Identifying representative drug resistant mutants of HIV

RNA-seq analysis of phagocytic cells from murine epididymal white adipose tissue shows immunosenescence and age-related phosphorus metabolism

The underlying state of alterations in adipose tissue is hypothesized to be as a result of age-related changes. Young and aged mice have been documented to show distinct gene expression and distinct macrophage-specific adipose tissue regulation. However, more biological understanding is required to know the processes associated with these conditions in relation to the aging process. Transcriptional profiling with RNA-seq analysis was used to determine differentially expressed genes in young (2 months old) and aged (20 months old) mice macrophage-enriched phagocytic stromal vascular fractions of pooled epididymal white adipose tissue using data obtained from gene expression omnibus. Results showed distinct differentially expressed genes in young and aged mice with a p value cutoff of 0.05 and dissimilarities in the young and aged epididymal white adipose tissue phagocytic cells. Functional enrichment showed activation of cytokine-cytokine receptor interaction pathways, phosphorus metabolic processes and inflammatory pathways such as IL-17, TNF, NF-kappa B, and TGF-β, while AMPK, PPAR and oxidative phosphorylation were suppressed. The analysis showed that aging is linked with phagocytic cell decline, accumulated cellular damages, inflammation, immunosenescence and increased phosphorus metabolism. Interventions that reduce phosphate-containing compound could improve phosphorus metabolism in old age to prolong lifespan and better health.

Revertant mutation V48G alters conformational dynamics of highly drug resistant HIV protease PRS17

Drug resistance is a serious problem for controlling the HIV/AIDS pandemic. Current antiviral drugs show several orders of magnitude worse inhibition of highly resistant clinical variant PRS17 of HIV-1 protease compared with wild-type protease. We have analyzed the effects of a common resistance mutation G48V in the flexible flaps of the protease by assessing the revertant PRS17_V48G for changes in enzyme kinetics, inhibition, structure, and dynamics. Both PRS17 and the revertant showed about 10-fold poorer catalytic efficiency than wild-type enzyme (0.55 and 0.39 μM^-1min^-1 compared to 6.3 μM^-1min^-1). Clinical inhibitors, amprenavir and darunavir, showed 2-fold and 8-fold better inhibition, respectively, of the revertant than of PRS17, although the inhibition constants for PRS17_V48G were still 25 to 1,200-fold worse than for wild-type protease. Crystal structures of inhibitor-free revertant and amprenavir complexes with revertant and PRS17 were solved at 1.3-1.5 Å resolution. The amprenavir complexes of PRS17_V48G and PRS17 showed no significant differences in the interactions with inhibitor, although changes were observed in the conformation of Phe53 and the interactions of the flaps. The inhibitor-free structure of the revertant showed flaps in an open conformation, however, the flap tips do not have the unusual curled conformation seen in inhibitor-free PRS17. Molecular dynamics simulations were run for 1 μs on the two inhibitor-free mutants and wild-type protease. PRS17 exhibited higher conformational fluctuations than the revertant, while the wild-type protease adopted the closed conformation and showed the least variation. The second half of the simulations captured the transition of the flaps of PRS17 from a closed to a semi-open state, whereas the flaps of PRS17_V48G tucked into the active site and the wild-type protease retained the closed conformation. These results suggest that mutation G48V contributes to drug resistance by altering the conformational dynamics of the flaps.

Novel HIV PR inhibitors with C4-substituted bis-THF and bis-fluoro-benzyl target the two active site mutations of highly drug resistant mutant PRS17

The emergence of multidrug resistant (MDR) HIV strains severely reduces the effectiveness of antiretroviral therapy. Clinical inhibitor darunavir (1) has picomolar binding affinity for HIV-1 protease (PR), however, drug resistant variants like PR^S17 show poor inhibition by 1, despite the presence of only two mutated residues in the inhibitor-binding site. Antiviral inhibitors that target MDR proteases like PR^S17 would be valuable as therapeutic agents. Inhibitors 2 and 3 derived from 1 through substitutions at P1, P2 and P2' positions exhibit 3.4- to 500-fold better inhibition than clinical inhibitors for PR^S17 with the exception of amprenavir. Crystal structures of PR^S17/2 and PR^S17/3 reveal how these inhibitors target the two active site mutations of PR^S17. The substituted methoxy P2 group of 2 forms new interactions with G48V mutation, while the modified bis-fluoro-benzyl P1 group of 3 forms a halogen interaction with V82S mutation, contributing to improved inhibition of PR^S17.

