IDENTIFICATION OF NOVEL NCP7 INHIBITORS FOR HIV DRUG DISCOVERY USING LIGAND-BASED COMPUTATIONAL APPROACHES

Background: NCp7 is a nucleocapsid protein of HIV-1, a retrovirus causing AIDS in human beings. It is a small protein of 72 amino acids that plays an important role in being a chaperone protein involved in viral development. HIV has shown resistance to drugs engineered to treat its infections. Objectives: In this study, a Structure-Activity Relationship analysis of two distinct derivatives based on point pharmacophore was carried out to obtain an NCp7 inhibitor of better performance. Materials and Methods: A Pharmacophore and 3D-QSAR modeling of Pyridinioalkanoyl thioesters and Benzamide-based thiolcarbamates derivatives was performed. Results: A four-point hypothesis of HHRR pharmacophoric feature was determined. A 3D-QSAR model was built which was validated through regression analysis. Molecular docking often lead compounds showed that the compound ZINC65398698 possesses a higher affinity towards NCp7 protein and binds well whereas other leads possessed only moderate binding affinity. The ADME/T prediction of all the ten lead compounds showed accepted values of biophysical properties. As ZINC65398698 showed higher binding affinity, a molecular dynamics simulation was performed to determine the stability of the protein-ligand system and to study the atomistic detail of protein residue behavior after forming a complex with the ligand. The RMSD and RMSF analysis showed that the complex is highly stable throughout the production run. So the complex can be more stable within the same environment and act as potential inhibitors was determined in this procedure. Conclusions: The suggested Ligand can be then subjected to a model study after the synthesizing procedure.