3D-QSAR, molecular docking and in silico ADMET studies of propiophenone derivatives with anti-HIV-1 protease activity

• Published in: Structural chemistry Vol. 32; no. 6; pp. 2341 - 2353
• Main Authors: Jovanović, Milan, Turković, Nemanja, Ivković, Branka, Vujić, Zorica, Nikolić, Katarina, Grubišić, Sonja
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.12.2021; Springer Nature B.V
• Subjects: Charge density; Chemistry; Chemistry and Materials Science; Computer Applications in Chemistry; Density functional theory; HIV; Human immunodeficiency virus; Molecular docking; Molecular orbitals; Original Research; Physical Chemistry; Protease; Protease inhibitors; Theoretical and Computational Chemistry; HIV/AIDS; Quantitative structure–activity relationship(s) (QSAR); Protease(s); HOMO-LUMO; Computer-aided drug design; Computational ADME; Molecular docking
• ISSN: 1040-0400; 1572-9001
• DOI: 10.1007/s11224-021-01810-1

HIV protease inhibitors are one of the most important agents for the treatment of HIV infection. In this work, molecular modeling studies combining 3D-QSAR, molecular docking, MESP, HOMO, and LUMO energy calculations were performed on propiophenone derivatives to explore structure activity relationships and structural requirements for the inhibitory activity. The aim of this study was to create a field point–based 3D-QSAR (3D-Quantitative structure-activity relationship) model by using chalcone structures with anti-HIV-1 protease activity from our previous study and to design new potentially more potent and safer inhibitors. The developed model showed acceptable predictive and descriptive capability as represented by standard statistical parameters R 2 (0.94) and Q 2 (0.59). High correlation between experimental and predicted activities of training set is noticed. All compounds fit into the defined applicability domain. The derived pharmacophoric features were further supported by MESP and Mulliken charge analysis using density functional theory. Statistically significant variables from 3D-QSAR were used to define key structural characteristics which enhance anti-HIV-1 protease activity. This information has been used to design new structures with anti-HIV-1 protease activity. Docking studies were conducted to understand the interactions in predicted compounds. All the compounds were subjected to in silico ADMET profiling in order to select the best potential drug candidates.