HIV Protease: Historical Perspective and Current Research

The retroviral protease of human immunodeficiency virus (HIV) is an excellent target for antiviral inhibitors for treating HIV/AIDS. Despite the efficacy of therapy, current efforts to control the disease are undermined by the growing threat posed by drug resistance. This review covers the historical background of studies on the structure and function of HIV protease, the subsequent development of antiviral inhibitors, and recent studies on drug-resistant protease variants. We highlight the important contributions of Dr. Stephen Oroszlan to fundamental knowledge about the function of the HIV protease and other retroviral proteases. These studies, along with those of his colleagues, laid the foundations for the design of clinical inhibitors of HIV protease. The drug-resistant protease variants also provide an excellent model for investigating the molecular mechanisms and evolution of resistance.

Evolution of drug resistance in HIV protease

BACKGROUND

Drug resistance is a critical problem limiting effective antiviral therapy for HIV/AIDS. Computational techniques for predicting drug resistance profiles from genomic data can accelerate the appropriate choice of therapy. These techniques can also be used to identify protease mutants for experimental studies of resistance and thereby assist in the development of next-generation therapies. Few studies, however, have assessed the evolution of resistance from genotype-phenotype data.

RESULTS

The machine learning produced highly accurate and robust classification of resistance to HIV protease inhibitors. Genotype data were mapped to the enzyme structure and encoded using Delaunay triangulation. Estimates of evolutionary relationships, based on this encoding, and using Minimum Spanning Trees, showed clusters of mutations that closely resemble the wild type. These clusters appear to evolve uniquely to more resistant phenotypes.

CONCLUSIONS

Using the triangulation metric and spanning trees results in paths that are consistent with evolutionary theory. The majority of the paths show bifurcation, namely they switch once from non-resistant to resistant or from resistant to non-resistant. Paths that lose resistance almost uniformly have far lower levels of resistance than those which either gain resistance or are stable. This strongly suggests that selection for stability in the face of a rapid rate of mutation is as important as selection for resistance in retroviral systems.

Highly drug-resistant HIV-1 protease reveals decreased intra-subunit interactions due to clusters of mutations

Drug-resistance is a serious problem for treatment of the HIV/AIDS pandemic. Potent clinical inhibitors of HIV-1 protease show several orders of magnitude worse inhibition of highly drug-resistant variants. Hence, the structure and enzyme activities were analyzed for HIV protease mutant HIV-1 protease (EC 3.4.23.16) (PR) with 22 mutations (PRS5B) from a clinical isolate that was selected by machine learning to represent high-level drug-resistance. PRS5B has 22 mutations including only one (I84V) in the inhibitor binding site; however, clinical inhibitors had poor inhibition of PRS5B activity with kinetic inhibition value (K_i ) values of 4-1000 nm or 18- to 8000-fold worse than for wild-type PR. High-resolution crystal structures of PRS5B complexes with the best inhibitors, amprenavir (APV) and darunavir (DRV) (K_i ~ 4 nm), revealed only minor changes in protease-inhibitor interactions. Instead, two distinct clusters of mutations in distal regions induce coordinated conformational changes that decrease favorable internal interactions across the entire protein subunit. The largest structural rearrangements are described and compared to other characterized resistant mutants. In the protease hinge region, the N83D mutation eliminates a hydrogen bond connecting the hinge and core of the protease and increases disorder compared to highly resistant mutants PR with 17 mutations and PR with 20 mutations with similar hinge mutations. In a distal β-sheet, mutations G73T and A71V coordinate with accessory mutations to bring about shifts that propagate throughout the subunit. Molecular dynamics simulations of ligand-free dimers show differences consistent with loss of interactions in mutant compared to wild-type PR. Clusters of mutations exhibit both coordinated and antagonistic effects, suggesting PRS5B may represent an intermediate stage in the evolution of more highly resistant variants. DATABASES: Structural data are available in Protein Data Bank under the accession codes 6P9A and 6P9B for PRS5B/DRV and PRS5B/APV, respectively.

