Structural studies on molecular mechanisms of Nelfinavir resistance caused by non-active site mutation V77I in HIV-1 protease

First Assessment of Acquired HIV-1 Drug Resistance and Mutation Patterns in Suriname

HIV drug resistance testing is fundamental in clinical patient management, but data on HIV-1 drug-resistant mutations (DRMs) is scarce in the Caribbean and in Suriname limited to one survey on transmitted resistance. The aim of this study was to address this gap, to gain insight in acquired HIV drug resistance (ADR) prevalence and mutation patterns, and to improve HIV-1 treatment outcome of people living with HIV (PLHIV) in Suriname. A prospective cross-sectional study was conducted from July 2018 through January 2019 among treatment-experienced PLHIV (n = 72), with either treatment failure or antiretroviral therapy restart. Genotypic drug resistance testing was performed and DRM impact on drug effectiveness was examined. Genotypic drug resistance testing revealed 97.2% HIV-1 subtype B, 2.8% B/D recombinants and a ADR prevalence of 63.2% in treatment failure patients, with a predominance of nonnucleoside reverse transcriptase inhibitor (NNRTI) mutations. The most common DRMs were M184V (23.6%) and K103N (18.8%). A high level of non-DRM polymorphisms was observed in both the reverse transcriptase (RT) and protease (PR) gene. Interesting deviations from the existing mutation datasets were noted at position E248 and R83 of the RT gene and L63 and V77 in the PR gene. Full susceptibility to all examined drugs was 54.2%, while high-level drug resistance was estimated at 37.5%, which seems promising for treatment outcomes for PLHIV in Suriname, although cross-resistance to next-generation NNRTIs was already estimated for nearly a quarter of the patients. The meager 2.9% of PR DRMs rendered protease inhibitors as an effective rescue HIV-1 treatment.

Identification of an Antiretroviral Small Molecule That Appears To Be a Host-Targeting Inhibitor of HIV-1 Assembly

Given the projected increase in multidrug-resistant HIV-1, there is an urgent need for development of antiretrovirals that act on virus life cycle stages not targeted by drugs currently in use. Host-targeting compounds are of particular interest because they can offer a high barrier to resistance. Here, we report identification of two related small molecules that inhibit HIV-1 late events, a part of the HIV-1 life cycle for which potent and specific inhibitors are lacking. This chemotype was discovered using cell-free protein synthesis and assembly systems that recapitulate intracellular host-catalyzed viral capsid assembly pathways. These compounds inhibit replication of HIV-1 in human T cell lines and peripheral blood mononuclear cells, and are effective against a primary isolate. They reduce virus production, likely by inhibiting a posttranslational step in HIV-1 Gag assembly. Notably, the compound colocalizes with HIV-1 Gag in situ; however, unexpectedly, selection experiments failed to identify compound-specific resistance mutations in gag or pol, even though known resistance mutations developed upon parallel nelfinavir selection. Thus, we hypothesized that instead of binding to Gag directly, these compounds localize to assembly intermediates, the intracellular multiprotein complexes containing Gag and host factors that form during immature HIV-1 capsid assembly. Indeed, imaging of infected cells shows compound colocalized with two host enzymes found in assembly intermediates, ABCE1 and DDX6, but not two host proteins found in other complexes. While the exact target and mechanism of action of this chemotype remain to be determined, our findings suggest that these compounds represent first-in-class, host-targeting inhibitors of intracellular events in HIV-1 assembly.IMPORTANCE The success of antiretroviral treatment for HIV-1 is at risk of being undermined by the growing problem of drug resistance. Thus, there is a need to identify antiretrovirals that act on viral life cycle stages not targeted by drugs in use, such as the events of HIV-1 Gag assembly. To address this gap, we developed a compound screen that recapitulates the intracellular events of HIV-1 assembly, including virus-host interactions that promote assembly. This effort led to the identification of a new chemotype that inhibits HIV-1 replication at nanomolar concentrations, likely by acting on assembly. This compound colocalized with Gag and two host enzymes that facilitate capsid assembly. However, resistance selection did not result in compound-specific mutations in gag, suggesting that the chemotype does not directly target Gag. We hypothesize that this chemotype represents a first-in-class inhibitor of virus production that acts by targeting a virus-host complex important for HIV-1 Gag assembly.

