 protease with molecular dynamics simulations and MM-GBSA calculations

HIV-1 protease (PR) is thought to be efficient targets of anti-AIDS drug design. Molecular dynamics (MD) simulations and multiple post-processing analysis technologies were applied to decipher molecular mechanism underlying binding of three drugs Lopinavir (LPV), Nelfinavir (NFV) and Atazanavir (ATV) to the PR. Binding free energies calculated by molecular mechanics generalized Born surface area (MM-GBSA) suggest that compensation between binding enthalpy and entropy plays a vital role in binding of drugs to PR. Dynamics analyses show that binding of LPV, NFV and ATV highly affects structural flexibility, motion modes and dynamics behaviour of the PR, especially for two flaps. Computational alanine scanning and interaction network analysis verify that although three drugs have structural difference, they share similar binding modes to the PR and common interaction clusters with the PR. The current findings also confirm that residues located interaction clusters, such as Asp25/Asp25', Gly27/Gly27', Ala28/Ala28', Asp29, Ile47/Ile47', Gly49/Gly49', Ile50/Ile50', Val82/Val82' and Ile84/Ile84, can be used as efficient targets of clinically available inhibitors towards the PR.

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.

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.

Accurate prediction of relative binding affinities of a series of HIV-1 protease inhibitors using semi-empirical quantum mechanical charge

A major challenge in computer-aided drug design is the accurate estimation of ligand binding affinity. Here, a new approach that combines the adaptive steered molecular dynamics (ASMD) and partial atomic charges calculated by semi-empirical quantum mechanics (SQMPC), namely ASMD-SQMPC, is suggested to predict the ligand binding affinities, with 24 HIV-1 protease inhibitors as testing examples. In the ASMD-SQMPC, the relative binding free energy (ΔG) is reflected by the average maximum potential of mean force (<PMF>_max ) between bound and unbound states. The correlation coefficient (R² ) between the <PMF>_max and experimentally determined ΔG is 0.86, showing a significant improvement compared with the conventional ASMD (R² = 0.52). Therefore, this study provides an efficient approach to predict the relative ΔG and reveals the significance of precise partial atomic charges in the theoretical simulations.

Novel radial distribution function approach in the study of point mutations: the HIV-1 protease case study

Background: Mutations are one of the engines of evolution. Under constant stress pressure, mutations can lead to the emergence of unwanted, drug-resistant entities. Methodology: The radial distribution function weighted by the number of valence shell electrons is used to design quantitative structure-activity relationship (QSAR) model relating descriptors with the inhibition constant for a series of wild-type HIV-1 protease inhibitor complexes. The residuals of complexes with mutant HIV-1 protease were correlated with the energy of the highest occupied molecular orbitals of the residues introduced to enzyme via point mutations. Conclusion: Successful identification of residues Ile3, Asp25, Val32 and Ile50 as the one whose substitution influences the inhibition constant the most, demonstrates the potential of the proposed methodology for the study of the effects of point mutations.

Performance of radial distribution function-based descriptors in the chemoinformatic studies of HIV-1 protease

Aim: This letter investigates the role of radial distribution function-based descriptors for in silico design of new drugs. Methodology: The multiple linear regression models for HIV-1 protease and its complexes with a series of inhibitors were constructed. A detailed analysis of major atomic contributions to the radial distribution function descriptor weighted by the number of valence shell electrons identified residues Arg8, Asp29 and residues of the catalytic triad as crucial for the correlation with the inhibition constant, together with residues Asp30 and Ile50, whose mutations are known to cause an emergence of drug resistant variants. Conclusion: This study demonstrates an easy and fast assessment of the activity of potential drugs and the derivation of structural information of their complexes with the receptor or enzyme.

