X-ray crystal structures of human immunodeficiency virus type 1 protease mutants complexed with atazanavir

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

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

GSK3640254 Is a Novel HIV-1 Maturation Inhibitor with an Optimized Virology Profile

HIV-1 maturation inhibitors (MIs) offer a novel mechanism of action and potential for use in HIV-1 treatment. Prior MIs displayed clinical efficacy but were associated with the emergence of resistance and some gastrointestinal tolerability events. Treatment with the potentially safer next-generation MI GSK3640254 (GSK'254) resulted in up to a 2-log10 viral load reduction in a phase IIa proof-of-concept study. In vitro experiments have defined the antiviral and resistance profiles for GSK'254. The compound displayed strong antiviral activity against a library of subtype B and C chimeric viruses containing Gag polymorphisms and site-directed mutants previously shown to affect potency of earlier-generation MIs, with a mean protein-binding adjusted 90% effective concentration (EC90) of 33 nM. Furthermore, GSK'254 exhibited robust antiviral activity against a panel of HIV-1 clinical isolates, with a mean EC50 of 9 nM. Mechanistic studies established that bound GSK'254 dissociated on average 7.1-fold more slowly from wild-type Gag virus-like particles (VLPs) than a previous-generation MI. In resistance studies, the previously identified A364V Gag region mutation was selected under MI pressure in cell culture and during the phase IIa clinical study. As expected, GSK'254 inhibited cleavage of p25 in a range of polymorphic HIV-1 Gag VLPs. Virus-like particles containing the A364V mutation exhibited a p25 cleavage rate 9.3 times higher than wild-type particles, providing a possible mechanism for MI resistance. The findings demonstrate that GSK'254 potently inhibits a broad range of HIV-1 strains expressing Gag polymorphisms.

Amino Acid and Peptide-Based Antiviral Agents

A significant number of antiviral agents used in clinical practice are amino acids, short peptides, or peptidomimetics. Among them, several HIV protease inhibitors (e. g. lopinavir, atazanavir), HCV protease inhibitors (e. g. grazoprevir, glecaprevir), and HCV NS5A protein inhibitors have contributed to a significant decrease in mortality from AIDS and hepatitis. However, there is an ongoing need for the discovery of new antiviral agents and the development of existing drugs; amino acids, both proteinogenic and non-proteinogenic in nature, serve as convenient building blocks for this purpose. The synthesis of non-proteinogenic amino acid components of antiviral agents could be challenging due to the need for enantiomerically or diastereomerically pure products. Herein, we present a concise review of antiviral agents whose structures are based on amino acids of both natural and unnatural origin. Special attention is paid to the synthetic aspects of non-proteinogenic amino acid components of those agents.

A Structural View on Medicinal Chemistry Strategies against Drug Resistance

The natural phenomenon of drug resistance is a widespread issue that hampers the performance of drugs in many major clinical indications. Antibacterial and antifungal drugs are affected, as well as compounds for the treatment of cancer, viral infections, or parasitic diseases. Despite the very diverse set of biological targets and organisms involved in the development of drug resistance, the underlying molecular mechanisms have been identified to understand the emergence of resistance and to overcome this detrimental process. Detailed structural information on the root causes for drug resistance is nowadays frequently available, so next-generation drugs can be designed that are anticipated to suffer less from resistance. This knowledge-based approach is essential for fighting the inevitable occurrence of drug resistance.

Structural analyses of 2015-updated drug-resistant mutations in HIV-1 protease: an implication of protease inhibitor cross-resistance

Background

Strategies to control HIV for improving the quality of patient lives have been aided by the Highly Active Anti-Retroviral Therapy (HAART), which consists of a cocktail of inhibitors targeting key viral enzymes. Numerous new drugs have been developed over the past few decades but viral resistances to these drugs in the targeted viral enzymes are increasingly reported. Nonetheless the acquired mutations often reduce viral fitness and infectivity. Viral compensatory secondary-line mutations mitigate this loss of fitness, equipping the virus with a broad spectrum of resistance against these drugs. While structural understanding of the viral protease and its drug resistance mutations have been well established, the interconnectivity and development of structural cross-resistance remain unclear. This paper reports the structural analyses of recent clinical mutations on the drug cross-resistance effects from various protease and protease inhibitors (PIs) complexes.

