CADD Acetylcholinesterase Inhibitors

The recent advances in technologies, namely automated platform, computational chemistry and computer aided drug design (CADD), are now offering a fast track to some limiting factors of therapeutic discovery as well. Computer-aided drug design (CADD), that offers an in silico alternative to medicinal chemistry techniques for studying the structure and predicting the biological activity of drug candidates, has the advantages of both speed and low cost and is becoming an indispensable program of major pharmaceutical companies.Alzheimer’s disease (AD) is a progressive neurodegenerative brain disorder that is characterized by dementia, cognitive impairment, and memory loss. Current treatment of AD focuses on increasing cholinergic neurotransmission in the brain through inhibiting Acetylcholinesterase (AChE) activity. Tacrine, the first AChE inhibitor approved by the FDA for the treatment of AD, suffers from therapy-limiting liver toxicity. Despite this limitation, tacrine has been widely used as scaffold for the development of new multifunctional agents with additional biological properties other than AChE inhibition. Due to the multi-pathogenesis of AD, one of the current strategies is to develop novel anti-AD agents with multiple potencies. In recent years, many studies have focused on the combined effects of AChEIs inhibition and scavenging oxygen radicals as well as reduction of the Aβ fibril self-aggregation by conjugating tacrine with other active groups.In the first chapter of the thesis, a review of CADD research, progress, and applications was presented. Enzymes and their inhibitors of Acetylcholinesterase were introduced.In the second chapter of the thesis, three-dimensional quantitative structure-activity relationship models were developed on a series of inhibitors of Acetylcholinesterase by using traditional comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods, respectively. Bioactive conformations were generated by docking a series of Tacrine Dimers Analogs with AChE crystal structure.3D quantitative structure activity relationship (3D-QSAR) models were developed for AChE inhibitors using modeling analysis. Cross-validation q2value of0.510and0.702, non-cross-validation r2value of0.998and0.988, r2pred value of0.750and0.742were obtained. The statistical results suggested that the models have good stability and predictive ability. In the third chapter of the thesis, three quantitative structure-activity relationship models were developed on a series of inhibitors of Acetylcholinesterase by Topomer CoMFA method. CoMFA has made significant contribution to ligand-based drug design. However, there are some restrictions for input ligands, the ligands should have typical3D-structures, and they have to align with molecules in database. The whole procedure is time-consuming, highly subjective and has low repeatability. The second generation of CoMFA method-Topomer CoMFA which belongs to one of fragment-based3D-QSAR methods can overcome the shortcomings. The cross-validated coefficient q2value of Topomer CoMFA was0.571, the non-cross-validated r2value was0.794, r2pred was0.766, and this model has good predictability. Compared with traditional comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods, the statistical results of those three models suggested that the models have good stability and predictive ability, and provide theoretical basis for designing new high activity molecules.In the fourth chapter of the thesis, Topomer Search method combined with molecular docking method were used for virtual screening for ZINC databases, in order to get highly active and selective inhibitors. In this chapter,125,909molecules obtained from ZINC database were virtual screened by using Topomer search,891molecules with potential AChE inhibitory activity were obtained. Then, the combination of891molecules and AChE crystal structure were confirmed by using molecular docking,66molecules endowed with dual binding were obtained, which have high selectivity of AChE inhibitory activity.This research was summed up as follows:(1) three-dimensional quantitative structure-activity relationship models were developed on a series of inhibitors of Acetylcholinesterase by using traditional comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods, respectively. The models can provide theoretical basis for designing new high activity molecules.(2) Three-dimensional quantitative structure-activity relationship models were developed on a series of inhibitors of Acetylcholinesterase by Topomer CoMFA method. It provided theoretical basis for designing new high activity and high selectivity molecules.(3) Topomer Search combined with molecular docking method were used for virtual screening, and a series of potential inhibitors with high selectivity and high selectivity were obtained. Through the research, we hope that it can provide a guide for the design of the molecular and can screen out AChE inhibitor molecules with high activity and high selectivity, reduce the side effects in the treatment of AD disease.