Gag-protease coevolution shapes the outcome of lopinavir-inclusive treatment regimens in chronically infected HIV-1 subtype C patients

MOTIVATION

Commonly, protease inhibitor failure is characterized by the development of multiple protease resistance mutations (PRMs). While the impact of PRMs on therapy failure are understood, the introduction of Gag mutations with protease remains largely unclear.

RESULTS

Here, we utilized phylogenetic analyses and Bayesian network learning as tools to understand Gag-protease coevolution and elucidate the pathways leading to Lopinavir failure in HIV-1 subtype C infected patients. Our analyses indicate that while PRMs coevolve in response to drug selection pressure within protease, the Gag mutations added to the existing network while specifically interacting with known Lopinavir failure PRMs. Additionally, the selection of mutations at specific positions in Gag-protease suggests that these coevolving mutational changes occurs to maintain structural integrity during Gag cleavage.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Reviewing HIV-1 Gag Mutations in Protease Inhibitors Resistance: Insights for Possible Novel Gag Inhibitor Designs

HIV protease inhibitors against the viral protease are often hampered by drug resistance mutations in protease and in the viral substrate Gag. To overcome this drug resistance and inhibit viral maturation, targeting Gag alongside protease rather than targeting protease alone may be more efficient. In order to successfully inhibit Gag, understanding of its drug resistance mutations and the elicited structural changes on protease binding needs to be investigated. While mutations on Gag have already been mapped to protease inhibitor resistance, there remain many mutations, particularly the non-cleavage mutations, that are not characterized. Through structural studies to unravel how Gag mutations contributes to protease drug resistance synergistically, it is thus possible to glean insights to design novel Gag inhibitors. In this review, we discuss the structural role of both novel and previously reported Gag mutations in PI resistance, and how new Gag inhibitors can be designed.

In silico approaches for investigating the binding propensity of apigenin and luteolin against class I HDAC isoforms

AIM

Aberrant activity of class I histone deacetylases (HDACs) has strong implications for various cancers. Targeting these HDACs with synthetic HDAC inhibitors has shown significant side effects such as atrial fibrillation and QT prolongation emphasizing the need of natural inhibitors as substitutes to synthetic ones.

RESULTS

The binding propensity of the two plant-derived inhibitors apigenin and luteolin towards class I HDAC isoforms was checked using extra-precision molecular docking and implicit solvation MMGBSA. Apigenin showed a superior binding affinity against these isoforms as compared to luteolin. Both inhibitors docked stable to the binding pocket of these HDACs as determined by molecular dynamics simulation study.

CONCLUSION

Apigenin and luteolin may serve as substitutes to synthetic inhibitors for effective HDAC based anticancer therapy.

Prediction of HIV Drug Resistance by Combining Sequence and Structural Properties

Drug resistance is a major obstacle faced by therapist in treating HIV infected patients. The reason behind these phenomena is either protein mutation or the changes in gene expression level that induces resistance to drug treatments. These mutations affect the drug binding activity, hence resulting in failure of treatment. Therefore, it is necessary to conduct resistance testing in order to carry out HIV effective therapy. This study combines both sequence and structural features for predicting HIV resistance by applying SVM and Random Forests classifiers. The model was tested on the mutants of HIV-1 protease and reverse transcriptase. Taken together the features we have used in our method, total contact energies among multiple mutations have a strong impact in predicting resistance as they are crucial in understanding the interactions of HIV mutants. The combination of sequence-structure features offers high accuracy with support vector machines as compared to Random Forests classifier. Both single and acquisition of multiple mutations are important in predicting HIV resistance to certain drug treatments. We have discovered the practicality of these features; hence, these can be used in the future to predict resistance for other complex diseases.