Methods

Using the 2015 updated clinical HIV protease mutations, we constructed a structure-based correlation network and a minimum-spanning tree (MST) based on the following features: (i) topology of the PI-binding pocket, (ii) allosteric effects of the mutations, and (iii) protease structural stability.

Results and conclusion

Analyis of the network and the MST of dominant mutations conferring resistance to the seven PIs (Atazanavir-ATV, Darunavir-DRV, Indinavir-IDV, Lopinavir-LPV, Nelfinavir-NFV, Saquinavir-SQV, and Tipranavir-TPV) showed that cross-resistance can develop easily across NFV, SQV, LPV, IDV, and DRV, but not for ATV or TPV. Through estimation of the changes in vibrational entropies caused by each reported mutation, some secondary mutations were found to destabilize protease structure. Our findings provide an insight into the mechanism of PI cross-resistance and may also be useful in guiding the selection of PI in clinical treatment to delay the onset of cross drug resistance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1372-3) contains supplementary material, which is available to authorized users.

Mechanistic Studies and Modeling Reveal the Origin of Differential Inhibition of Gag Polymorphic Viruses by HIV-1 Maturation Inhibitors

HIV-1 maturation inhibitors (MIs) disrupt the final step in the HIV-1 protease-mediated cleavage of the Gag polyprotein between capsid p24 capsid (CA) and spacer peptide 1 (SP1), leading to the production of infectious virus. BMS-955176 is a second generation MI with improved antiviral activity toward polymorphic Gag variants compared to a first generation MI bevirimat (BVM). The underlying mechanistic reasons for the differences in polymorphic coverage were studied using antiviral assays, an LC/MS assay that quantitatively characterizes CA/SP1 cleavage kinetics of virus like particles (VLPs) and a radiolabel binding assay to determine VLP/MI affinities and dissociation kinetics. Antiviral assay data indicates that BVM does not achieve 100% inhibition of certain polymorphs, even at saturating concentrations. This results in the breakthrough of infectious virus (partial antagonism) regardless of BVM concentration. Reduced maximal percent inhibition (MPI) values for BVM correlated with elevated EC50 values, while rates of HIV-1 protease cleavage at CA/SP1 correlated inversely with the ability of BVM to inhibit HIV-1 Gag polymorphic viruses: genotypes with more rapid CA/SP1 cleavage kinetics were less sensitive to BVM. In vitro inhibition of wild type VLP CA/SP1 cleavage by BVM was not maintained at longer cleavage times. BMS-955176 exhibited greatly improved MPI against polymorphic Gag viruses, binds to Gag polymorphs with higher affinity/longer dissociation half-lives and exhibits greater time-independent inhibition of CA/SP1 cleavage compared to BVM. Virological (MPI) and biochemical (CA/SP1 cleavage rates, MI-specific Gag affinities) data were used to create an integrated semi-quantitative model that quantifies CA/SP1 cleavage rates as a function of both MI and Gag polymorph. The model outputs are in accord with in vitro antiviral observations and correlate with observed in vivo MI efficacies. Overall, these findings may be useful to further understand antiviral profiles and clinical responses of MIs at a basic level, potentially facilitating further improvements to MI potency and coverage.

