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 basis and distal effects of Gag substrate coevolution in drug resistance to HIV-1 protease.

Drug resistance mutations in response to HIV-1 protease inhibitors are selected not only in the drug target but elsewhere in the viral genome, especially at the protease cleavage sites in the precursor protein Gag. To understand the molecular basis of this protease-substrate coevolution, we solved the crystal structures of drug resistant I50V/A71V HIV-1 protease with p1-p6 substrates bearing coevolved mutations. Analyses of the protease-substrate interactions reveal that compensatory coevolved mutations in the substrate do not restore interactions lost due to protease mutations, but instead establish other interactions that are not restricted to the site of mutation. Mutation of a substrate residue has distal effects on other residues' interactions as well, including through the induction of a conformational change in the protease. Additionally, molecular dynamics simulations suggest that restoration of active site dynamics is an additional constraint in the selection of coevolved mutations. Hence, protease-substrate coevolution permits mutational, structural, and dynamic changes via molecular mechanisms that involve distal effects contributing to drug resistance.

HIV-1 protease-substrate coevolution in nelfinavir resistance.

UNLABELLED: Resistance to various human immunodeficiency virus type 1 (HIV-1) protease inhibitors (PIs) challenges the effectiveness of therapies in treating HIV-1-infected individuals and AIDS patients. The virus accumulates mutations within the protease (PR) that render the PIs less potent. Occasionally, Gag sequences also coevolve with mutations at PR cleavage sites contributing to drug resistance. In this study, we investigated the structural basis of coevolution of the p1-p6 cleavage site with the nelfinavir (NFV) resistance D30N/N88D protease mutations by determining crystal structures of wild-type and NFV-resistant HIV-1 protease in complex with p1-p6 substrate peptide variants with L449F and/or S451N. Alterations of residue 30's interaction with the substrate are compensated by the coevolving L449F and S451N cleavage site mutations. This interdependency in the PR-p1-p6 interactions enhances intermolecular contacts and reinforces the overall fit of the substrate within the substrate envelope, likely enabling coevolution to sustain substrate recognition and cleavage in the presence of PR resistance mutations. IMPORTANCE: Resistance to human immunodeficiency virus type 1 (HIV-1) protease inhibitors challenges the effectiveness of therapies in treating HIV-1-infected individuals and AIDS patients. Mutations in HIV-1 protease selected under the pressure of protease inhibitors render the inhibitors less potent. Occasionally, Gag sequences also mutate and coevolve with protease, contributing to maintenance of viral fitness and to drug resistance. In this study, we investigated the structural basis of coevolution at the Gag p1-p6 cleavage site with the nelfinavir (NFV) resistance D30N/N88D protease mutations. Our structural analysis reveals the interdependency of protease-substrate interactions and how coevolution may restore substrate recognition and cleavage in the presence of protease drug resistance mutations.

The molecular basis of drug resistance against hepatitis C virus NS3/4A protease inhibitors.

Hepatitis C virus (HCV) infects over 170 million people worldwide and is the leading cause of chronic liver diseases, including cirrhosis, liver failure, and liver cancer. Available antiviral therapies cause severe side effects and are effective only for a subset of patients, though treatment outcomes have recently been improved by the combination therapy now including boceprevir and telaprevir, which inhibit the viral NS3/4A protease. Despite extensive efforts to develop more potent next-generation protease inhibitors, however, the long-term efficacy of this drug class is challenged by the rapid emergence of resistance. Single-site mutations at protease residues R155, A156 and D168 confer resistance to nearly all inhibitors in clinical development. Thus, developing the next-generation of drugs that retain activity against a broader spectrum of resistant viral variants requires a comprehensive understanding of the molecular basis of drug resistance. In this study, 16 high-resolution crystal structures of four representative protease inhibitors--telaprevir, danoprevir, vaniprevir and MK-5172--in complex with the wild-type protease and three major drug-resistant variants R155K, A156T and D168A, reveal unique molecular underpinnings of resistance to each drug. The drugs exhibit differential susceptibilities to these protease variants in both enzymatic and antiviral assays. Telaprevir, danoprevir and vaniprevir interact directly with sites that confer resistance upon mutation, while MK-5172 interacts in a unique conformation with the catalytic triad. This novel mode of MK-5172 binding explains its retained potency against two multi-drug-resistant variants, R155K and D168A. These findings define the molecular basis of HCV N3/4A protease inhibitor resistance and provide potential strategies for designing robust therapies against this rapidly evolving virus.