Tuberculosis, HIV, and viral hepatitis diagnostics in eastern Europe and central Asia: high time for integrated and people-centred services

Globally, high rates (and in the WHO European region an increasing prevalence) of co-infection with tuberculosis and HIV and HIV and hepatitis C virus exist. In eastern European and central Asian countries, the tuberculosis, HIV, and viral hepatitis programmes, including diagnostic services, are separate vertical structures. In this Personal View, we consider underlying reasons for the poor integration for these diseases, particularly in the WHO European region, and how to address this with an initial focus on diagnostic services. In part, this low integration has reflected different diagnostic development histories, global funding sources, and sample types used for diagnosis (eg, typically sputum for tuberculosis and blood for HIV and hepatitis C). Cooperation between services improved as patients with tuberculosis needed routine testing for HIV and vice versa, but financial, infection control, and logistical barriers remain. Multidisease diagnostic platforms exist, but to be used optimally, appropriate staff training and sensible understanding of different laboratory and infection control risks needs rapid implementation. Technically these ideas are all feasible. Poor coordination between these vertical systems remains unhelpful. There is a need to increase political and operational integration of diagnostic and treatment services and bring them closer to patients.

Highly Drug-Resistant HIV-1 Protease Mutant PRS17 Shows Enhanced Binding to Substrate Analogues

We report the structural analysis of highly drug-resistant human immunodeficiency virus protease (PR) variant PR^S17, rationally selected by machine learning, in complex with substrate analogues. Crystal structures were solved of inhibitor-free inactive PR^S17-D25N, wild-type PR/CA-p2 complex, and PR^S17 in complex with substrate analogues, CA-p2 and p2-NC. Peptide analogues p2-NC and CA-p2 exhibit inhibition constants of 514 and 22 nM, respectively, for PR^S17 or approximately 3-fold better than for PR. CA-p2 is a better inhibitor of PR^S17 than are clinical inhibitors (K _i = 50-8390 nM) except for amprenavir (K _i = 11 nM). G48V resistance mutation induces curled flap tips in PR^S17-D25N structure. The inner P2-P2' residues of substrate analogues in PR^S17 complexes maintain similar conformations to those of wild-type complex, while significant conformational changes are observed in the peripheral residues P3, P4' of CA-p2 and P3, P4, and P3' of p2-NC. The loss of β-branched side chain by V82S mutation initiates a shift in 80's loop and reshapes the S3/S3' subsite, which enhances substrate binding with new hydrogen bonds and van der Waals interactions that are absent in the wild-type structures. The steric hindrance caused by G48V mutation in the flap of PR^S17 contributes to altered binding interactions of P3 Arg, P4' norleucine of CA-p2, and P4 and P3' of p2-NC with the addition of new hydrogen bonds and van der Waals contacts. The enhanced interaction of PR^S17 with substrate analogues agrees with their relative inhibition, suggesting that this mutant improves substrate binding while decreasing affinity for clinical inhibitors.

Analysis of drug resistance in HIV protease

BACKGROUND

Drug resistance in HIV is the major problem limiting effective antiviral therapy. Computational techniques for predicting drug resistance profiles from genomic data can accelerate the appropriate choice of therapy. These techniques can also be used to select protease mutants for experimental studies of resistance and thereby assist in the development of next-generation therapies.

RESULTS

The machine learning produced highly accurate and robust classification of HIV protease resistance. Genotype data were mapped to the enzyme structure and encoded using Delaunay triangulation. Generative machine learning models trained on one inhibitor could classify resistance from other inhibitors with varying levels of accuracy. Generally, the accuracy was best when the inhibitors were chemically similar.

CONCLUSIONS

Restricted Boltzmann Machines are an effective machine learning tool for classification of genomic and structural data. They can also be used to compare resistance profiles of different protease inhibitors.

Decoding HIV resistance: from genotype to therapy

Genetic variation in HIV poses a major challenge for prevention and treatment of the AIDS pandemic. Resistance occurs by mutations in the target proteins that lower affinity for the drug or alter the protein dynamics, thereby enabling viral replication in the presence of the drug. Due to the prevalence of drug-resistant strains, monitoring the genotype of the infecting virus is recommended. Computational approaches for predicting resistance from genotype data and guiding therapy are discussed. Many prediction methods rely on rules derived from known resistance-associated mutations, however, statistical or machine learning can improve the classification accuracy and assess unknown mutations. Adding classifiers such as information on the atomic structure of the protein can further enhance the predictions.