Identification and Characterization of BMS-955176, a Second-Generation HIV-1 Maturation Inhibitor with Improved Potency, Antiviral Spectrum, and Gag Polymorphic Coverage

BMS-955176 is a second-generation human immunodeficiency virus type 1 (HIV-1) maturation inhibitor (MI). A first-generation MI, bevirimat, showed clinical efficacy in early-phase studies, but ∼50% of subjects had viruses with reduced susceptibility associated with naturally occurring polymorphisms in Gag near the site of MI action. MI potency was optimized using a panel of engineered reporter viruses containing site-directed polymorphic changes in Gag that reduce susceptibility to bevirimat (including V362I, V370A/M/Δ, and T371A/Δ), leading incrementally to the identification of BMS-955176. BMS-955176 exhibits potent activity (50% effective concentration [EC50], 3.9 ± 3.4 nM [mean ± standard deviation]) toward a library (n = 87) of gag/pr recombinant viruses representing 96.5% of subtype B polymorphic Gag diversity near the CA/SP1 cleavage site. BMS-955176 exhibited a median EC50 of 21 nM toward a library of subtype B clinical isolates assayed in peripheral blood mononuclear cells (PBMCs). Potent activity was maintained against a panel of reverse transcriptase, protease, and integrase inhibitor-resistant viruses, with EC50s similar to those for the wild-type virus. A 5.4-fold reduction in EC50 occurred in the presence of 40% human serum plus 27 mg/ml of human serum albumin (HSA), which corresponded well to an in vitro measurement of 86% human serum binding. Time-of-addition and pseudotype reporter virus studies confirm a mechanism of action for the compound that occurs late in the virus replication cycle. BMS-955176 inhibits HIV-1 protease cleavage at the CA/SP1 junction within Gag in virus-like particles (VLPs) and in HIV-1-infected cells, and it binds reversibly and with high affinity to assembled Gag in purified HIV-1 VLPs. Finally, in vitro combination studies showed no antagonistic interactions with representative antiretrovirals (ARVs) of other mechanistic classes. In conclusion, BMS-955176 is a second-generation MI with potent in vitro anti-HIV-1 activity and a greatly improved preclinical profile compared to that of bevirimat.

Heteroaromatic π-stacking energy landscapes

In this study we investigate π-stacking interactions of a variety of aromatic heterocycles with benzene using dispersion corrected density functional theory. We calculate extensive potential energy surfaces for parallel-displaced interaction geometries. We find that dispersion contributes significantly to the interaction energy and is complemented by a varying degree of electrostatic interactions. We identify geometric preferences and minimum interaction energies for a set of 13 5- and 6-membered aromatic heterocycles frequently encountered in small drug-like molecules. We demonstrate that the electrostatic properties of these systems are a key determinant for their orientational preferences. The results of this study can be applied in lead optimization for the improvement of stacking interactions, as it provides detailed energy landscapes for a wide range of coplanar heteroaromatic geometries. These energy landscapes can serve as a guide for ring replacement in structure-based drug design.

Ligand placement based on prior structures: the guided ligand-replacement method

The process of iterative structure-based drug design involves the X-ray crystal structure determination of upwards of 100 ligands with the same general scaffold (i.e. chemotype) complexed with very similar, if not identical, protein targets. In conjunction with insights from computational models and assays, this collection of crystal structures is analyzed to improve potency, to achieve better selectivity and to reduce liabilities such as absorption, distribution, metabolism, excretion and toxicology. Current methods for modeling ligands into electron-density maps typically do not utilize information on how similar ligands bound in related structures. Even if the electron density is of sufficient quality and resolution to allow de novo placement, the process can take considerable time as the size, complexity and torsional degrees of freedom of the ligands increase. A new module, Guided Ligand Replacement (GLR), was developed in Phenix to increase the ease and success rate of ligand placement when prior protein-ligand complexes are available. At the heart of GLR is an algorithm based on graph theory that associates atoms in the target ligand with analogous atoms in the reference ligand. Based on this correspondence, a set of coordinates is generated for the target ligand. GLR is especially useful in two situations: (i) modeling a series of large, flexible, complicated or macrocyclic ligands in successive structures and (ii) modeling ligands as part of a refinement pipeline that can automatically select a reference structure. Even in those cases for which no reference structure is available, if there are multiple copies of the bound ligand per asymmetric unit GLR offers an efficient way to complete the model after the first ligand has been placed. In all of these applications, GLR leverages prior knowledge from earlier structures to facilitate ligand placement in the current structure.