Machine Learning ADME Models in Practice: Four Guidelines from a Successful Lead Optimization Case Study.

Optimization of the ADME properties and pharmacokinetic (PK) profile of compounds is one of the critical activities in any medicinal chemistry campaign to discover a future clinical candidate. Finding ways to expedite the process to address ADME/PK shortcomings and reduce the number of compounds to synthesize is highly valuable. This article provides practical guidelines and a case study on the use of ML ADME models to guide compound design in small molecule lead optimization. These guidelines highlight that ML models cannot have an impact in a vacuum: they help advance a program when they have the trust of users, are tuned to the needs of the program, and are integrated into decision-making processes in a way that complements and augments the expertise of chemists.

The Pan-RAF-MEK Nondegrading Molecular Glue NST-628 Is a Potent and Brain-Penetrant Inhibitor of the RAS-MAPK Pathway with Activity across Diverse RAS- and RAF-Driven Cancers.

Alterations in the RAS-MAPK signaling cascade are common across multiple solid tumor types and are a driver for many cancers. NST-628 is a potent pan-RAF-MEK molecular glue that prevents the phosphorylation and activation of MEK by RAF, overcoming the limitations of traditional RAS-MAPK inhibitors and leading to deep durable inhibition of the pathway. Cellular, biochemical, and structural analyses of RAF-MEK complexes show that NST-628 engages all isoforms of RAF and prevents the formation of BRAF-CRAF heterodimers, a differentiated mechanism from all current RAF inhibitors. With a potent and durable inhibition of the RAF-MEK signaling complex as well as high intrinsic permeability into the brain, NST-628 demonstrates broad efficacy in cellular and patient-derived tumor models harboring diverse MAPK pathway alterations, including orthotopic intracranial models. Given its functional and pharmacokinetic mechanisms that are differentiated from previous therapies, NST-628 is positioned to make an impact clinically in areas of unmet patient need. Significance: This study introduces NST-628, a molecular glue having differentiated mechanism and drug-like properties. NST-628 treatment leads to broad efficacy with high tolerability and central nervous system activity across multiple RAS- and RAF-driven tumor models. NST-628 has the potential to provide transformative clinical benefits as both monotherapy and vertical combination anchor.

Context surrounding processing sites is crucial in determining cleavage rate of a subset of processing sites in HIV-1 Gag and Gag-Pro-Pol polyprotein precursors by viral protease.

Processing of the human immunodeficiency virus type 1 (HIV-1) Gag and Gag-Pro-Pol polyproteins by the HIV-1 protease (PR) is essential for the production of infectious particles. However, the determinants governing the rates of processing of these substrates are not clearly understood. We studied the effect of substrate context on processing by utilizing a novel protease assay in which a substrate containing HIV-1 matrix (MA) and the N-terminal domain of capsid (CA) is labeled with a FlAsH (fluorescein arsenical hairpin) reagent. When the seven cleavage sites within the Gag and Gag-Pro-Pol polyproteins were placed at the MA/CA site, the rates of cleavage changed dramatically compared with that of the cognate sites in the natural context reported previously. The rate of processing was affected the most for three sites: CA/spacer peptide 1 (SP1) (≈10-fold increase), SP1/nucleocapsid (NC) (≈10-30-fold decrease), and SP2/p6 (≈30-fold decrease). One of two multidrug-resistant (MDR) PR variants altered the pattern of processing rates significantly. Cleavage sites within the Pro-Pol region were cleaved in a context-independent manner, suggesting for these sites that the sequence itself was the determinant of rate. In addition, a chimera consisting of SP1/NC P4-P1 and MA/CA P1'-P4' residues (ATIM↓PIVQ) abolished processing by wild type and MDR proteases, and the reciprocal chimera consisting of MA/CA P4-P1 and SP1/NC P1'-4' (SQNY↓IQKG) was cleaved only by one of the MDR proteases. These results suggest that complex substrate interactions both beyond the active site of the enzyme and across the scissile bond contribute to defining the rate of processing by the HIV-1 PR.