Characterizing Protein-Ligand Binding Using Atomistic Simulation and Machine Learning: Application to Drug Resistance in HIV-1 Protease

Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have provided detailed insights into their function. Comparing the results of such simulations for a few closely related systems has guided our understanding of the mechanisms by which changes such as ligand binding or mutation can alter the function. The general problem of detecting and interpreting such mechanisms from simulations of many related systems, however, remains a challenge. This problem is addressed here by applying supervised and unsupervised machine learning techniques to a variety of thermodynamic observables extracted from molecular dynamics simulations of different systems. As an important test case, these methods are applied to understand the evasion by human immunodeficiency virus type-1 (HIV-1) protease of darunavir, a potent inhibitor to which resistance can develop via the simultaneous mutation of multiple amino acids. Complex mutational patterns have been observed among resistant strains, presenting a challenge to developing a mechanistic picture of resistance in the protease. In order to dissect these patterns and gain mechanistic insight into the role of specific mutations, molecular dynamics simulations were carried out on a collection of HIV-1 protease variants, chosen to include highly resistant strains and susceptible controls, in complex with darunavir. Using a machine learning approach that takes advantage of the hierarchical nature in the relationships among the sequence, structure, and function, an integrative analysis of these trajectories reveals key details of the resistance mechanism, including changes in the protein structure, hydrogen bonding, and protein-ligand contacts.

Effective estimation of the inhibitor affinity of HIV-1 protease via a modified LIE approach

The inhibition of the Human Immunodeficiency Virus Type 1 Protease (HIV-1 PR) can prevent the synthesis of new viruses. Computer-aided drug design (CADD) would enhance the discovery of new therapies, through which the estimation of ligand-binding affinity is critical to predict the most efficient inhibitor. A time-consuming binding free energy method would reduce the usefulness of CADD. The modified linear interaction energy (LIE) approach emerges as an appropriate protocol that performs this task. In particular, the polar interaction free energy, which is obtained via numerically resolving the linear Poisson–Boltzmann equation, plays as an important role in driving the binding mechanism of the HIV-1 PR + inhibitor complex. The electrostatic interaction energy contributes to the attraction between two molecules, but the vdW interaction acts as a repulsive factor between the ligand and the HIV-1 PR. Moreover, the ligands were found to adopt a very strong hydrophobic interaction with the HIV-1 PR. Furthermore, the results obtained corroborate the high accuracy and precision of computational studies with a large correlation coefficient value R = 0.83 and a small RMSE δ_RMSE = 1.25 kcal mol⁻¹. This method is less time-consuming than the other end-point methods, such as the molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) and free energy perturbation (FEP) approaches. Overall, the modified LIE approach would provide ligand-binding affinity with HIV-1 PR accurately, precisely, and rapidly, resulting in a more efficient design of new inhibitors.

The inhibition of the Human Immunodeficiency Virus Type 1 Protease (HIV-1 PR) can prevent the synthesis of new viruses.

Protease Inhibitors for the Treatment of HIV/AIDS: Recent Advances and Future Challenges

Acquired Immunodeficiency Syndrome (AIDS) is a chronic disease characterized by multiple life-threatening illnesses caused by a retro-virus, Human Immunodeficiency Virus (HIV). HIV infection slowly destroys the immune system and increases the risk of various other infections and diseases. Although, there is no immediate cure for HIV infection/AIDS, several drugs targeting various cruxes of HIV infection are used to slow down the progress of the disease and to boost the immune system. One of the key therapeutic strategies is Highly Active Antiretroviral Therapy (HAART) or ' AIDS cocktail' in a general sense, which is a customized combination of anti-retroviral drugs designed to combat the HIV infection. Since HAART's inception in 1995, this treatment was found to be effective in improving the life expectancy of HIV patients over two decades. Among various classes of HAART treatment regimen, Protease Inhibitors (PIs) are known to be widely used as a major component and found to be effective in treating HIV infection/AIDS. For the past several years, a variety of protease inhibitors have been reported. This review outlines the drug design strategies of PIs, chemical and pharmacological characteristics of some mechanism-based inhibitors, summarizes the recent developments in small molecule based drug discovery with HIV protease as a drug target. Further discussed are the pharmacology, PI drug resistance on HIV PR, adverse effects of HIV PIs and challenges/impediments in the successful application of HIV PIs as an important class of drugs in HAART regimen for the effective treatment of AIDS.

