Highly conserved glycine 86 and arginine 87 residues contribute differently to the structure and activity of the mature HIV-1 protease

Enthalpic Classification of Water Molecules in Target-Ligand Binding

Water molecules play various roles in target-ligand binding. For example, they can be replaced by the ligand and leave the surface of the binding pocket or stay conserved in the interface and form bridges with the target. While experimental techniques supply target-ligand complex structures at an increasing rate, they often have limitations in the measurement of a detailed water structure. Moreover, measurements of binding thermodynamics cannot distinguish between the different roles of individual water molecules. However, such a distinction and classification of the role of individual water molecules would be key to their application in drug design at atomic resolution. In this study, we investigate a quantitative approach for the description of the role of water molecules during ligand binding. Starting from complete hydration structures of the free and ligand-bound target molecules, binding enthalpy scores are calculated for each water molecule using quantum mechanical calculations. A statistical evaluation showed that the scores can distinguish between conserved and displaced classes of water molecules. The classification system was calibrated and tested on more than 1000 individual water positions. The practical tests of the enthalpic classification included important cases of antiviral drug research on HIV-1 protease inhibitors and the Influenza A ion channel. The methodology of classification is based on open source program packages, Gromacs, Mopac, and MobyWat, freely available to the scientific community.

NDK/NME proteins: a host-pathogen interface perspective towards therapeutics

No effective vaccine is available for any parasitic disease. The treatment to those is solely dependent on chemotherapy, which is always threatened due to development of drug resistance in bugs. This warrants identification of new drug targets. Here, we discuss Nucleoside diphosphate kinases (NDKs) of pathogens that alter host's intra and extracellular environment, as novel drug targets to simultaneously tackle multiple pathogens. NDKs having diverse functions, are highly conserved among prokaryotes and eukaryotes (the mammal NDKs are called NMEs [non-metastatic enzymes]). However, NDKs and NMEs have been separately analysed in the past for their structure and functions. The role of NDKs of pathogen in modulation of inflammation, phagocytosis, apoptosis, and ROS generation in host is known. Conversely, its combined contribution in host-pathogen interaction has not been studied yet. Through the sequence and domain analysis, we found that NDKs can be classified in two groups. One group comprised NMEs 1-4 and few NDKs of select essential protozoan parasites and the bacterium Mycobacterium tuberculosis. The other group included NME7 and the other NDKs of those parasites, posing challenges in the development of drugs specifically targeting pathogen NDKs, without affecting NME7. However, common drugs targeting group 2 NDKs of pathogens can be designed, as NME7 of group 2 is expressed only in ciliated host cells. This review thus analyses comparatively for the first time the structures and functions of human NMEs and pathogen NDKs and predicts the possibilities of NDKs as drug targets. In addition, pathogen NDKs have been now provided a nomenclature in alignment with the NMEs of humans.

Prediction of HIV drug resistance based on the 3D protein structure: Proposal of molecular field mapping

A method for predicting HIV drug resistance by using genotypes would greatly assist in selecting appropriate combinations of antiviral drugs. Models reported previously have had two major problems: lack of information on the 3D protein structure and processing of incomplete sequencing data in the modeling procedure. We propose obtaining the 3D structural information of viral proteins by using homology modeling and molecular field mapping, instead of just their primary amino acid sequences. The molecular field potential parameters reflect the physicochemical characteristics associated with the 3D structure of the proteins. We also introduce the Bayesian conditional mutual information theory to estimate the probabilities of occurrence of all possible protein candidates from an incomplete sequencing sample. This approach allows for the effective use of uncertain information for the modeling process. We applied these data analysis techniques to the HIV-1 protease inhibitor dataset and developed drug resistance prediction models with reasonable performance.

