Prediksi Efektivitas Efavirenz terhadap Berbagai Human-Infecting Retrovirus secara In-Silico Menggunakan Tools Bioinformatika dan Kimia Medisinal - Billgerd Tjengal; Ade Fany Safitri; Julio Jonathan Gilbert Alexis; Nadira Rahmatunisa; Sigit Nur Pratama (Berkala Ilmiah Mahasiswa Farmasi Indonesia, 2019)
Introduction: One strategy for HIV-1 (retroviridae) infection therapy is using NNRTI (non-nucleoside reverse transcriptase inhibitor) to suppress viral replication by binding to the reverse transcriptase (RT-ase) enzyme. One drug in this class is Efavirenz (EFV). Based on the good effectivity of EFV in HIV-1, it is suspected that EFV also has activity against HIV-2 and HTLV. This study aims to determine the activity of EFV in the human-infecting retroviruses such as HIV-2, HTLV-1, and HTLV-2. Methods: This study uses Bioinformatics and Medicinal Chemistry tools such as, phylogenetic tree construction, pairwise sequence alignment, looking for RT-ase motifs and domains, predicting secondary structures, modelling 3D RT-ase structures, docking, and predicting hydrophobicity with Kyte-Doolittle Hydropathy Plot. Result: There is a common ancestor of the four viruses according to the constructed phylogenetic tree. There are also RT_like Superfamily domains at HIV-2 and HTLV-1. The similarity and identity value, and results of HTLV-1 and HTLV-2 RT-ase structural modeling do not give good results. Binding energy value of EFV to HIV-2 RT-ase is higher than HIV-1 RT-ase. Conclusion: EFV is not effective against HIV-2, HTLV-1 and HTLV-2