Drug targeted virtual screening and molecular dynamics of LipU protein of Mycobacterium tuberculosis and Mycobacterium leprae

The lipolytic protein LipU was conserved in mycobacterium sp. including M. tuberculosis (MTB LipU) and M. leprae (MLP LipU). The MTB LipU was identified in extracellular fraction and was reported to be essential for the survival of mycobacterium. Therefore to address the problem of drug resistance in pathogen, LipU was selected as a drug target and the viability of finding out some FDA approved drugs as LipU inhibitors in both the cases was explored. Three-dimensional (3D) model structures of MTB LipU and MLP LipU were generated and stabilized through molecular dynamics (MD). FDA approved drugs were screened against these proteins. The result showed that the top-scoring compounds for MTB LipU were Diosmin, Acarbose and Ouabain with the Glide XP score of -12.8, -11.9 and -11.7 kcal/mol, respectively, whereas for MLP LipU protein, Digoxin (-9.2 kcal/mol), Indinavir (-8.2 kcal/mol) and Travoprost (-8.2 kcal/mol) showed highest affinity. These drugs remained bound in the active site pocket of MTB LipU and MLP LipU structure and interaction grew stronger after dynamics. RMSD, RMSF and Rg were found to be persistent throughout the simulation period. Hydrogen bonds along with large number of hydrophobic interactions stabilized the complex structures. Binding free energies obtained through Prime/MM-GBSA were found in the significant range from -63.85 kcal/mol to -34.57 kcal/mol for MTB LipU and -71.33 kcal/mol to -23.91 kcal/mol for MLP LipU. The report suggested high probability of these drugs to demolish the LipU activity and could be probable drug candidates to combat TB and leprosy disease.

Insight into the inhibitor discrimination by FLT3 F691L

Fms-like tyrosine kinase 3 (FLT3) belongs to the receptor tyrosine kinase family and expressed in hematopoietic progenitor cells. FLT3 gene mutations are reported in ~30% of acute myeloid leukemia cases. FLT3 kinase domain mutation F691L is one of the common causes of acquired resistance to the FLT3 inhibitors including quizartinib. MZH29 and crenolanib were previously reported to inhibit FLT3 F691L. However, crenolanib was reported for the moderate inhibition. We found that Glu661and Asp829 were the most significant residues to target the FLT3 F691L which contribute most significantly to the binding energy with MZH29 and crenolanib. These interactions were found absent with quizartinib. Further free energy landscape analysis revealed that FLT3 F691L bound to MZH29 and crenolanib was more stable as compared to quizartinib.

Structural investigations on mechanism of lapatinib resistance caused by HER-2 mutants

HER-2 belongs to the human epidermal growth factor receptor (HER) family. Via different signal transduction pathways, HER-2 regulates normal cell proliferation, survival, and differentiation. Recently, it was reported that MCF10A, BT474, and MDA-MB-231 cells bearing the HER2 K753E mutation were resistant to lapatinib. Present study revealed that HER-2 mutant K753E showed some contrasting behaviour as compared to wild, L768S and V773L HER-2 in complex with lapatinib while similar to previously known lapatinib resistant L755S HER-2 mutant. Lapatinib showed stable but reverse orientation in binding site of K753E and the highest binding energy among studied HER2-lapatinib complexes but slightly lesser than L755S mutant. Results indicate that K753E has similar profile as L755S mutant for lapatinib. The interacting residues were also found different from other three studied forms as revealed by free energy decomposition and ligplot analysis.

A decade of viral mutations and associated drug resistance in a population of HIV-1+ Puerto Ricans: 2002-2011

Puerto Rico has one of the highest rates of HIV/AIDS seen for any US state or territory, and antiretroviral therapy has been a mainstay of efforts to mitigate the HIV/AIDS public health burden on the island. We studied the evolutionary dynamics of HIV-1 mutation and antiretroviral drug resistance in Puerto Rico by monitoring the population frequency of resistance-associated mutations from 2002 to 2011. Whole blood samples from 4,475 patients were analyzed using the TRUGENE HIV-1 Genotyping Kit and OpenGene DNA Sequencing System in the Immunoretrovirus Research Laboratory at Universidad Central del Caribe. Results show that 64.0% of female and 62.9% of male patients had HIV-1 mutations that confer resistance to at least one antiretroviral medication. L63P and M184V were the dominant mutations observed for the protease (PRO) and reverse transcriptase (RT) encoding genes, respectively. Specific resistance mutations, along with their associated drug resistance profiles, can be seen to form temporal clusters that reveal a steadily changing landscape of resistance trends over time. Both women and men showed resistance mutations for an average of 4.8 drugs over the 10-year period, further underscoring the strong selective pressure exerted by antiretrovirals along with the rapid adaptive response of HIV. Nevertheless, both female and male patients showed a precipitous decrease for overall drug resistance, and for PRO mutations in particular, over the entire course of the study, with the most rapid decrease in frequency seen after 2006. The reduced HIV-1 mutation and drug resistance trends that we observed are consistent with previous reports from multi-year studies conducted around the world. Reduced resistance can be attributed to the use of more efficacious antiretroviral drug therapy, including the introduction of multi-drug combination therapies, which limited the ability of the virus to mount rapid adaptive responses to antiretroviral selection pressure.