HIV-1 Protease Inhibitors Incorporating Stereochemically Defined P2' Ligands To Optimize Hydrogen Bonding in the Substrate Envelope

A structure-guided design strategy was used to improve the resistance profile of HIV-1 protease inhibitors by optimizing hydrogen bonding and van der Waals interactions with the protease while staying within the substrate envelope. Stereoisomers of 4-(1-hydroxyethyl)benzene and 4-(1,2-dihydroxyethyl)benzene moieties were explored as P2' ligands providing pairs of diastereoisomers epimeric at P2', which exhibited distinct potency profiles depending on the configuration of the hydroxyl group and size of the P1' group. While compounds with the 4-(1-hydroxyethyl)benzene P2' moiety maintained excellent antiviral potency against a panel of multidrug-resistant HIV-1 strains, analogues with the polar 4-(1,2-dihydroxyethyl)benzene moiety were less potent, and only the (R)-epimer incorporating a larger 2-ethylbutyl P1' group showed improved potency. Crystal structures of protease-inhibitor complexes revealed strong hydrogen bonding interactions of both (R)- and (S)-stereoisomers of the hydroxyethyl group with Asp30'. Notably, the (R)-dihydroxyethyl group was involved in a unique pattern of direct hydrogen bonding interactions with the backbone amides of Asp29' and Asp30'. The SAR data and analysis of crystal structures provide insights for optimizing these promising HIV-1 protease inhibitors.

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.

Exploring the conformational landscapes of HIV protease structural ensembles using principal component analysis

HIV protease, an essential enzyme for viral particle maturation, is an important drug target of HIV. Its structural conformation is a key determinant of both biological function as well as efficient binding of protease inhibitor molecules. In the present study we analyzed 471 crystal structures of HIV-1 protease to understand the conformational changes induced by mutations or binding of various ligands and substrates. We performed principal component analysis on the ensembles of the HIV-1 protease structures to explore the conformational landscapes. The study identified structural differences between drug resistant and drug sensitive protease structures. Conformational changes were identified in the A and B chains of homo-dimeric HIV protease structures having different combinations of mutations, and also rigidity in the binding conformation of HIV drugs within the active site of the protein.© 2018 Wiley Periodicals, Inc.

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.

Structural exploration of hydroxyethylamines as HIV-1 protease inhibitors: new features identified

The current study deals with chemometric modelling strategies (Naïve Bayes classification, hologram-based quantitative structure-activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA)) to explore the important features of hydroxylamine derivatives for exerting potent human immunodeficiency virus-1 (HIV-1) protease inhibition. Depending on the statistically validated reliable and robust quantitative structure-activity relationship (QSAR) models, important and crucial structural features have been identified that may be responsible for enhancing the activity profile of these hydroxylamine compounds. Arylsulfonamide function along with methoxy or fluoro substitution is important for enhancing activity. Bulky steric substitution at the sulfonamide nitrogen disfavours activity whereas smaller hydrophobic substitution at the same position is found to be favourable. Apart from the crucial oxazolidinone moiety, pyrrolidine, cyclic urea and methyl ester functions are also responsible for increasing the HIV-1 protease inhibitory profile. Observations derived from these modelling studies may be utilized further in designing promising HIV-1 protease inhibitors of this class.

Hydroxyethylamine derivatives as HIV-1 protease inhibitors: a predictive QSAR modelling study based on Monte Carlo optimization

Application of HIV-1 protease inhibitors (as an anti-HIV regimen) may serve as an attractive strategy for anti-HIV drug development. Several investigations suggest that there is a crucial need to develop a novel protease inhibitor with higher potency and reduced toxicity. Monte Carlo optimized QSAR study was performed on 200 hydroxyethylamine derivatives with antiprotease activity. Twenty-one QSAR models with good statistical qualities were developed from three different splits with various combinations of SMILES and GRAPH based descriptors. The best models from different splits were selected on the basis of statistically validated characteristics of the test set and have the following statistical parameters: r² = 0.806, Q² = 0.788 (split 1); r² = 0.842, Q² = 0.826 (split 2); r² = 0.774, Q² = 0.755 (split 3). The structural attributes obtained from the best models were analysed to understand the structural requirements of the selected series for HIV-1 protease inhibitory activity. On the basis of obtained structural attributes, 11 new compounds were designed, out of which five compounds were found to have better activity than the best active compound in the series.

