Science Letters

Chemical & Physical Sciences | Research article | https://doi.org/10.47262/SL/8.2.132020005

Molecular Docking and Quantitative Structure Activity Relationship for the Identification of Novel Phyto-inhibitors of Matrix Metalloproteinase-2

Damilohun Samuel Metibemu 1, 2, Oluwatoba Emmanuel Oyeneyin 3, 4*, Damilola Esther Omotoyinbo 2, Olawole Yakubu Adeniran 2, Ayorinde Omolara Metibemu 2, Mary Bose Oyewale 2, Omolara Faith Yakubu 5, Idowu Olaposi Omotuyi 1, 2

1 Centre for Biocomputing and Drug Development; 2 Department of Biochemistry; 3 Theoretical and Computational Chemistry Unit; 4 Department of Chemical Sciences; Adekunle Ajasin University, Akungba-Akoko, Ondo State, Nigeria

5 Department of Biochemistry, College of Science and Technology, Covenant University, Canaan land, Ota, Ogun State, Nigeria

Abstract

Cancer is a deadly disease that affects humans of all races, gender, and age. The matrix metalloproteinase-2 (MMP-2) protein is a good target when designing an anticancer drug. The expression of this protein influences cell growth and division. The activation of this protein opens the extracellular matrix and provides entry of the new cells into the body system. Phytochemicals are known to possess the ability to cure human diseases with little or no side effect. In this study, phytochemicals from yellow mombin, turmeric, green chiretta, African basil and ginger were evaluated against the MMP-2 orthosteric sites and three-dimensional quantitative structure activity relationship (3D-QSAR) was used to generate a model for MMP-2 inhibitors. The drug-like properties of the lead compounds and the standard drug were tested by employing the Lipinski rule of five. Azulene from ginger, Andrographidine A from green chiretta and Isovitexin from African basil with the docking scores of -7.3 kcal/mol, -9.3 kcal/mol, and -8.2 kcal/mol, respectively, were found to be the lead compounds as potential MMP-2 inhibitors. A robust regression model for the inhibition of MMP-2 was generated. Andrographidine A with the highest docking score stood out as a potential inhibitor of MMP-2 by sharing selective interactions with his-120 and his-130. The QSAR model proposed herein was thoroughly validated and hence offers a tool for the identification of potential MMP-2 inhibitors in the future.