Discovery of BLU-945, a Reversible, Potent, and Wild-Type-Sparing Next-Generation EGFR Mutant Inhibitor for Treatment-Resistant Non-Small-Cell Lung Cancer.

While epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have changed the treatment landscape for EGFR mutant (L858R and ex19del)-driven non-small-cell lung cancer (NSCLC), most patients will eventually develop resistance to TKIs. In the case of first- and second-generation TKIs, up to 60% of patients will develop an EGFR T790M mutation, while third-generation irreversible TKIs, like osimertinib, lead to C797S as the primary on-target resistance mutation. The development of reversible inhibitors of these resistance mutants is often hampered by poor selectivity against wild-type EGFR, resulting in potentially dose-limiting toxicities and a sub-optimal profile for use in combinations. BLU-945 (compound 30) is a potent, reversible, wild-type-sparing inhibitor of EGFR+/T790M and EGFR+/T790M/C797S resistance mutants that maintains activity against the sensitizing mutations, especially L858R. Pre-clinical efficacy and safety studies supported progression of BLU-945 into clinical studies, and it is currently in phase 1/2 clinical trials for treatment-resistant EGFR-driven NSCLC.

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

Drug resistance mutations in HIV-1 protease selectively alter inhibitor binding without significantly affecting substrate recognition and cleavage. This alteration in molecular recognition led us to develop the substrate-envelope hypothesis which predicts that HIV-1 protease inhibitors that fit within the overlapping consensus volume of the substrates are less likely to be susceptible to drug-resistant mutations, as a mutation impacting such inhibitors would simultaneously impact the processing of substrates. To evaluate this hypothesis, over 130 HIV-1 protease inhibitors were designed and synthesized using three different approaches with and without substrate-envelope constraints. A subset of 16 representative inhibitors with binding affinities to wild-type protease ranging from 58 nM to 0.8 pM was chosen for crystallographic analysis. The inhibitor-protease complexes revealed that tightly binding inhibitors (at the picomolar level of affinity) appear to "lock" into the protease active site by forming hydrogen bonds to particular active-site residues. Both this hydrogen bonding pattern and subtle variations in protein-ligand van der Waals interactions distinguish nanomolar from picomolar inhibitors. In general, inhibitors that fit within the substrate envelope, regardless of whether they are picomolar or nanomolar, have flatter profiles with respect to drug-resistant protease variants than inhibitors that protrude beyond the substrate envelope; this provides a strong rationale for incorporating substrate-envelope constraints into structure-based design strategies to develop new HIV-1 protease inhibitors.

Machine learning integration for predicting the effect of single amino acid substitutions on protein stability.

BACKGROUND: Computational prediction of protein stability change due to single-site amino acid substitutions is of interest in protein design and analysis. We consider the following four ways to improve the performance of the currently available predictors: (1) We include additional sequence- and structure-based features, namely, the amino acid substitution likelihoods, the equilibrium fluctuations of the alpha- and beta-carbon atoms, and the packing density. (2) By implementing different machine learning integration approaches, we combine information from different features or representations. (3) We compare classification vs. regression methods to predict the sign vs. the output of stability change. (4) We allow a reject option for doubtful cases where the risk of misclassification is high. RESULTS: We investigate three different approaches: early, intermediate and late integration, which respectively combine features, kernels over feature subsets, and decisions. We perform simulations on two data sets: (1) S1615 is used in previous studies, (2) S2783 is the updated version (as of July 2, 2009) extracted also from ProTherm. For S1615 data set, our highest accuracy using both sequence and structure information is 0.842 on cross-validation and 0.904 on testing using early integration. Newly added features, namely, local compositional packing and the mobility extent of the mutated residues, improve accuracy significantly with intermediate integration. For S2783 data set, we also train regression methods to estimate not only the sign but also the amount of stability change and apply risk-based classification to reject when the learner has low confidence and the loss of misclassification is high. The highest accuracy is 0.835 on cross-validation and 0.832 on testing using only sequence information. The percentage of false positives can be decreased to less than 0.005 by rejecting 10 per cent using late integration. CONCLUSION: We find that in both early and late integration, combining inputs or decisions is useful in increasing accuracy. Intermediate integration allows assessing the contributions of individual features by looking at the assigned weights. Overall accuracy of regression is not better than that of classification but it has less false positives, especially when combined with the reject option. The server for stability prediction for three integration approaches and the data sets are available at http://www.prc.boun.edu.tr/appserv/prc/mlsta.

