Analysis of local molecular interaction networks underlying HIV-1 resistance to reverse transcriptase inhibitors.
(English)Manuscript (preprint) (Refereed)
Rapid emergence of drug resistant HIV-1 mutants is the ma jor cause of many treatment failures. A number of individual drug resistance mutations is known but the way they interact to create resistance often remains an open question. So far this question could be answered in an experimental way only. Here we apply a novel Monte Carlo feature selection-based approach to uncover molecular interaction networks that form HIV-1 reverse transcriptase (RT) resistome. By considering mutation-induced changes in the physicochemical properties of mutating amino acids, we were able to elucidate interaction networks leading to resistance to six anti-viral drugs. We selected signiﬁcant properties (p − value <= 0.05) and analyzed the networks of the 20% strongest interdependencies between them. The topology of each network was validated by mapping it onto the 3D structure of RT and by relating the ﬁndings to the existing knowledge. The method can be easily applied to a wide range of similar problems in the domain of proteomics.
HIV-1 resistance, interaction networks, resistome, MCFS-ID, feature selection, interdependency discovery
Bioinformatics and Systems Biology
Research subject Biopharmaceutics; Biology, with specialization in structural biology
IdentifiersURN: urn:nbn:se:uu:diva-109835OAI: oai:DiVA.org:uu-109835DiVA: diva2:274119