AIMC Topic: Drug Resistance, Viral

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Enhancing the understandings on SARS-CoV-2 main protease (M) mutants from molecular dynamics and machine learning.

International journal of biological macromolecules Apr 10, 2025
While star drugs like Paxlovid have shown remarkable performance in combating SARS-CoV-2, we still face serious challenges such as viral mutants and resistance. In this study, we employ a computational framework combining molecular dynamics (MD) simu...
Humans Machine Learning Molecular Dynamics Simulation Drug Resistance, Viral Protease Inhibitors Coronavirus 3C Proteases COVID-19 SARS-CoV-2 Antiviral Agents Mutation
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A graph neural network-based model with out-of-distribution robustness for enhancing antiretroviral therapy outcome prediction for HIV-1.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jan 10, 2025
Predicting the outcome of antiretroviral therapies (ART) for HIV-1 is a pressing clinical challenge, especially when the ART includes drugs with limited effectiveness data. This scarcity of data can arise either due to the introduction of a new drug ...
Drug Resistance, Viral Graph Neural Networks Treatment Outcome Anti-Retroviral Agents HIV-1 Humans Neural Networks, Computer HIV Infections Anti-HIV Agents
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Using machine learning and big data to explore the drug resistance landscape in HIV.

PLoS computational biology Aug 26, 2021
Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are commonly transmitted to naive patients. The standard approach to reveal new DRMs is to test for significant frequency differences of mutations between treated and naive...
Anti-HIV Agents Computational Biology Logistic Models Models, Genetic Humans Africa Big Data HIV Infections United Kingdom Epistasis, Genetic HIV Reverse Transcriptase Genes, Viral Mutation Supervised Machine Learning Databases, Genetic HIV-1 Decision Trees Drug Resistance, Viral Bayes Theorem
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Predicting HIV drug resistance using weighted machine learning method at target protein sequence-level.

Molecular diversity Jul 9, 2021
Acquired immune deficiency syndrome (AIDS) is a fatal disease caused by human immunodeficiency virus (HIV). Although 23 different drugs have been available, the treatment of AIDS remains challenging because the virus mutates very quickly which can le...
HIV Amino Acid Sequence Drug Resistance, Viral Viral Proteins Support Vector Machine Dose-Response Relationship, Drug Mutation Humans Machine Learning Algorithms Databases, Factual Reproducibility of Results Anti-HIV Agents Models, Theoretical
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Deciphering Complex Mechanisms of Resistance and Loss of Potency through Coupled Molecular Dynamics and Machine Learning.

Journal of chemical theory and computation Mar 30, 2021
Drug resistance threatens many critical therapeutics through mutations in the drug target. The molecular mechanisms by which combinations of mutations, especially those remote from the active site, alter drug binding to confer resistance are poorly u...
HIV Protease Inhibitors Mutation Molecular Dynamics Simulation Drug Resistance, Viral HIV Protease Machine Learning
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Evolution of drug resistance in HIV protease.

BMC bioinformatics Dec 30, 2020
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...
HIV Protease HIV Protease Inhibitors Humans Machine Learning Genotype Phenotype Evolution, Molecular HIV Infections HIV-1 Drug Resistance, Viral
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Drug Resistance Prediction Using Deep Learning Techniques on HIV-1 Sequence Data.

Viruses May 19, 2020
The fast replication rate and lack of repair mechanisms of human immunodeficiency virus (HIV) contribute to its high mutation frequency, with some mutations resulting in the evolution of resistance to antiretroviral therapies (ART). As such, studying...
Humans Neural Networks, Computer Phylogeny Deep Learning Mutation Anti-Retroviral Agents HIV-1 Drug Resistance, Viral HIV Infections Genotype Databases, Genetic
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Characterizing Protein-Ligand Binding Using Atomistic Simulation and Machine Learning: Application to Drug Resistance in HIV-1 Protease.

Journal of chemical theory and computation Jan 16, 2020
Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have provided detailed insights into their function. Comparing the results of such simulations for a few clo...
HIV Protease Inhibitors Hydrogen Bonding Static Electricity Monte Carlo Method Humans HIV-1 Machine Learning Ligands Drug Resistance, Viral HIV Protease Protein Binding Mutation Molecular Dynamics Simulation
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Accurate Prediction for Antibody Resistance of Clinical HIV-1 Isolates.

Scientific reports Oct 11, 2019
Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope glycoprotein (Env) have promising utility in prevention and treatment of HIV-1 infection, and several are currently undergoing clinical trials. Due to the high sequence diversity an...
HIV-1 Neutralization Tests Data Accuracy Humans env Gene Products, Human Immunodeficiency Virus Computer Simulation Drug Resistance, Viral HIV Antibodies Epitope Mapping Prognosis Binding Sites, Antibody Deep Learning Broadly Neutralizing Antibodies HIV Infections Immunoglobulin Idiotypes
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Data-driven supervised learning of a viral protease specificity landscape from deep sequencing and molecular simulations.

Proceedings of the National Academy of Sciences of the United States of America Dec 26, 2018
Biophysical interactions between proteins and peptides are key determinants of molecular recognition specificity landscapes. However, an understanding of how molecular structure and residue-level energetics at protein-peptide interfaces shape these l...
Energy Metabolism Models, Molecular Antiviral Agents Drug Resistance, Viral Substrate Specificity Serine Proteases Metabolomics Supervised Machine Learning Peptide Hydrolases Viral Nonstructural Proteins Structure-Activity Relationship Hepacivirus High-Throughput Nucleotide Sequencing
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