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

Abdul Ghafoor, Naeem; Kırboğa, Kevser; Baysal, Ömür; Süzek, Barış; Silme, Ragıp

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

Abdul Ghafoor N., Kırboğa K. K., Baysal Ö., Süzek B. E., Silme R. S.

Diğer, ss.1-28, 2023

Yayın Türü: Diğer Yayınlar / Diğer
Basım Tarihi: 2023
Sayfa Sayıları: ss.1-28
İstanbul Üniversitesi Adresli: Evet

Özet

In this study, we developed a process to identify an HIV-1 protein target and a new drug candidate. Genomic analysis was conducted on HIV-1 genomes to identify a viable target for disrupting viral replication and the reverse transcriptase enzyme. Based on MAUVE analysis, we selected the RNase H activity of the reverse transcriptase as the potential target due to its low mutation rate and high conservation. We screened 94,000 small molecule inhibitors and performed virtual screening. Molecular dynamics simulations and MM/PBSA were used to validate hit compounds' stability and binding free energy. Phomoarcherin B, known for its anticancer properties, emerged as the top candidate, showing potential as an inhibitor of HIV-1 reverse transcriptase RNase H activity.