Proteases and protease inhibitors in infectious diseases

There are numerous proteases of pathogenic organisms that are currently targeted for therapeutic intervention along with many that are seen as potential drug targets. This review discusses the chemical and biological makeup of some key druggable proteases expressed by the five major classes of disease causing agents, namely bacteria, viruses, fungi, eukaryotes, and prions. While a few of these enzymes including HIV protease and HCV NS3-4A protease have been targeted to a clinically useful level, a number are yet to yield any clinical outcomes in terms of antimicrobial therapy. A significant aspect of this review discusses the chemical and pharmacological characteristics of inhibitors of the various proteases discussed. A total of 25 inhibitors have been considered potent and safe enough to be trialed in humans and are at different levels of clinical application. We assess the mechanism of action and clinical performance of the protease inhibitors against infectious agents with their developmental strategies and look to the next frontiers in the use of protease inhibitors as anti-infective agents.

Computational membrane biophysics: From ion channel interactions with drugs to cellular function

The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

I36T↑T mutation in South African subtype C (C-SA) HIV-1 protease significantly alters protease-drug interactions

The efficacy of HIV-1 protease (PR) inhibition therapies is often compromised by the emergence of mutations in the PR molecule that reduces the binding affinity of inhibitors while maintaining viable catalytic activity and affinity for natural substrates. In the present study, we used a recombinant HIV-1 C-SA PR and a recently reported variant for inhibition (Ki, IC50) and thermodynamic studies against nine clinically used inhibitors. This is the first time that binding free energies for C-SA PR and the mutant are reported. This variant PR harbours a mutation and insertion (I36T↑T) at position 36 of the C-SA HIV-1 PR, and did not show a significant difference in the catalytic effect of the HIV-1 PR. However, the nine clinically approved HIV PR drugs used in this study demonstrated weaker inhibition and lower binding affinities toward the variant when compared to the wild type HIV-1 PR. All the protease inhibitors (PIs), except Amprenavir and Ritonavir exhibited a significant decrease in binding affinity (p<0.0001). Darunavir and Nelfinavir exhibited the weakest binding affinity, 155- and 95-fold decreases respectively, toward the variant. Vitality values for the variant PR, against the seven selected PIs, confirm the impact of the mutation and insertion on the South African HIV-1 subtype C PR. This information has important clinical implications for thousands of patients in Sub-Saharan Africa.

Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets

De novo design can be used to explore vast areas of chemical space in computational lead discovery. As a complement to virtual screening, from-scratch construction of molecules is not limited to compounds in pre-existing vendor catalogs. Here, we present an iterative fragment growth method, integrated into the program DOCK, in which new molecules are built using rules for allowable connections based on known molecules. The method leverages DOCK's advanced scoring and pruning approaches and users can define very specific criteria in terms of properties or features to customize growth toward a particular region of chemical space. The code was validated using three increasingly difficult classes of calculations: (1) Rebuilding known X-ray ligands taken from 663 complexes using only their component parts (focused libraries), (2) construction of new ligands in 57 drug target sites using a library derived from ∼13M drug-like compounds (generic libraries), and (3) application to a challenging protein-protein interface on the viral drug target HIVgp41. The computational testing confirms that the de novo DOCK routines are robust and working as envisioned, and the compelling results highlight the potential utility for designing new molecules against a wide variety of important protein targets. © 2017 Wiley Periodicals, Inc.

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.

Investigational protease inhibitors as antiretroviral therapies

INTRODUCTION

Highly Active Antiretroviral Therapy (HAART) has tremendously improved the life expectancy of the HIV-infected population over the past three decades. Protease inhibitors have been one of the major classes of drugs in HAART regimens that are effective in treating HIV. However, the emergence of resistance and cross-resistance against protease inhibitors encourages researchers to develop new PIs with broad-spectrum activity, as well as novel means of enhancing the efficacy of existing PIs.