Automating crystallographic structure solution and refinement of protein-ligand complexes

High-throughput drug-discovery and mechanistic studies often require the determination of multiple related crystal structures that only differ in the bound ligands, point mutations in the protein sequence and minor conformational changes. If performed manually, solution and refinement requires extensive repetition of the same tasks for each structure. To accelerate this process and minimize manual effort, a pipeline encompassing all stages of ligand building and refinement, starting from integrated and scaled diffraction intensities, has been implemented in Phenix. The resulting system is able to successfully solve and refine large collections of structures in parallel without extensive user intervention prior to the final stages of model completion and validation.

Elucidating a relationship between conformational sampling and drug resistance in HIV-1 protease

Enzyme targets in rapidly replicating systems, such as retroviruses, commonly respond to drug-selective pressure with mutations arising in the active site pocket that limit inhibitor effectiveness by introducing steric hindrance or by eliminating essential molecular interactions. However, these primary mutations are disposed to compromising pathogenic fitness. Emerging secondary mutations, which are often found outside of the binding cavity, may or can restore fitness while maintaining drug resistance. The accumulated drug pressure selected mutations could have an indirect effect in the development of resistance, such as altering protein flexibility or the dynamics of protein-ligand interactions. Here, we show that accumulation of mutations in a drug-resistant HIV-1 protease (HIV-1 PR) variant, D30N/M36I/A71V, changes the fractional occupancy of the equilibrium conformational sampling ensemble. Correlations are made among populations of the conformational states, namely, closed-like, semiopen, and open-like, with inhibition constants, as well as kinetic parameters. Mutations that stabilize a closed-like conformation correlate with enzymes of lowered activity and with higher affinity for inhibitors, which is corroborated by a further increase in the fractional occupancy of the closed state upon addition of inhibitor or substrate-mimic. Cross-resistance is found to correlate with combinations of mutations that increase the population of the open-like conformations at the expense of the closed-like state while retaining native-like occupancy of the semiopen population. These correlations suggest that at least three states are required in the conformational sampling model to establish the emergence of drug resistance in HIV-1 PR. More importantly, these results shed light on a possible mechanism whereby mutations combine to impart drug resistance while maintaining catalytic activity.

[Bioinformatics studies on drug resistance against anti-HIV-1 drugs]

More than 20 drugs have been available for anti-HIV-1 treatment in Japan. Combination therapy with these drugs dramatically decreases in morbidity and mortality of AIDS. However, due to high mutation rate of HIV-1, treatment with ineffective drugs toward patients infected with HIV-1 causes accumulation of mutations in the virus, and emergence of drug resistant viruses. Thus, to achieve appropriate application of the drugs toward the respective patients living with HIV-1, methods for predicting the level of drug-resistance using viral sequence information has been developed on the basis of bioinformatics. Furthermore, ultra-deep sequencing by next-generation sequencer whose data analysis is also based on bioinformatics, or in silico structural modeling have been achieved to understand drug resistant mechanisms. In this review, I overview the bioinformatics studies about drug resistance against anti-HIV-1 drugs.

Rationale for more diverse inhibitors in competition with substrates in HIV-1 protease

The structural fluctuations of HIV-1 protease in interaction with its substrates versus inhibitors were analyzed using the anisotropic network model. The directions of fluctuations in the most cooperative functional modes differ mainly around the dynamically key regions, i.e., the hinge axes, which appear to be more flexible in substrate complexes. The flexibility of HIV-1 protease is likely optimized for the substrates' turnover, resulting in substrate complexes being dynamic. In contrast, in an inhibitor complex, the inhibitor should bind and lock down to inactivate the active site. Protease and ligands are not independent. Substrates are also more flexible than inhibitors and have the potential to meet the dynamic distributions that are inherent in the protease. This may suggest a rationale and guidelines for designing inhibitors that can better fit the ensemble of binding sites that are dynamically accessible to the protease.

