A new insight into computational molecular design: A case study on BACE-1 inhibitors

Abstract

Virtual bioactive molecular design is an important part of modern drug discovery projects. In this regard, molecular docking may be looked upon as a well established in silico approach in structure-based hit/lead development. Stereoelectronic complementary fit of a bioactive ligand with its receptor may be predicted by molecular docking. Generally docking simulations are compromised of two principal steps; search algorithm and a scoring function. Search algorithms explore the ligand-receptor configurational space while scoring functions apply molecular mechanic force fields to estimate the free binding energies of various ligand-enzyme poses. In the present contribution, a new probability factor (PF) was proposed that could successfully enhance the predictability of AutoDock4.2 scoring function with regard to FRET-based BACE-1 inhibitory activities of some organic small molecules. BACE-1 or beta site amyloid precursor protein cleaving enzyme is a major therapeutic target for Alzheimer disease due to its determinant role in pathogenesis of the disease.