Dynamics of fluoroquinolones induced resistance in DNA gyrase of Mycobacterium tuberculosis

DNA gyrase is a validated target of fluoroquinolones which are key components of multidrug resistance tuberculosis (TB) treatment. Most frequent occurring mutations associated with high level of resistance to fluoroquinolone in clinical isolates of TB patients are A90V, D94G, and A90V-D94G (double mutant [DM]), present in the larger subunit of DNA Gyrase. In order to explicate the molecular mechanism of drug resistance corresponding to these mutations, molecular dynamics (MD) and mechanics approach was applied. Structure-based molecular docking of complex comprised of DNA bound with Gyrase A (large subunit) and Gyrase C (small subunit) with moxifloxacin (MFX) revealed high binding affinity to wild type with considerably high Glide XP docking score of -7.88 kcal/mol. MFX affinity decreases toward single mutants and was minimum toward the DM with a docking score of -3.82 kcal/mol. Docking studies were also performed against 8-Methyl-moxifloxacin which exhibited higher binding affinity against wild and mutants DNA gyrase when compared to MFX. Molecular Mechanics/Generalized Born Surface Area method predicted the binding free energy of the wild, A90V, D94G, and DM complexes to be -55.81, -25.87, -20.45, and -12.29 kcal/mol, respectively. These complexes were further subjected to 30 ns long MD simulations to examine significant interactions and conformational flexibilities in terms of root mean square deviation, root mean square fluctuation, and strength of hydrogen bond formed. This comparative drug interaction analysis provides systematic insights into the mechanism behind drug resistance and also paves way toward identifying potent lead compounds that could combat drug resistance of DNA gyrase due to mutations.

Dissecting the role of mutations in chymase inhibition: Free energy and decomposition analysis

Chymase enzyme abundantly found in secretory granules of mast cells and catalyzes the hydrolysis of peptide bonds to generate angiotensin II via hydrolysis of angiotensin I and also activates transforming growth factor-b and MMP-9. MMP-9 and TGF-b have significant role in tissue inflammation and fibrosis. In present study, we investigated that Lys192Met mutation leads to a higher loss in binding energy of inhibitors than mutation Arg143Gln in chymase. The energy decomposition revealed that the contributing residues are almost same in all the forms with some change in energy value. All the results pointing that arginine and lysine residues of chymase play the most significant role in inhibitor binding revealed by energy decomposition. The Lys40, Arg90, Lys192 and Arg217 are found to be most prominent residues in two different inhibitor systems but the role of other lysine and arginine also important as they also have significant contribution in the total binding energy.

Computational Screening and Exploration of Disease-Associated Genes in Alzheimer's Disease

Alzheimer's is a neurodegenerative disease affecting large populations worldwide characterized mainly by progressive loss of memory along with various other symptoms. The foremost cause of the disease is still unclear, however various mechanisms have been proposed to cause the disease that include amyloid hypothesis, tau hypothesis, and cholinergic hypothesis in addition to genetic factors. Various genes have been known to be involved which are APOE, PSEN1, PSEN2, and APP among others. In the present study, we have used computational methods to examine the pathogenic effects of non-synonymous single nucleotide polymorphisms (SNPs) associated with ABCA7, CR1, MS4A6A, CD2AP, PSEN1, PSEN2, and APP genes. The SNPs were obtained from dbSNP database followed by identification of deleterious SNPs and prediction of their functional impact. Prediction of disease-associated mutations was performed and the impact of the mutations on the stability of the protein was carried out. To study the structural significance of the computationally prioritized mutations on the proteins, molecular dynamics simulation studies were carried out. On analysis, the SNPs with IDs rs76282929 ABCA7; CR1 rs55962594; MS4A6A rs601172; CD2AP rs61747098; PSEN1 rs63750231, rs63750265, rs63750526, rs63750577, rs63750687, rs63750815, rs63750900, rs63751037, rs63751163, rs63751399; PSEN2 rs63749851; and APP rs63749964, rs63750066, rs63750734, and rs63751039 were predicted to be deleterious and disease-associated having significant structural impact on the proteins. The current study proposes a precise computational methodology for the identification of disease-associated SNPs. J. Cell. Biochem. 118: 1471-1479, 2017. © 2016 Wiley Periodicals, Inc.

