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.

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 β3-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 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 substrateenvelope 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.

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 wildtype 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.

HIV-1 protease is one of the major antiviral targets in the treatment of patients infected with HIV-1. The nine FDA approved HIV-1 protease inhibitors were developed with extensive use of structure-based drug design, thus the atomic details of how the inhibitors bind are well characterized. From this structural understanding the molecular basis for drug resistance in HIV-1 protease can be elucidated. Selected mutations in response to therapy and diversity between clades in HIV-1 protease have altered the shape of the active site, potentially altered the dynamics and even altered the sequence of the cleavage sites in the Gag polyprotein. All of these interdependent changes act in synergy to confer drug resistance while simultaneously maintaining the fitness of the virus. New strategies, such as incorporation of the substrate envelope constraint to design robust inhibitors that incorporate details of HIV-1 protease’s function and decrease the probability of drug resistance, are necessary to continue to effectively target this key protein in HIV-1 life cycle.

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 (PR) permits viral maturation by processing the Gag and Gag-Pro-Pol polyproteins. Though HIV-1 PR inhibitors (PIs) are used in combination antiviral therapy, the emergence of drug resistance has limited their efficacy. The rapid evolution of HIV-1 necessitates the consideration of drug resistance in novel drug-design strategies. Drug-resistant HIV-1 PR variants, while no longer efficiently inhibited, continue to efficiently hydrolyze the natural viral substrates. Though highly diverse in sequence, the HIV-1 PR substrates bind in a conserved three-dimensional shape we defined as the “substrate envelope”. We previously showed that resistance mutations arise where PIs protrude beyond the substrate envelope, as these regions are crucial for drug binding but not for substrate recognition. Here, we extend this model by considering the role of protein dynamics in the interaction of HIV-1 PR with its substrates. Seven molecular dynamics simulations of PR-substrate complexes were performed to estimate the conformational flexibility of substrates in their complexes. Interdependency of the substrate-protease interactions may compensate for the variations in cleavage-site sequences, and explain how a diverse set of sequences can be recognized as substrates by the same enzyme. This diversity may be essential for regulating sequential processing of substrates. We also 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.

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