Literature DB >> 25743214

LEADOPT: an automatic tool for structure-based lead optimization, and its application in structural optimizations of VEGFR2 and SYK inhibitors.

Guo-Bo Li1, Sen Ji1, Ling-Ling Yang2, Rong-Jie Zhang1, Kai Chen1, Lei Zhong1, Shuang Ma1, Sheng-Yong Yang3.   

Abstract

Lead optimization is one of the key steps in drug discovery, and currently it is carried out mostly based on experiences of medicinal chemists, which often suffers from low efficiency. In silico methods are thought to be useful in improving the efficiency of lead optimization. Here we describe a new in silico automatic tool for structure-based lead optimization, termed LEADOPT. The structural modifications in LEADOPT mainly include two operations: fragment growing and fragment replacing, which are restricted to carry out in the active pocket of target protein with the core scaffold structure of ligand kept unchanged. The bioactivity of the newly generated molecules is estimated by ligand efficiency rather than a commonly used scoring function. Twelve important pharmacokinetic and toxic properties are evaluated using SCADMET, a program for the prediction of pharmacokinetic and toxic properties. LEADOPT was first evaluated using two retrospective cases, in which it showed a very good performance. LEADOPT was then applied to the structural optimizations of the VEGFR2 inhibitor, sorafenib, and the SYK inhibitor, R406. Though just several compounds were synthesized, we have obtained some compounds that are more potent than sorafenib and R406 in enzymatic and functional assays. All of these have validated, at least to some extent, the effectiveness of LEADOPT.
Copyright © 2015. Published by Elsevier Masson SAS.

Entities:  

Keywords:  Fragment growing; Fragment replacing; Lead optimization; Ligand efficiency; Structure-based drug design (SBDD)

Mesh:

Substances:

Year:  2015        PMID: 25743214     DOI: 10.1016/j.ejmech.2015.02.019

Source DB:  PubMed          Journal:  Eur J Med Chem        ISSN: 0223-5234            Impact factor:   6.514


  1 in total

1.  NMR-filtered virtual screening leads to non-metal chelating metallo-β-lactamase inhibitors.

Authors:  Guo-Bo Li; Martine I Abboud; Jürgen Brem; Hidenori Someya; Christopher T Lohans; Sheng-Yong Yang; James Spencer; David W Wareham; Michael A McDonough; Christopher J Schofield
Journal:  Chem Sci       Date:  2016-12-14       Impact factor: 9.825

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.