Selectively Modulating Conformational States of USP7 Catalytic Domain for Activation.

Ubiquitin-specific protease 7 (USP7) deubiquitinase activity is controlled by a number of regulatory factors, including stimulation by intramolecular accessory domains. Alone, the USP7 catalytic domain (USP7cd) shows limited activity and apo USP7cd crystal structures reveal a disrupted catalytic triad. By contrast, ubiquitin-conjugated USP7cd structures demonstrate the canonical cysteine protease active-site geometry; however, the structural features of the USP7cd that stabilize the inactive conformation and the mechanism of transition between inactive and active states remain unclear. Here we use comparative structural analyses, molecular dynamics simulations, and in silico sequence re-engineering via directed sampling by RosettaDesign to identify key molecular determinants of USP7cd activation and successfully engineer USP7cd for improved activity. Full kinetic analysis and multiple X-ray crystal structures of our designs indicate that electrostatic interactions in the distal "switching loop" region and local packing in the hydrophobic core mediate subtle but significant conformational changes that modulate USP7cd activation.

Clusters of isoleucine, leucine, and valine side chains define cores of stability in high-energy states of globular proteins: Sequence determinants of structure and stability.

Measurements of protection against exchange of main chain amide hydrogens (NH) with solvent hydrogens in globular proteins have provided remarkable insights into the structures of rare high-energy states that populate their folding free-energy surfaces. Lacking, however, has been a unifying theory that rationalizes these high-energy states in terms of the structures and sequences of their resident proteins. The Branched Aliphatic Side Chain (BASiC) hypothesis has been developed to explain the observed patterns of protection in a pair of TIM barrel proteins. This hypothesis supposes that the side chains of isoleucine, leucine, and valine (ILV) residues often form large hydrophobic clusters that very effectively impede the penetration of water to their underlying hydrogen bond networks and, thereby, enhance the protection against solvent exchange. The linkage between the secondary and tertiary structures enables these ILV clusters to serve as cores of stability in high-energy partially folded states. Statistically significant correlations between the locations of large ILV clusters in native conformations and strong protection against exchange for a variety of motifs reported in the literature support the generality of the BASiC hypothesis. The results also illustrate the necessity to elaborate this simple hypothesis to account for the roles of adjacent hydrocarbon moieties in defining stability cores of partially folded states along folding reaction coordinates.

Molecular Basis for Differential Patterns of Drug Resistance in Influenza N1 and N2 Neuraminidase.

Neuraminidase (NA) inhibitors are used for the prevention and treatment of influenza A virus infections. Two subtypes of NA, N1 and N2, predominate in viruses that infect humans, but differential patterns of drug resistance have emerged in each subtype despite highly homologous active sites. To understand the molecular basis for the selection of these drug resistance mutations, structural and dynamic analyses on complexes of N1 and N2 NA with substrates and inhibitors were performed. Comparison of dynamic substrate and inhibitor envelopes and interactions at the active site revealed how differential patterns of drug resistance have emerged for specific drug resistance mutations, at residues I222, S246, and H274 in N1 and E119 in N2. Our results show that the differences in intermolecular interactions, especially van der Waals contacts, of the inhibitors versus substrates at the NA active site effectively explain the selection of resistance mutations in the two subtypes. Avoiding such contacts that render inhibitors vulnerable to resistance by better mimicking the dynamics and intermolecular interactions of substrates can lead to the development of novel inhibitors that avoid drug resistance in both subtypes.

Activation Mechanism of Oncogenic Deletion Mutations in BRAF, EGFR, and HER2.

