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HIV Reverse Transcriptase

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Use of Dried Plasma Spots for HIV-1 Viral Load Determination and Drug Resistance Genotyping in Mexican Patients.

BioMed research international 26779533
Monitoring antiretroviral therapy using measurements of viral load (VL) and the genotyping of resistance mutations is not routinely performed in low- to middle-income countries because of the high costs of the commercial assays that are used. The ana...
Adult Dried Blood Spot Testing Drug Resistance, Viral Female Genotype HIV Infections HIV Protease HIV Reverse Transcriptase HIV-1 Humans Male Mexico Mutation Phylogeny pol Gene Products, Human Immunodeficiency Virus RNA, Viral Viral Load
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Improving fold resistance prediction of HIV-1 against protease and reverse transcriptase inhibitors using artificial neural networks.

BMC bioinformatics 28810826
BACKGROUND: Drug resistance in HIV treatment is still a worldwide problem. Predicting resistance to antiretrovirals (ARVs) before starting any treatment is important. Prediction accuracy is essential, as low-accuracy predictions increase the risk of ...
Databases, Factual Drug Resistance, Viral HIV Infections HIV Protease HIV Protease Inhibitors HIV Reverse Transcriptase HIV-1 Humans Neural Networks, Computer Reverse Transcriptase Inhibitors
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A Machine Learning Approach for Predicting HIV Reverse Transcriptase Mutation Susceptibility of Biologically Active Compounds.

Journal of chemical information and modeling 29953819
HIV resistance emerging against antiretroviral drugs represents a great threat to the continued prolongation of the lifespans of HIV-infected patients. Therefore, methods capable of predicting resistance susceptibility in the development of compounds...
Bayes Theorem Drug Discovery Drug Resistance, Viral HIV Infections HIV Reverse Transcriptase HIV-1 Humans Machine Learning Models, Biological Point Mutation Reverse Transcriptase Inhibitors
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Multiple Machine Learning Comparisons of HIV Cell-based and Reverse Transcriptase Data Sets.

Molecular pharmaceutics 30779585
The human immunodeficiency virus (HIV) causes over a million deaths every year and has a huge economic impact in many countries. The first class of drugs approved were nucleoside reverse transcriptase inhibitors. A newer generation of reverse transcr...
Anti-HIV Agents Bayes Theorem Databases, Factual Decision Trees Drug Discovery HIV HIV Infections HIV Reverse Transcriptase Humans Machine Learning Neural Networks, Computer Reverse Transcriptase Inhibitors Support Vector Machine
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Using machine learning and big data to explore the drug resistance landscape in HIV.

PLoS computational biology 34437532
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...
Africa Anti-HIV Agents Bayes Theorem Big Data Computational Biology Databases, Genetic Decision Trees Drug Resistance, Viral Epistasis, Genetic Genes, Viral HIV Infections HIV Reverse Transcriptase HIV-1 Humans Logistic Models Models, Genetic Mutation Supervised Machine Learning United Kingdom
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Pre-training strategy for antiviral drug screening with low-data graph neural network: A case study in HIV-1 K103N reverse transcriptase.

Journal of computational chemistry 39434589
Graph neural networks (GNN) offer an alternative approach to boost the screening effectiveness in drug discovery. However, their efficacy is often hindered by limited datasets. To address this limitation, we introduced a robust GNN training framework...
Anti-HIV Agents Drug Evaluation, Preclinical HIV Reverse Transcriptase HIV-1 Humans Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Neural Networks, Computer Reverse Transcriptase Inhibitors
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