Framework Predicts HIV Protease Drug-Resistant Evolution
Aggarwal and Periwal (published January 27, 2026) develop a computational framework that learns coevolutionary transition probabilities from protease genotypes and predicts drug resistance using clinical resistance measurements. They simulate thousands of evolutionary trajectories to forecast persistent drug-resistant HIV protease genotypes, finding the Atazanavir+Ritonavir regimen least likely to induce resistance and identifying seven critical point mutations including L63P for Nelfinavir.
Scoring Rationale
Novel, peer-reviewed forecasting framework with actionable mutation predictions, limited by focus on protease-only evolution and dataset sparsity.
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