Activating mutations in protein kinases drive many cancers. While how recurring point mutations affect kinase activity has been described, the effect of in-frame deletions is not well understood. We show that oncogenic deletions within the ß3-αC loop of HER2 and BRAF are analogous to the recurrent EGFR exon 19 deletions. We identify pancreatic carcinomas with BRAF deletions mutually exclusive with KRAS mutations. Crystal structures of BRAF deletions reveal the truncated loop restrains αC in an active "in" conformation, imparting resistance to inhibitors like vemurafenib that bind the αC "out" conformation. Characterization of loop length explains the prevalence of five amino acid deletions in BRAF, EGFR, and HER2 and highlights the importance of this region for kinase activity and inhibitor efficacy.

Drug-resistant HIV-1 protease regains functional dynamics through cleavage site coevolution.

Drug resistance is caused by mutations that change the balance of recognition favoring substrate cleavage over inhibitor binding. Here, a structural dynamics perspective of the regained wild-type functioning in mutant HIV-1 proteases with coevolution of the natural substrates is provided. The collective dynamics of mutant structures of the protease bound to p1-p6 and NC-p1 substrates are assessed using the Anisotropic Network Model (ANM). The drug-induced protease mutations perturb the mechanistically crucial hinge axes that involve key sites for substrate binding and dimerization and mainly coordinate the intrinsic dynamics. Yet with substrate coevolution, while the wild-type dynamic behavior is restored in both p1-p6 ((LP) (1'F)p1-p6D30N/N88D) and NC-p1 ((AP) (2) (V)NC-p1V82A) bound proteases, the dynamic behavior of the NC-p1 bound protease variants (NC-p1V82A and (AP) (2) (V)NC-p1V82A) rather resemble those of the proteases bound to the other substrates, which is consistent with experimental studies. The orientational variations of residue fluctuations along the hinge axes in mutant structures justify the existence of coevolution in p1-p6 and NC-p1 substrates, that is, the dynamic behavior of hinge residues should contribute to the interdependent nature of substrate recognition. Overall, this study aids in the understanding of the structural dynamics basis of drug resistance and evolutionary optimization in the HIV-1 protease system.

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.

Evaluating the role of macrocycles in the susceptibility of hepatitis C virus NS3/4A protease inhibitors to drug resistance.

The hepatitis C virus (HCV) infects an estimated 150 million people worldwide and is the major cause of viral hepatitis, cirrhosis, and liver cancer. The available antiviral therapies, which include PEGylated interferon, ribavirin, and one of the HCV NS3/4A protease inhibitors telaprevir or boceprevir, are ineffective for some patients and cause severe side effects. More potent NS3/4A protease inhibitors are in clinical development, but the long-term effectiveness of these drugs is challenged by the development of drug resistance. Here, we investigated the role of macrocycles in the susceptibility of NS3/4A protease inhibitors to drug resistance in asunaprevir, danoprevir, vaniprevir, and MK-5172, with similar core structures but varied P2 moieties and macrocyclizations. Linear and macrocyclic analogues of these drugs were designed, synthesized, and tested against wild-type and drug-resistant variants R155K, V36M/R155K, A156T, and D168A in enzymatic and antiviral assays. Macrocyclic inhibitors were generally more potent, but the location of the macrocycle was critical for retaining activity against drug-resistant variants: the P1-P3 macrocyclic inhibitors were less susceptible to drug resistance than the linear and P2-P4 macrocyclic analogues. In addition, the heterocyclic moiety at P2 largely determined the inhibitor resistance profile, susceptibility to drug resistance, and the extent of modulation by the helicase domain. Our findings suggest that to design robust inhibitors that retain potency to drug-resistant NS3/4A protease variants, inhibitors should combine P1-P3 macrocycles with flexible P2 moieties that optimally contact with the invariable catalytic triad of this enzyme.

HIV-1 Protease and Substrate Coevolution Validates the Substrate Envelope As the Substrate Recognition Pattern.