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.

HIV-1 drug resistance mutations emerging on darunavir therapy in PI-naive and -experienced patients in the UK

BACKGROUND

Darunavir is considered to have a high genetic barrier to resistance. Most darunavir-associated drug resistance mutations (DRMs) have been identified through correlation of baseline genotype with virological response in clinical trials. However, there is little information on DRMs that are directly selected by darunavir in clinical settings.

OBJECTIVES

We examined darunavir DRMs emerging in clinical practice in the UK.

PATIENTS AND METHODS

Baseline and post-exposure protease genotypes were compared for individuals in the UK Collaborative HIV Cohort Study who had received darunavir; analyses were stratified for PI history. A selection analysis was used to compare the evolution of subtype B proteases in darunavir recipients and matched PI-naive controls.

RESULTS

Of 6918 people who had received darunavir, 386 had resistance tests pre- and post-exposure. Overall, 2.8% (11/386) of these participants developed emergent darunavir DRMs. The prevalence of baseline DRMs was 1.0% (2/198) among PI-naive participants and 13.8% (26/188) among PI-experienced participants. Emergent DRMs developed in 2.0% of the PI-naive group (4 mutations) and 3.7% of the PI-experienced group (12 mutations). Codon 77 was positively selected in the PI-naive darunavir cases, but not in the control group.

CONCLUSIONS

Our findings suggest that although emergent darunavir resistance is rare, it may be more common among PI-experienced patients than those who are PI-naive. Further investigation is required to explore whether codon 77 is a novel site involved in darunavir susceptibility.

Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes

Background

Alzheimer’s disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheimer’s is still unclear, however one of the other major factors involved in AD pathogenesis are the genetic factors and around 70 % risk of the disease is assumed to be due to the large number of genes involved. Although genetic association studies have revealed a number of potential AD susceptibility genes, there still exists a need for identification of unidentified AD-associated genes and therapeutic targets to have better understanding of the disease-causing mechanisms of Alzheimer’s towards development of effective AD therapeutics.

Results

In the present study, we have used machine learning approach to identify candidate AD associated genes by integrating topological properties of the genes from the protein-protein interaction networks, sequence features and functional annotations. We also used molecular docking approach and screened already known anti-Alzheimer drugs against the novel predicted probable targets of AD and observed that an investigational drug, AL-108, had high affinity for majority of the possible therapeutic targets. Furthermore, we performed molecular dynamics simulations and MM/GBSA calculations on the docked complexes to validate our preliminary findings.

Conclusions

To the best of our knowledge, this is the first comprehensive study of its kind for identification of putative Alzheimer-associated genes using machine learning approaches and we propose that such computational studies can improve our understanding on the core etiology of AD which could lead to the development of effective anti-Alzheimer drugs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3108-1) contains supplementary material, which is available to authorized users.

Role of Conformational Motions in Enzyme Function: Selected Methodologies and Case Studies

It is now common knowledge that enzymes are mobile entities relying on complex atomic-scale dynamics and coordinated conformational events for proper ligand recognition and catalysis. However, the exact role of protein dynamics in enzyme function remains either poorly understood or difficult to interpret. This mini-review intends to reconcile biophysical observations and biological significance by first describing a number of common experimental and computational methodologies employed to characterize atomic-scale residue motions on various timescales in enzymes, and second by illustrating how the knowledge of these motions can be used to describe the functional behavior of enzymes and even act upon it. Two biologically relevant examples will be highlighted, namely the HIV-1 protease and DNA polymerase β enzyme systems.