Dimer Interface Organization is a Main Determinant of Intermonomeric Interactions and Correlates with Evolutionary Relationships of Retroviral and Retroviral-Like Ddi1 and Ddi2 Proteases

The life cycles of retroviruses rely on the limited proteolysis catalyzed by the viral protease. Numerous eukaryotic organisms also express endogenously such proteases, which originate from retrotransposons or retroviruses, including DNA damage-inducible 1 and 2 (Ddi1 and Ddi2, respectively) proteins. In this study, we performed a comparative analysis based on the structural data currently available in Protein Data Bank (PDB) and Structural summaries of PDB entries (PDBsum) databases, with a special emphasis on the regions involved in dimerization of retroviral and retroviral-like Ddi proteases. In addition to Ddi1 and Ddi2, at least one member of all seven genera of the Retroviridae family was included in this comparison. We found that the studied retroviral and non-viral proteases show differences in the mode of dimerization and density of intermonomeric contacts, and distribution of the structural characteristics is in agreement with their evolutionary relationships. Multiple sequence and structure alignments revealed that the interactions between the subunits depend mainly on the overall organization of the dimer interface. We think that better understanding of the general and specific features of proteases may support the characterization of retroviral-like proteases.

Evidence of genomic information and structural restrictions of HIV-1 PR and RT gene regions from individuals experiencing antiretroviral virologic failure

OBJECTIVES

This study analyzed Protease-PR and Reverse Transcriptase-RT HIV-1 genomic information entropy metrics among patients under antiretroviral virologic failure, according to the numbers of virologic failures or resistance mutations.

METHODS

For this purpose, we used genomic sequences from PR and RT of HIV-1 from a cohort of chronic patients followed up at São Paulo Hospital.

RESULTS

Informational entropy proportionally increases with the number of antiretroviral virologic failures in PR and RT (p < .001). Affected regions of PR were related to catalytic and structural functions, such as Fulcrum (K20) Flap (M46) and Cantilever (A71). In RT, this occurred at Fingers (E44) and Palm (K219). Informational entropy increases according to the number of resistance mutations in PR and RT (p < .001). Higher PR entropy was proportional to the resistance mutation numbers in Fulcrum (L10), Active site (L24) Flap (M46), Cantilever (L63) and near Interface (L90). In RT, they related to regions responsible for protein stability such as Fingers (T39) and Palm (L100).

CONCLUSIONS

The antiretroviral selective pressure affects HIV genomic informational entropy at the PR and RT regions, leading to the emergence of more unstable virions. Mapping the three-dimensional structure in these HIV-1 proteins is relevant to designing new antiretroviral targeting resistant strains.

Hydration Structure and Dynamics of Inhibitor-Bound HIV-1 Protease

Water is essential in many biological processes, and the hydration structure plays a critical role in facilitating protein folding, dynamics, and ligand binding. A variety of biophysical spectroscopic techniques have been used to probe the water solvating proteins, often complemented with molecular dynamics (MD) simulations to resolve the spatial and dynamic features of the hydration shell, but comparing relative water structure is challenging. In this study 1 μs MD simulations were performed to identify and characterize hydration sites around HIV-1 protease bound to an inhibitor, darunavir (DRV). The water density, hydration site occupancy, extent and anisotropy of fluctuations, coordinated water molecules, and hydrogen bonds were characterized and compared to the properties of bulk water. The water density of the principal hydration shell was found to be higher than bulk, dependent on the topology and physiochemical identity of the biomolecular surface. The dynamics of water molecules occupying principal hydration sites was highly dependent on the number of water-water interactions and inversely correlated with hydrogen bonds to the protein-inhibitor complex. While many waters were conserved following the symmetry of homodimeric HIV protease, the asymmetry induced by DRV resulted in asymmetric lower-occupancy hydration sites at the concave surface of the active site. Key interactions between water molecules and the protease, that stabilize the protein in the inhibited form, were altered in a drug resistant variant of the protease indicating that modulation of solvent-solute interactions might play a key role in conveying drug resistance. Our analysis provides insights into the interplay between an enzyme inhibitor complex and the hydration shell and has implications in elucidating water structure in a variety of biological processes and applications including ligand binding, inhibitor design, and resistance.