AREAS COVERED

In this article we discuss recent advances in HIV protease inhibitor (PI) development, focusing on both investigational and experimental agents. We also include a section on pharmacokinetic booster drugs for improved bioavailability of protease inhibitors. Further, we discuss novel drug delivery systems using a variety of nanocarriers for the delivery of PIs across the blood-brain barrier to treat the HIV in the brain.

EXPERT OPINION

We discuss our opinion on the promises and challenges on the development of novel investigational and experimental PIs that are less toxic and more effective in combating drug-resistance. Further, we discuss the future of novel nanocarriers that have been developed to deliver PIs to the brain cells. Although these are promising findings, many challenges need to be overcome prior to making them a viable option.

Liquid phase oxidation chemistry in continuous-flow microreactors

This review gives an exhaustive overview of the engineering principles, safety aspects and chemistry associated with liquid phase oxidation in continuous-flow microreactors.

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.

Fluorogenic Assay for Inhibitors of HIV-1 Protease with Sub-picomolar Affinity

A fluorogenic substrate for HIV-1 protease was designed and used as the basis for a hypersensitive assay. The substrate exhibits a k_cat of 7.4 s⁻¹, K_M of 15 μM, and an increase in fluorescence intensity of 104-fold upon cleavage, thus providing sensitivity that is unmatched in a continuous assay of HIV-1 protease. These properties enabled the enzyme concentration in an activity assay to be reduced to 25 pM, which is close to the K_d value of the protease dimer. By fitting inhibition data to Morrison’s equation, K_i values of amprenavir, darunavir, and tipranavir were determined to be 135, 10, and 82 pM, respectively. This assay, which is capable of measuring K_i values as low as 0.25 pM, is well-suited for characterizing the next generation of HIV-1 protease inhibitors.

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.

Ametoctradin is a potent Qo site inhibitor of the mitochondrial respiration complex III

Ametoctradin is a new Oomycete-specific fungicide under development by BASF. It is a potent inhibitor of the bc1 complex in mitochondrial respiration. However, its detailed action mechanism remains unknown. In the present work, the binding mode of ametoctradin was first uncovered by integrating molecular docking, MD simulations, and MM/PBSA calculations, which showed that ametoctradin should be a Q(o) site inhibitor of bc1 complex. Subsequently, a series of new 1,2,4-triazolo[1,5-a]pyrimidine derivatives were designed and synthesized to further understand the substituent effects on the 5- and 6-position of 1,2,4-triazolo[1,5-a]pyrimidine. The calculated binding free energies (ΔG(cal)) of newly synthesized analogues as Qo site inhibitors correlated very well (R(2) = 0.96) with their experimental binding free energies (ΔG(exp)). Two compounds (4a and 4c) with higher inhibitory activity against porcine SQR than ametoctradin were successfully identified. The structural and mechanistic insights obtained from the present study will provide a valuable clue for future designing of a new promising bc1 inhibitor.

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.

The triple threat of HIV-1 protease inhibitors

Newly released human immunodeficiency virus type 1 (HIV-1) particles obligatorily undergo a maturation process to become infectious. The HIV-1 protease (PR) initiates this step, catalyzing the cleavage of the Gag and Gag-Pro-Pol structural polyproteins. Proper organization of the mature virus core requires that cleavage of these polyprotein substrates proceeds in a highly regulated, specific series of events. The vital role the HIV-1 PR plays in the viral life cycle has made it an extremely attractive target for inhibition and has accordingly fostered the development of a number of highly potent substrate-analog inhibitors. Though the PR inhibitors (PIs) inhibit only the HIV-1 PR, their effects manifest at multiple different stages in the life cycle due to the critical importance of the PR in preparing the virus for these subsequent events. Effectively, PIs masquerade as entry inhibitors, reverse transcription inhibitors, and potentially even inhibitors of post-reverse transcription steps. In this chapter, we review the triple threat of PIs: the intermolecular cooperativity in the form of a cooperative dose-response for inhibition in which the apparent potency increases with increasing inhibition; the pleiotropic effects of HIV-1 PR inhibition on entry, reverse transcription, and post-reverse transcription steps; and their potency as transition state analogs that have the potential for further improvement that could lead to an inability of the virus to evolve resistance in the context of single drug therapy.

