A look inside HIV resistance through retroviral protease interaction maps.
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ABSTRACT:
SUBMITTER: Kontijevskis A
PROVIDER: S-EPMC1817660 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Drug resistance significantly impairs the efficacy of AIDS therapy. Therefore, precise prediction of resistant viral mutants is particularly useful for developing effective drugs and designing therapeutic regimen. In this study, we applied a structure-based computational approach to predict mutants of the HIV-1 protease resistant to the seven FDA approved drugs. We analyzed the energetic pattern of the protease-drug interaction by calculating the molecular interaction energy components (MIECs) between the drug and the protease residues. Support vector machines (SVMs) were trained on MIECs to classify protease mutants into resistant and nonresistant categories. The high prediction accuracies for the test sets of cross-validations suggested that the MIECs successfully characterized the interaction interface between drugs and the HIV-1 protease. We conducted a proof-of-concept study on a newly approved drug, darunavir (TMC114), on which no drug resistance data were available in the public domain. Compared with amprenavir, our analysis suggested that darunavir might be more potent to combat drug resistance. To quantitatively estimate binding affinities of drugs and study the contributions of protease residues to causing resistance, linear regression models were trained on MIECs using partial least squares (PLS). The MIEC-PLS models also achieved satisfactory prediction accuracy. Analysis of the fitting coefficients of MIECs in the regression model revealed the important resistance mutations and shed light into understanding the mechanisms of these mutations to cause resistance. Our study demonstrated the advantages of characterizing the protease-drug interaction using MIECs. We believe that MIEC-SVM and MIEC-PLS can help design new agents or combination of therapeutic regimens to counter HIV-1 protease resistant strains.
| S-EPMC3210569 | biostudies-literature
Project description:The effects of many protease inhibitor (PI)-selected mutations on the susceptibility to individual PIs are unknown. We analyzed in vitro susceptibility test results on 2,725 HIV-1 protease isolates. More than 2,400 isolates had been tested for susceptibility to fosamprenavir, indinavir, nelfinavir, and saquinavir; 2,130 isolates had been tested for susceptibility to lopinavir; 1,644 isolates had been tested for susceptibility to atazanavir; 1,265 isolates had been tested for susceptibility to tipranavir; and 642 isolates had been tested for susceptibility to darunavir. We applied least-angle regression (LARS) to the 200 most common mutations in the data set and identified a set of 46 mutations associated with decreased PI susceptibility of which 40 were not polymorphic in the eight most common HIV-1 group M subtypes. We then used least-squares regression to ascertain the relative contribution of each of these 46 mutations. The median number of mutations associated with decreased susceptibility to each PI was 28 (range, 19 to 32), and the median number of mutations associated with increased susceptibility to each PI was 2.5 (range, 1 to 8). Of the mutations with the greatest effect on PI susceptibility, I84AV was associated with decreased susceptibility to eight PIs; V32I, G48V, I54ALMSTV, V82F, and L90M were associated with decreased susceptibility to six to seven PIs; I47A, G48M, I50V, L76V, V82ST, and N88S were associated with decreased susceptibility to four to five PIs; and D30N, I50L, and V82AL were associated with decreased susceptibility to fewer than four PIs. This study underscores the greater impact of nonpolymorphic mutations compared with polymorphic mutations on decreased PI susceptibility and provides a comprehensive quantitative assessment of the effects of individual mutations on susceptibility to the eight clinically available PIs.
| S-EPMC2944562 | biostudies-literature
Project description:When using coherent activation mapping, adjusting scar settings even below the noise level (bipolar voltage amplitude ≤0.03 mV) should be considered to obtain the important information contained in the SNO zone.
| S-EPMC7733560 | biostudies-literature
Project description:BackgroundDrug 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.ResultsThe 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.ConclusionsRestricted 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.
| S-EPMC6196403 | biostudies-literature
Project description:BackgroundDrug 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.ResultsThe 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.ConclusionsUsing 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.