Structural Studies of a Rationally Selected Multi-Drug Resistant HIV-1 Protease Reveal Synergistic Effect of Distal Mutations on Flap Dynamics

We report structural analysis of HIV protease variant PR^S17 which was rationally selected by machine learning to represent wide classes of highly drug-resistant variants. Crystal structures were solved of PR^S17 in the inhibitor-free form and in complex with antiviral inhibitor, darunavir. Despite its 17 mutations, PR^S17 has only one mutation (V82S) in the inhibitor/substrate binding cavity, yet exhibits high resistance to all clinical inhibitors. PR^S17 has none of the major mutations (I47V, I50V, I54ML, L76V and I84V) associated with darunavir resistance, but has 10,000-fold weaker binding affinity relative to the wild type PR. Comparable binding affinity of 8000-fold weaker than PR is seen for drug resistant mutant PR20, which bears 3 mutations associated with major resistance to darunavir (I47V, I54L and I84V). Inhibitor-free PR^S17 shows an open flap conformation with a curled tip correlating with G48V flap mutation. NMR studies on inactive PR^S17_D25N unambiguously confirm that the flaps adopt mainly an open conformation in solution very similar to that in the inhibitor-free crystal structure. In PR^S17, the hinge loop cluster of mutations, E35D, M36I and S37D, contributes to the altered flap dynamics by a mechanism similar to that of PR20. An additional K20R mutation anchors an altered conformation of the hinge loop. Flap mutations M46L and G48V in PR^S17/DRV complex alter the Phe53 conformation by steric hindrance between the side chains. Unlike the L10F mutation in PR20, L10I in PR^S17 does not break the inter-subunit ion pair or diminish the dimer stability, consistent with a very low dimer dissociation constant comparable to that of wild type PR. Distal mutations A71V, L90M and I93L propagate alterations to the catalytic site of PR^S17. PR^S17 exhibits a molecular mechanism whereby mutations act synergistically to alter the flap dynamics resulting in significantly weaker binding yet maintaining active site contacts with darunavir.

Binding of Clinical Inhibitors to a Model Precursor of a Rationally Selected Multidrug Resistant HIV-1 Protease Is Significantly Weaker Than That to the Released Mature Enzyme

We have systematically validated the activity and inhibition of a HIV-1 protease (PR) variant bearing 17 mutations (PR(S17)), selected to represent high resistance by machine learning on genotype-phenotype data. Three of five mutations in PR(S17) correlating with major drug resistance, M46L, G48V, and V82S, and five of 11 natural variations differ from the mutations in two clinically derived extreme mutants, PR20 and PR22 bearing 19 and 22 mutations, respectively. PR(S17), which forms a stable dimer (<10 nM), is ∼10- and 2-fold less efficient in processing the Gag polyprotein than the wild type and PR20, respectively, but maintains the same cleavage order. Isolation of a model precursor of PR(S17) flanked by the 56-amino acid transframe region (TFP-p6pol) at its N-terminus, which is impossible upon expression of an analogous PR20 precursor, allowed systematic comparison of inhibition of TFP-p6pol-PR(S17) and mature PR(S17). Resistance of PR(S17) to eight protease inhibitors (PIs) relative to PR (Ki) increases by 1.5-5 orders of magnitude from 0.01 to 8.4 μM. Amprenavir, darunavir, atazanavir, and lopinavir, the most effective of the eight PIs, inhibit precursor autoprocessing at the p6pol/PR site with IC50 values ranging from ∼7.5 to 60 μM. Thus, this process, crucial for stable dimer formation, shows inhibition ∼200-800-fold weaker than that of the mature PR(S17). TFP/p6pol cleavage, which occurs faster, is inhibited even more weakly by all PIs except darunavir (IC50 = 15 μM); amprenavir shows a 2-fold increase in IC50 (∼15 μM), and atazanavir and lopinavir show increased IC50 values of >42 and >70 μM, respectively.