Systematic molecular dynamics, MM-PBSA, and ab initio approaches to the saquinavir resistance mechanism in HIV-1 PR due to 11 double and multiple mutations

Mutations in the human immunodeficiency virus (HIV) enable virus replication even when appropriate antiretroviral therapy is followed, thus leading to the emergence of drug resistance. In a previous work, we systematically examined seven single mutations that are associated with saquinavir (SQV) resistance in HIV-1 protease (Tzoupis, H.; Leonis, G.; Mavromoustakos, T.; Papadopoulos, M. G. J. Chem. Theory Comput. 2013, 9, 1754-1764). Herein, we extend our analysis, which includes seven double (G48V-V82A, L10I-G48V, G48V-L90M, I84V-L90M, L10I-V82A, L10I-L63P, A71V-G73S) and four multiple (L10I-L63P-A71V, L10I-G48V-V82A, G73S-I84V-L90M, L10I-L63P-A71V-G73S-I84V-L90M) SQV-HIV-1 PR mutant complexes, in an attempt to generalize our findings and formulate the main elements of the SQV resistance mechanism in the protease. On the basis of molecular dynamics (MD), molecular mechanics Poisson-Boltzmann surface area (MM-PBSA), and ab initio computational approaches, we identified specific features that constitute the HIV-1 PR mechanism of resistance at the molecular level: the low flexibility of SQV in the binding cavity and the preservation of hydrogen bonding (HB) and van der Waals interactions between SQV and several active-site (Gly27/27', Asp29/29'/30/30', especially Asp25/25') and flap (Ile50/50', Gly48/48') residues of the protease contribute significantly to efficient binding. The total enthalpy loss in all mutants is mostly due to the loss in enthalpy of the active-site region. Furthermore, it was observed that mutation accumulation may induce stabilization to SQV and to the flaps through enhanced HB interactions that lead to improved inhibition (e.g., accumulation of mutations in complexes containing L10I, G48V, L63P, I84V, or L90M single mutations). It was also concluded that permanent flap closure is obtained independently of mutations and SQV binding is mostly driven by van der Waals, nonpolar, and exchange-energy contributions. Importantly, it was indicated that the optimal positioning of SQV and the structure of the binding cavity are tightly coupled, since small changes in geometry may affect the binding energy greatly. The results of our theoretical approaches are in agreement with experimental evidence and provide a reliable description of SQV resistance in HIV-1 PR.

Drug Resistance Mutations Alter Dynamics of Inhibitor-Bound HIV-1 Protease

Under the selective pressure of therapy, HIV-1 protease mutants resistant to inhibitors evolve to confer drug resistance. Such mutations can impact both the dynamics and structures of the bound and unbound forms of the enzyme. Flap+ is a multidrug-resistant variant of HIV-1 protease with a combination of primary and secondary resistance mutations (L10I, G48V, I54V, V82A) and a strikingly altered thermodynamic profile for darunavir (DRV) binding relative to the wild-type protease. We elucidated the impact of these mutations on protein dynamics in the DRV-bound state using molecular dynamics simulations and NMR relaxation experiments. Both methods concur in that the conformational ensemble and dynamics of protease are impacted by the drug resistance mutations in Flap+ variant. Surprisingly this change in ensemble dynamics is different from that observed in the unliganded form of the same variant (Cai, Y. et al. J. Chem. Theory Comput.2012, 8, 3452–3462). Our comparative analysis of both inhibitor-free and bound states presents a comprehensive picture of the altered dynamics in drug-resistant mutant HIV-1 protease and underlies the importance of incorporating dynamic analysis of the whole system, including the unliganded state, into revealing drug resistance mechanisms.

