Affiliations: [a] Department of Medicinal Chemistry, School of Pharmacy, Ardabil University of Medical Sciences, Ardabil, Iran | [b] Chemistry Department, Shiraz University, Shiraz, Iran | [c] Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz, Iran | [d] Department of Medicinal Chemistry, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran
Correspondence:
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Corresponding author: Nima Razzaghi-Asl, Department of Medicinal Chemistry, School of Pharmacy, Ardabil University of Medical Sciences, PO code 5618953134, Ardabil, Iran. Tel.: +98 451 5522438; Fax: +98 451 5523833; E-mail: [email protected], [email protected].
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.
Keywords: Alzheimer, BACE-1, docking, scoring function