A switch-on mechanism to activate maize ribosome-inactivating protein for targeting HIV-infected cells

Maize ribosome-inactivating protein (RIP) is a plant toxin that inactivates eukaryotic ribosomes by depurinating a specific adenine residue at the α-sarcin/ricin loop of 28S rRNA. Maize RIP is first produced as a proenzyme with a 25-amino acid internal inactivation region on the protein surface. During germination, proteolytic removal of this internal inactivation region generates the active heterodimeric maize RIP with full N-glycosidase activity. This naturally occurring switch-on mechanism provides an opportunity for targeting the cytotoxin to pathogen-infected cells. Here, we report the addition of HIV-1 protease recognition sequences to the internal inactivation region and the activation of the maize RIP variants by HIV-1 protease in vitro and in HIV-infected cells. Among the variants generated, two were cleaved efficiently by HIV-1 protease. The HIV-1 protease-activated variants showed enhanced N-glycosidase activity in vivo as compared to their un-activated counterparts. They also possessed potent inhibitory effect on p24 antigen production in human T cells infected by two HIV-1 strains. This switch-on strategy for activating the enzymatic activity of maize RIP in target cells provides a platform for combating pathogens with a specific protease.

Atazanavir: its role in HIV treatment

Azatanavir is a protease inhibitor (PI) approved for the treatment of HIV-1 infection. Atazanavir is a substrate and inhibitor of cytochrome P450 isozyme 3A and an inhibitor and inducer of P-glycoprotein. It has similar virologic efficacy as efavirenz and ritonavir-boosted lopinavir in antiretroviral-naive individuals. Its impact on lipids is less than other PIs and it is suitable for those in whom hyperlipidemia is undesirable. Ritonavir boosting of atazanavir enhances the bioavailability of atazanavir but may result in some elevation of lipids and is recommended for treatment-experienced patients and those receiving efavirenz or tenofovir. Ritonavir-boosted atazanavir has similar antiviral activity as ritonavir-boosted lopinavir in both antiretroviral therapy-naive and -experienced patients. Atazanavir causes unconjugated bilirubinemia in over 40% of patients but results in less than 2% discontinuations. Atazanavir is licensed for once-daily use and atazanavir/ritonavir competes with lopinavir/ritonavir as the most commonly prescribed PI.

Effect of the active site D25N mutation on the structure, stability, and ligand binding of the mature HIV-1 protease

All aspartic proteases, including retroviral proteases, share the triplet DTG critical for the active site geometry and catalytic function. These residues interact closely in the active, dimeric structure of HIV-1 protease (PR). We have systematically assessed the effect of the D25N mutation on the structure and stability of the mature PR monomer and dimer. The D25N mutation (PR(D25N)) increases the equilibrium dimer dissociation constant by a factor >100-fold (1.3 +/- 0.09 microm) relative to PR. In the absence of inhibitor, NMR studies reveal clear structural differences between PR and PR(D25N) in the relatively mobile P1 loop (residues 79-83) and flap regions, and differential scanning calorimetric analyses show that the mutation lowers the stabilities of both the monomer and dimer folds by 5 and 7.3 degrees C, respectively. Only minimal differences are observed in high resolution crystal structures of PR(D25N) complexed to darunavir (DRV), a potent clinical inhibitor, or a non-hydrolyzable substrate analogue, Ac-Thr-Ile-Nle-r-Nle-Gln-Arg-NH(2) (RPB), as compared with PR.DRV and PR.RPB complexes. Although complexation with RPB stabilizes both dimers, the effect on their T(m) is smaller for PR(D25N) (6.2 degrees C) than for PR (8.7 degrees C). The T(m) of PR(D25N).DRV increases by only 3 degrees C relative to free PR(D25N), as compared with a 22 degrees C increase for PR.DRV, and the mutation increases the ligand dissociation constant of PR(D25N).DRV by a factor of approximately 10(6) relative to PR.DRV. These results suggest that interactions mediated by the catalytic Asp residues make a major contribution to the tight binding of DRV to PR.