Insilico evaluation on potential Mt-Sp1/matriptase inhibitors data: DFT and molecular modelling approaches

Abstract

Nine heterocyclic compounds were investigated using density functional theory, molecular operating environment software, material studio, swissparam (Swiss drug design) software. In this work, the descriptors generated from the optimized compounds proved to be efficient and explain the level of reactivity of the investigated compound. The developed quantitative structure activity relationship (QSAR) model was predictive and reliable. Also, compound 9 proved to be capable of inhibiting Mt-Sp1/Matriptase (pdb id: 1eax) than other examined heterocyclic compounds. Target prediction analysis was carried out on the compound with highest binding affinity (Compound 9) and the results were reported.

Keywords

• Mt-Sp1/Matriptase
• Inhibitors
• GFA
• DFT
• Docking
• Target prediction