Mutations Proximal to Sites of Autoproteolysis and the α-Helix That Co-evolve under Drug Pressure Modulate the Autoprocessing and Vitality of HIV-1 Protease

N-Terminal self-cleavage (autoprocessing) of the HIV-1 protease precursor is crucial for liberating the active dimer. Under drug pressure, evolving mutations are predicted to modulate autoprocessing, and the reduced catalytic activity of the mature protease (PR) is likely compensated by enhanced conformational/dimer stability and reduced susceptibility to self-degradation (autoproteolysis). One such highly evolved, multidrug resistant protease, PR20, bears 19 mutations contiguous to sites of autoproteolysis in retroviral proteases, namely clusters 1-3 comprising residues 30-37, 60-67, and 88-95, respectively, accounting for 11 of the 19 mutations. By systematically replacing corresponding clusters in PR with those of PR20, and vice versa, we assess their influence on the properties mentioned above and observe no strict correlation. A 10-35-fold decrease in the cleavage efficiency of peptide substrates by PR20, relative to PR, is reflected by an only ∼4-fold decrease in the rate of Gag processing with no change in cleavage order. Importantly, optimal N-terminal autoprocessing requires all 19 PR20 mutations as evaluated in vitro using the model precursor TFR-PR20 in which PR is flanked by the transframe region. Substituting PR20 cluster 3 into TFR-PR (TFR-PR(PR20-3)) requires the presence of PR20 cluster 1 and/or 2 for autoprocessing. In accordance, substituting PR clusters 1 and 2 into TFR-PR20 affects the rate of autoprocessing more drastically (>300-fold) compared to that of TFR-PR(PR20-3) because of the cumulative effect of eight noncluster mutations present in TFR-PR20(PR-12). Overall, these studies imply that drug resistance involves a complex synchronized selection of mutations modulating all of the properties mentioned above governing PR regulation and function.

HIV-1 Nef inhibits Protease activity and its absence alters protein content of mature viral particles

Nef is an important player for viral infectivity and AIDS progression, but the mechanisms involved are not completely understood. It was previously demonstrated that Nef interacts with GagPol through p6*-Protease region. Because p6* and Protease are involved in processing, we explored the effect of Nef on viral Protease activity and virion assembly. Using in vitro assays, we observed that Nef is highly capable of inhibiting Protease activity. The IC50 for nef-deficient viruses in drug susceptibility assays were 1.7- to 3.5-fold higher than the wild-type counterpart varying with the type of the Protease inhibitor used. Indicating that, in the absence of Nef, Protease is less sensitive to Protease inhibitors. We compared the protein content between wild-type and nef-deficient mature viral particles by gradient sedimentation and observed up to 2.7-fold reduction in the Integrase levels in nef-deficient mature particles. This difference in levels of Integrase correlated with the difference in infectivity levels of wild type and nef-deficient viral progeny. In addition, an overall decrease in the production of mature particles was detected in nef-deficient viruses. Collectively, our data support the hypothesis that the decreased infectivity typical of nef-deficient viruses is due to an abnormal function of the viral Protease, which is in turn associated with less mature particles being produced and the loss of Integrase content in these particles, and these results may characterize Nef as a regulator of viral Protease activity.

Toward in silico biomolecular manipulation through static modes: atomic scale characterization of HIV-1 protease flexibility

Probing biomolecular flexibility with atomic-scale resolution is a challenging task in current computational biology for fundamental understanding and prediction of biomolecular interactions and associated functions. This paper makes use of the static mode method to study HIV-1 protease considered as a model system to investigate the full biomolecular flexibility at the atomic scale, the screening of active site biomechanical properties, the blind prediction of allosteric sites, and the design of multisite strategies to target deformations of interest. Relying on this single calculation run of static modes, we demonstrate that in silico predictive design of an infinite set of complex excitation fields is reachable, thanks to the storage of the static modes in a data bank that can be used to mimic single or multiatom contact and efficiently anticipate conformational changes arising from external stimuli. All along this article, we compare our results to data previously published and propose a guideline for efficient, predictive, and custom in silico experiments.