Intracellular antiviral activity of low-dose ritonavir in boosted protease inhibitor regimens

Protease inhibitors are largely used for the treatment of HIV infection in combination with other antiretroviral drugs. Their improved pharmacokinetic profiles can be achieved through the concomitant administration of low doses of ritonavir (RTV), a protease inhibitor currently used as a booster, increasing the exposure of companion drugs. Since ritonavir-boosted regimens are associated with long-term adverse events, cobicistat, a CYP3A4 inhibitor without antiviral activity, has been developed. Recently, high intracellular concentrations of ritonavir in lymphocytes and monocytes were reported even when ritonavir was administered at low doses, so we aimed to compare its theoretical antiviral activity with those of the associated protease inhibitors. Intracellular concentrations of ritonavir and different protease inhibitors were determined through the same method. Inhibitory constants were obtained from the literature. The study enrolled 103 patients receiving different boosted protease inhibitors, darunavir-ritonavir 600 and 100 mg twice daily and 800 and 100 mg once daily (n = 22 and 4, respectively), atazanavir-ritonavir 300 and 100 mg once daily (n = 40), lopinavir-ritonavir 400 and 100 mg twice daily (n = 21), or tipranavir-ritonavir 500 and 200 mg twice daily (n = 16). According to the observed concentrations, we calculated the ratios between the intracellular concentrations of ritonavir and those of the companion protease inhibitor and between the theoretical viral protease reaction speeds with each drug, with and without ritonavir. The median ratios were 4.04 and 0.63 for darunavir-ritonavir twice daily, 2.49 and 0.74 for darunavir-ritonavir once daily, 0.42 and 0.74 for atazanavir-ritonavir, 0.57 and 0.95 for lopinavir-ritonavir, and 0.19 and 0.84 for tipranavir-ritonavir, respectively. Therefore, the antiviral effect of ritonavir was less than that of the concomitant protease inhibitors but, importantly, mostly with darunavir. Thus, further in vitro and in vivo studies of the RTV antiviral effect are warranted.

Protein side-chain modeling with a protein-dependent optimized rotamer library

Despite years of effort, the problem of predicting the conformations of protein side chains remains a subject of inquiry. This problem has three major issues, namely defining the conformations that a side chain may adopt within a protein, developing a sampling procedure for generating possible side-chain packings, and defining a scoring function that can rank these possible packings. To solve the former of these issues, most procedures rely on a rotamer library derived from databases of known protein structures. We introduce an alternative method that is free of statistics. We begin with a rotamer library that is based only on stereochemical considerations; this rotamer library is then optimized independently for each protein under study. We show that this optimization step restores the diversity of conformations observed in native proteins. We combine this protein-dependent rotamer library (PDRL) method with the self-consistent mean field (SCMF) sampling approach and a physics-based scoring function into a new side-chain prediction method, SCMF-PDRL. Using two large test sets of 831 and 378 proteins, respectively, we show that this new method compares favorably with competing methods such as SCAP, OPUS-Rota, and SCWRL4 for energy-minimized structures.

Improving the Resistance Profile of Hepatitis C NS3/4A Inhibitors: Dynamic Substrate Envelope Guided Design

Drug resistance is a principal concern in the treatment of quickly evolving diseases. The viral protease NS3/4A is a primary drug target for the hepatitis C virus (HCV) and is known to evolve resistance mutations in response to drug therapy. At the molecular level, drug resistance reflects a subtle change in the balance of molecular recognition by NS3/4A; the drug resistant protease variants are no longer effectively inhibited by the competitive active site inhibitors but can still process the natural substrates with enough efficiency for viral survival. In previous works we have developed the "substrate envelope" hypothesis, which posits that inhibitors should be less susceptible to drug resistance if they better mimic the natural substrate molecular recognition features. In this work, we perform molecular dynamics simulations on four native substrates bound to NS3/4A and discover a clearly conserved dynamic substrate envelope. We show that the most severe drug resistance mutations in NS3/4A occur at residues that are outside the substrate envelope. Comparative analysis of three NS3/4A inhibitors reveals structural and dynamic characteristics of inhibitors that could lead to resistance. We also suggest inhibitor modifications to improve resistance profiles based on the dynamic substrate envelope. This study provides a general framework for guiding the development of novel inhibitors that will be more robust against resistance by mimicking the static and dynamic binding characteristics of natural substrates.