Drug resistance of HIV-1 protease alters the balance in the molecular recognition events in favor of substrate processing versus inhibitor binding. To develop robust inhibitors targeting ensembles of drug-resistant variants, the code of this balance needs to be cracked. For this purpose, the principles governing the substrate recognition are required to be revealed. Previous crystallographic studies on the WT protease-substrate complexes showed that the substrates have a conserved consensus volume in the protease active site despite their low sequence homology. This consensus volume is termed as the substrate envelope. The substrate envelope was recently reevaluated by taking the substrate dynamics into account, and the dynamic substrate envelope was reported to better define the substrate specificity for HIV-1 protease. Drug resistance occurs mostly through mutations in the protease, occasionally accompanied by cleavage site mutations. In this study, three coevolved protease-substrate complexes (AP2VNC-p1V82A, LP1'Fp1-p6D30N/N88D, and SP3'Np1-p6D30N/N88D) were investigated for structural and dynamic properties by molecular modeling and dynamics simulations. The results show the substrate envelope is preserved by these cleavage site mutations in the presence of drug-resistance mutations in the protease, if not enhanced. This study on the conformational and mutational ensembles of protease-substrate complexes validates the substrate envelope as the substrate recognition motif for HIV-1 protease. The substrate envelope hypothesis allows for the elucidation of possible drug resistance mutation patterns in the polyprotein cleavage sites.

Extreme entropy-enthalpy compensation in a drug-resistant variant of HIV-1 protease.

The development of HIV-1 protease inhibitors has been the historic paradigm of rational structure-based drug design, where structural and thermodynamic analyses have assisted in the discovery of novel inhibitors. While the total enthalpy and entropy change upon binding determine the affinity, often the thermodynamics are considered in terms of inhibitor properties only. In the current study, profound changes are observed in the binding thermodynamics of a drug-resistant variant compared to wild-type HIV-1 protease, irrespective of the inhibitor bound. This variant (Flap+) has a combination of flap and active site mutations and exhibits extremely large entropy-enthalpy compensation compared to wild-type protease, 5-15 kcal/mol, while losing only 1-3 kcal/mol in total binding free energy for any of six FDA-approved inhibitors. Although entropy-enthalpy compensation has been previously observed for a variety of systems, never have changes of this magnitude been reported. The co-crystal structures of Flap+ protease with four of the inhibitors were determined and compared with complexes of both the wild-type protease and another drug-resistant variant that does not exhibit this energetic compensation. Structural changes conserved across the Flap+ complexes, which are more pronounced for the flaps covering the active site, likely contribute to the thermodynamic compensation. The finding that drug-resistant mutations can profoundly modulate the relative thermodynamic properties of a therapeutic target independent of the inhibitor presents a new challenge for rational drug design.

Dynamics of preferential substrate recognition in HIV-1 protease: redefining the substrate envelope.

Human immunodeficiency virus type 1 (HIV-1) protease (PR) permits viral maturation by processing the gag and gag-pro-pol polyproteins. HIV-1 PR inhibitors (PIs) are used in combination antiviral therapy but the emergence of drug resistance has limited their efficacy. The rapid evolution of HIV-1 necessitates consideration of drug resistance in novel drug design. Drug-resistant HIV-1 PR variants no longer inhibited efficiently, continue to hydrolyze the natural viral substrates. Though highly diverse in sequence, the HIV-1 PR substrates bind in a conserved three-dimensional shape we termed the substrate envelope. Earlier, we showed that resistance mutations arise where PIs protrude beyond the substrate envelope, because these regions are crucial for drug binding but not for substrate recognition. We extend this model by considering the role of protein dynamics in the interaction of HIV-1 PR with its substrates. We simulated the molecular dynamics of seven PR-substrate complexes to estimate the conformational flexibility of the bound substrates. Interdependence of substrate-protease interactions might compensate for variations in cleavage-site sequences and explain how a diverse set of sequences are recognized as substrates by the same enzyme. This diversity might be essential for regulating sequential processing of substrates. We define a dynamic substrate envelope as a more accurate representation of PR-substrate interactions. This dynamic substrate envelope, described by a probability distribution function, is a powerful tool for drug design efforts targeting ensembles of resistant HIV-1 PR variants with the aim of developing drugs that are less susceptible to resistance.