Investigation on the mechanism for the binding and drug resistance of wild type and mutations of G86 residue in HIV-1 protease complexed with Darunavir by molecular dynamic simulation and free energy calculation

Residue Gly86 is considered as the highly conversed residue in the HIV-1 protease. In our work, the detailed binding free energies for the wild-type (WT) and mutated proteases binding to the TMC-114 are estimated to investigate the protein-inhibitor binding and drug resistance mechanism by molecule dynamic simulations and molecular mechanics Poisson Boltzmann surface area (MM-PBSA) method. The binding affinities between the mutants and inhibitor are different than that in the wild-type complex and the major resistance to Darunavir (DRV) of G86A and G86S originate from the electrostatic energy and entropy, respectively. Furthermore, free energy decomposition analysis for the WT and mutated complexes on the basis of per-residue indicates that the mutagenesis influences the energy contribution of the residue located at three regions: active site region (residue 24-32), the flap region, and the region around the mutated residue G86 (residue 79-88), especially the flap region. Finally, further hydrogen bonds and structure analysis are carried out to detect the relationship between the energy and conformation. In all, the G86 mutations change the flap region's conformation. The experimental results are in good agreement with available results.

Understanding HIV-1 protease autoprocessing for novel therapeutic development

In the infected cell, HIV-1 protease (PR) is initially synthesized as part of the GagPol polyprotein. PR autoprocessing is a virus-specific process by which the PR domain embedded in the precursor catalyzes proteolytic reactions responsible for liberation of free mature PRs, which then recognize and cleave at least ten different peptide sequences in the Gag and GagPol polyproteins. Despite extensive structure and function studies of the mature PRs as well as the successful development of ten US FDA-approved catalytic-site inhibitors, the precursor autoprocessing mechanism remains an intriguing yet-to-be-solved puzzle. This article discusses current understanding of the autoprocessing mechanism, in an effort to prompt the development of novel anti-HIV drugs that selectively target precursor autoprocessing.

Novel P2 tris-tetrahydrofuran group in antiviral compound 1 (GRL-0519) fills the S2 binding pocket of selected mutants of HIV-1 protease

GRL-0519 (1) is a potent antiviral inhibitor of HIV-1 protease (PR) possessing tris-tetrahydrofuran (tris-THF) at P2. The high resolution X-ray crystal structures of inhibitor 1 in complexes with single substitution mutants PR(R8Q), PR(D30N), PR(I50V), PR(I54M), and PR(V82A) were analyzed in relation to kinetic data. The smaller valine side chain in PR(I50V) eliminated hydrophobic interactions with inhibitor and the other subunit consistent with 60-fold worse inhibition. Asn30 in PR(D30N) showed altered interactions with neighboring residues and 18-fold worse inhibition. Mutations V82A and I54M showed compensating structural changes consistent with 6-7-fold lower inhibition. Gln8 in PR(R8Q) replaced the ionic interactions of wild type Arg8 with hydrogen bond interactions without changing the inhibition significantly. The carbonyl oxygen of Gly48 showed two alternative conformations in all structures likely due to the snug fit of the large tris-THF group in the S2 subsite in agreement with high antiviral efficacy of 1 on resistant virus.

Structure-based methods for predicting target mutation-induced drug resistance and rational drug design to overcome the problem

Drug resistance has become one of the biggest challenges in drug discovery and/or development and has attracted great research interests worldwide. During the past decade, computational strategies have been developed to predict target mutation-induced drug resistance. Meanwhile, various molecular design strategies, including targeting protein backbone, targeting highly conserved residues and dual/multiple targeting, have been used to design novel inhibitors for combating the drug resistance. In this article we review recent advances in development of computational methods for target mutation-induced drug resistance prediction and strategies for rational design of novel inhibitors that could be effective against the possible drug-resistant mutants of the target.