| S-EPMC7772915 | biostudies-literature
Project description:Most viruses encode their own proteases to carry out viral maturation and these often require dimerization for activity. Studies on human immunodeficiency virus type 1 (HIV-1), type 2 (HIV-2) and human T-cell leukemia virus (HTLV-1) proteases have shown that the activity of these proteases can be reversibly regulated by cysteine (Cys) glutathionylation and/or methionine oxidation (for HIV-2). These modifications lead to inhibition of protease dimerization and therefore loss of activity. These changes are reversible with the cellular enzymes, glutaredoxin or methionine sulfoxide reductase. Perhaps more importantly, as a result, the maturation of retroviral particles can also be regulated through reversible oxidation and this has been demonstrated for HIV-1, HIV-2, Mason-Pfizer monkey virus (M-PMV) and murine leukemia virus (MLV). More recently, our group has learned that SARS-CoV-2 main protease (Mpro) dimerization and activity can also be regulated through reversible glutathionylation of Cys300. Overall, these studies reveal a conserved way for viruses to regulate viral polyprotein processing particularly during oxidative stress and reveal novel targets for the development of inhibitors of dimerization and activity of these important viral enzyme targets.
| S-EPMC9598996 | biostudies-literature
Project description:The escape mutant of HIV-1 protease (PR) containing 20 mutations (PR20) undergoes efficient polyprotein processing even in the presence of clinical protease inhibitors (PIs). PR20 shows >3 orders of magnitude decreased affinity for PIs darunavir (DRV) and saquinavir (SQV) relative to PR. Crystal structures of PR20 crystallized with yttrium, substrate analogue p2-NC, DRV, and SQV reveal three distinct conformations of the flexible flaps and diminished interactions with inhibitors through the combination of multiple mutations. PR20 with yttrium at the active site exhibits widely separated flaps lacking the usual intersubunit contacts seen in other inhibitor-free dimers. Mutations of residues 35-37 in the hinge loop eliminate interactions and perturb the flap conformation. Crystals of PR20/p2-NC contain one uninhibited dimer with one very open flap and one closed flap and a second inhibitor-bound dimer in the closed form showing six fewer hydrogen bonds with the substrate analogue relative to wild-type PR. PR20 complexes with PIs exhibit expanded S2/S2' pockets and fewer PI interactions arising from coordinated effects of mutations throughout the structure, in agreement with the strikingly reduced affinity. In particular, insertion of the large aromatic side chains of L10F and L33F alters intersubunit interactions and widens the PI binding site through a network of hydrophobic contacts. The two very open conformations of PR20 as well as the expanded binding site of the inhibitor-bound closed form suggest possible approaches for modifying inhibitors to target extreme drug-resistant HIV.
| S-EPMC3328860 | biostudies-literature
Project description:UnlabelledResistance 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.ImportanceResistance 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.
| S-EPMC4054462 | biostudies-literature
Project description:Antiviral inhibitors of HIV-1 protease are a notable success of structure-based drug design and have dramatically improved AIDS therapy. Analysis of the structures and activities of drug resistant protease variants has revealed novel molecular mechanisms of drug resistance and guided the design of tight-binding inhibitors for resistant variants. The plethora of structures reveals distinct molecular mechanisms associated with resistance: mutations that alter the protease interactions with inhibitors or substrates; mutations that alter dimer stability; and distal mutations that transmit changes to the active site. These insights will inform the continuing design of novel antiviral inhibitors targeting resistant strains of HIV.
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Project description:In the last years, imaging has played a key role in the diagnosis and monitoring and critical illness, including acute respiratory distress syndrome (ARDS). Chest X-ray (CXR) and computed tomography (CT) are the conventional techniques most performed in the critically ill patients, the latter being the gold standard to assess lung aeration in ARDS patients. In addition, two bedside techniques are now gaining popularity alongside the conventional ones: lung ultrasound (LUS) and electrical impedance tomography (EIT). These techniques do not involve the use of ionizing radiations, are non-invasive and relatively easy to use, and are under extensive investigation as a complement, and for some application a substitution of conventional techniques. At last, positron emission tomography (PET) and magnetic resonance imaging (MRI) can provide functional information on the lung and respiratory function, and are increasingly used in research to improve the understanding of the pathophysiological mechanisms underlying ARDS. The purpose of this review is to give an up-to-date overview of the conventional and emerging imaging techniques available the diagnosis and management of patients with ARDS.
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