In silico molecular docking and dynamic simulation of anti-cholinesterase compounds from the extract of Catunaregam spinosa for possible treatment of Alzheimer's disease

Abstract

Alzheimer's disease (AD), is characterized by a progressive loss of cognitive abilities as well as behavioral symptoms including disorientation, trouble solving problems, personality and mood changes. Acetylcholinesterase (AChE) is a promising target for symptomatic improvement in AD due to its consistent and early cholinergic deficit. This research has investigated the potential compounds from Catunaregam spinosa as AChE inhibitors as a treatment option for AD, aiming to enhance cholinergic neurotransmission and alleviate cognitive decline. Tacrine, the FDA's first approved treatment for AD, is no longer in use due to its hepatotoxicity. Box-Behnken design (BBD) modelling was used to optimise the ultrasonic extraction of alkaloids from the dried fruits of C. spinosa. GC-MS analysis revealed the presence of ninety phytoconstituents in the extract. Among them, eighty-nine new phytoconstituents are reported in this plant fruit for the first time. Out of ninety phytoconstituents, eight phytoconstituents showed the best binding affinity against the AChE enzyme, i.e., PDB IDs 1GQR, 1QTI and 4PQE of AD targets using iGEMDOCK. The lead hits were tested for their drug-like properties and atomistic binding mechanisms using in silico ADMET prediction, LigPlot analysis, and molecular dynamics simulation. The results suggest four compounds such as 1,4,7,10,13,16-hexaoxacyclooctadecane; butanoic acid, 3-methyl-2-[(phenylmethoxy)imino]-, trime; butane-1,2,3,4-tetraol; and D-(+)-ribonic acid.gamma-lactone as potent inhibitors of AChE for the possible treatment of AD.

Keywords

• Alzheimer's disease
• In silico
• Catunaregam spinosa
• ADMET
• Acetylcholinesterase