Discovery Of Selective ERβ Ligands Via Combinational Virtual Screening And Molecular Modeling Study Of Para-nitrobenzyl Esterase And Its Mutants

In the1980s, a new tool for drug discovery had appeared in the field of drug research and development which is termed computer aided drug design. It plays an important role in the drug research and development process as well as functional study of biomacromolecules. In this thesis, CADD methods were taken to discover the ligands targeting estrogen receptor β (ERp) and study engineering para-nitrobenzyl esterase from Bacillus amyloliquefaciens (BAE).In Chapter1, a simple introduction about CADD subject was given and some methods associated with the work from the next two chapters were described in detail.In Chapter2, a virtual screening strategy combining similarity search based on2D fingerprint and docking based on molecular dynamics optimized ERβ LBD to discover selective ERp ligands in Enamine database.61compounds we chosen showed ER activities in the bioassay which included14agonists,13antagonists,3partial agonists and1dual-profile compound. Among them,12exhibited agonistic activities to ERβ and5of them showed high selectivity for ERp.In Chapter3, homology modeling and molecular docking were conducted to study engineering the para-nitrobenzyl esterase from Bacillus amyloliquefaciens. After the modeled structure was optimized, it was proved to be reliable by evaluation using Ramachandran plot and Profile-3D. Next, we performed molecular docking with modifying the structures and, based on which, we provided guides for the follow-up protein engineering. Finally,3variants were discovered to be improved which could be clarified by their binding modes and binding free energy calculations.Chapter4is the summary of the work in this thesis.