Testing the substrate-envelope hypothesis with designed pairs of compounds

Acquired resistance to therapeutic agents is a significant barrier to the development of clinically effective treatments for diseases in which evolution occurs on clinical time scales, frequently arising from target mutations. We previously reported a general strategy to design effective inhibitors for rapidly mutating enzyme targets, which we demonstrated for HIV-1 protease inhibition [Altman et al. J. Am. Chem. Soc. 2008, 130, 6099–6113]. Specifically, we developed a computational inverse design procedure with the added constraint that designed inhibitors bind entirely inside the substrate envelope, a consensus volume occupied by natural substrates. The rationale for the substrate-envelope constraint is that it prevents designed inhibitors from making interactions beyond those required by substrates and thus limits the availability of mutations tolerated by substrates but not by designed inhibitors. The strategy resulted in subnanomolar inhibitors that bind robustly across a clinically derived panel of drug-resistant variants. To further test the substrate-envelope hypothesis, here we have designed, synthesized, and assayed derivatives of our original compounds that are larger and extend outside the substrate envelope. Our designs resulted in pairs of compounds that are very similar to one another, but one respects and one violates the substrate envelope. The envelope-respecting inhibitor demonstrates robust binding across a panel of drug-resistant protease variants, whereas the envelope-violating one binds tightly to wild type but loses affinity to at least one variant. This study provides strong support for the substrate-envelope hypothesis as a design strategy for inhibitors that reduce susceptibility to resistance mutations.

Fitness trade-offs restrict the evolution of resistance to amphotericin B

The rarity of clinical drug resistance to the antifungal amphotericin B is explained by the extreme costs that resistance mutations impose upon stress responses and virulence factors.

The evolution of drug resistance in microbial pathogens provides a paradigm for investigating evolutionary dynamics with important consequences for human health. Candida albicans, the leading fungal pathogen of humans, rapidly evolves resistance to two major antifungal classes, the triazoles and echinocandins. In contrast, resistance to the third major antifungal used in the clinic, amphotericin B (AmB), remains extremely rare despite 50 years of use as monotherapy. We sought to understand this long-standing evolutionary puzzle. We used whole genome sequencing of rare AmB-resistant clinical isolates as well as laboratory-evolved strains to identify and investigate mutations that confer AmB resistance in vitro. Resistance to AmB came at a great cost. Mutations that conferred resistance simultaneously created diverse stresses that required high levels of the molecular chaperone Hsp90 for survival, even in the absence of AmB. This requirement stemmed from severe internal stresses caused by the mutations, which drastically diminished tolerance to external stresses from the host. AmB-resistant mutants were hypersensitive to oxidative stress, febrile temperatures, and killing by neutrophils and also had defects in filamentation and tissue invasion. These strains were avirulent in a mouse infection model. Thus, the costs of evolving resistance to AmB limit the emergence of this phenotype in the clinic. Our work provides a vivid example of the ways in which conflicting selective pressures shape evolutionary trajectories and illustrates another mechanism by which the Hsp90 buffer potentiates the emergence of new phenotypes. Developing antibiotics that deliberately create such evolutionary constraints might offer a strategy for limiting the rapid emergence of drug resistance.

The evolution of drug resistance in human pathogens is considered an inevitable consequence of the selective pressures imposed by antimicrobial drugs. Yet resistance to one antifungal drug, amphotericin B (AmB), remains extremely rare despite decades of widespread use. Here we explore the biological mechanisms underlying this conundrum. By examining natural and experimental populations of Candida albicans, we identify multiple mutations that confer resistance to AmB in vitro. As with the evolution of resistance to other antifungals, we find that the chaperone protein Hsp90 is involved in enabling the evolution of resistance to AmB. We also discover, however, that mutations that confer AmB resistance impose massive costs on other aspects of fungal pathogenicity; strains that are resistant to AmB are hypersensitive to attack by the host immune system and are unable to invade and damage host tissue. Thus, the evolution of resistance to AmB is restricted by a tradeoff between tolerance of the drug and the ability to cause disease. We propose that developing new antibiotics for which resistance presents such dire tradeoffs may be a promising strategy to prevent the evolution of resistance.