Computational screening of promising beta-secretase 1 inhibitors through multi-step molecular docking and molecular dynamics simulations - pharmacoinformatics approach

Abstract

Alzheimer’s disease (AD) is a neurodegenerative disorder generally developed with aging. AD slowly hammers the memory and cognitive abilities which eventually leads to abnormal behaviour, and ultimately left with disability and dependency. It is anticipated that by the year 2050, world population will experience the incidence of 100 million AD cases. It has been more than hundred years passed since AD recognized as a dreadfull disease, but there is no effective curative agent discovered against AD to date. One of the major hallmarks of the AD development is the accumulation of extracellular amyloid-beta (Aβ) plaques in the brain. In the amyloidogenic process, an extensively studied beta-secretase enzyme, known as BACE1, plays a key role in the accumulation and production of Aβ fragments. Therefore, successful inhibition of BACE1 by small molecular chemical entities can be an effective approach for anti-AD drug development. Hence, the current study has been perceived to find out potential BACE1 inhibitiors by virtual screening of entire Asinex chemical library database through multi-step molecular docking methodologies. Further, sequential screening of in-silico pharmacokinetics, molecular dynamic (MD) simulations analyses along with binding free energy estimation were performed. Comparative analyses and characteristics of molecular binding interactions assessment finally suggests that five molecules (B1–B5) to be the most promising BACE1 inhibitors. Molecular interactions analyses revealed that either one or both the catalytic dyad residues (Asp32 and Asp228) of BACE1 has formed strong molecular interactions with all the proposed molecules. Not only the catalytic dyad residues are involved in the formation of molecular binding interactions but also other important non-Asp binders residues such as Gly34, Tyr71, Trp115, Arg128, Lys224, Gly230, Thr231, Thr232, Arg235, Thr329, and Val332 found to interact with the selected compounds. Moreover, the dynamic behaviour of proposed molecules and BACE1 was explored through all-atoms MD simulation study for 100 ns time span. Analysis of MD simulation trajectories explained that all identified molecules are efficient enough to retain the structural and molecular interactions integrity inside the receptor cavity of BACE1 in dynamic environment. Finally, the binding free energy of each molecule has calculated from MD simulation trajectories through MM-PBSA method and found that all molecules possess a strong binding affinity towards the BACE1. The high negative binding free energies are found to be within the range of −994.978 to −561.562 kJ/mol for the identified compounds. Henceforth, analyses of extensively studied multi-cheminformatics approaches explained that proposed molecules might be promising BACE1 inhibitors for therapeutic application in AD, subjected to experimental validation.