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Related Concept Videos

Retrovirus Life Cycles01:10

Retrovirus Life Cycles

Retroviruses have a single-stranded RNA genome that undergoes a special form of replication. Once the retrovirus has entered the host cell, an enzyme called reverse transcriptase synthesizes double-stranded DNA from the retroviral RNA genome. This DNA copy of the genome is then integrated into the host’s genome inside the nucleus via an enzyme called integrase. Consequently, the retroviral genome is transcribed into RNA whenever the host’s genome is transcribed, allowing the retrovirus to...
Viral Mutations00:36

Viral Mutations

A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material for adaptive...

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Related Experiment Video

Updated: May 12, 2026

An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
19:57

An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings

Published on: March 30, 2014

Forecasting drug resistant HIV protease evolution.

Manu Aggarwal1, Vipul Periwal1

  • 1National Institutes of Health, Bethesda, MD.

Biorxiv : the Preprint Server for Biology
|June 26, 2025
PubMed
Summary
This summary is machine-generated.

Forecasting drug resistance in human immunodeficiency virus (HIV) is crucial. A new model predicts viral evolution and identifies key mutations, suggesting Atazanavir (ATV) and Ritonavir (RTV) combination therapy is least resistant.

Keywords:
HIV treatmentdrug resistanceprotein evolutionstatistical physics

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Last Updated: May 12, 2026

An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
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Published on: March 30, 2014

Rapid Screening of HIV Reverse Transcriptase and Integrase Inhibitors
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Published on: April 10, 2014

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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

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Area of Science:

  • Computational biology
  • Virology
  • Drug resistance studies

Background:

  • Protease inhibitors (PIs) are vital for human immunodeficiency virus (HIV) treatment.
  • Drug-resistant strains emerge, compromising PI efficacy.
  • Forecasting drug resistance is essential for effective treatment strategies.

Purpose of the Study:

  • To develop a probabilistic model for inferring epistatic interactions and predicting viral evolution.
  • To identify critical mutations driving drug resistance.
  • To evaluate the drug resistance of different PI combination therapies.

Main Methods:

  • Developed a probabilistic large-deviation model to infer epistatic interactions.
  • Simulated stochastic evolutionary paths weighted by mutation transition probabilities.
  • Trained classification models on in vitro susceptibility data to infer drug resistance.
  • Predicted drug resistance along simulated evolutionary paths.

Main Results:

  • Low-probability mutations are necessary for viral populations to evolve diverse, fit genotypes.
  • The combination therapy of Atazanavir (ATV) and Ritonavir (RTV) showed the least drug resistance.
  • The model predicted known primary and secondary PI-resistant mutations without prior knowledge.

Conclusions:

  • The developed model effectively infers mechanistic relationships from sparse sequence data.
  • The model can predict drug resistance and identify critical mutations in viral evolution.
  • The ATV/RTV combination therapy is predicted to be the most effective against drug resistance.