Data mining and molecular dynamics analysis to detect HIV-1 reverse transcriptase RNase H activity inhibitor

Abstract

HIV-1 is a deadly virus that affects millions of people worldwide. In this study, we aimed to inhibit viral replication by targeting one of the HIV-1 proteins and identifying a new drug candidate. We used data mining and molecular dynamics methods on HIV-1 genomes. Based on MAUVE analysis, we selected the RNase H activity of the reverse transcriptase (R.T) enzyme as a potential target due to its low mutation rate and high conservation level. We screened about 94,000 small molecule inhibitors by virtual screening. We validated the hit compounds' stability and binding free energy through molecular dynamics simulations and MM/PBSA. Phomoarcherin B, known for its anticancer properties, emerged as the best candidate and showed potential as an HIV-1 reverse transcriptase RNase H activity inhibitor. This study presents a new target and drug candidate for HIV-1 treatment. However, in vitro and in vivo tests are required. Also, the effect of RNase H activity on viral replication and the interaction of Phomoarcherin B with other HIV-1 proteins should be investigated.