化学空间
化学
药物发现
透视图(图形)
预处理器
计算生物学
虚拟筛选
纳米技术
生化工程
数据科学
组合化学
计算机科学
人工智能
生物化学
工程类
生物
材料科学
作者
Bernd Kuhn,Wolfgang Guba,Jérôme Hert,David W. Banner,Caterina Bissantz,Simona Ceccarelli,Wolfgang Haap,Matthias Körner,A. Kuglstatter,C. Lerner,Patrizio Mattei,Werner Neidhart,Emmanuel Pinard,M.G. Rudolph,Tanja Schulz‐Gasch,Thomas J. Woltering,Martin Ståhl
标识
DOI:10.1021/acs.jmedchem.5b01875
摘要
We present a series of small molecule drug discovery case studies where computational methods were prospectively employed to impact Roche research projects, with the aim of highlighting those methods that provide real added value. Our brief accounts encompass a broad range of methods and techniques applied to a variety of enzymes and receptors. Most of these are based on judicious application of knowledge about molecular conformations and interactions: filling of lipophilic pockets to gain affinity or selectivity, addition of polar substituents, scaffold hopping, transfer of SAR, conformation analysis, and molecular overlays. A case study of sequence-driven focused screening is presented to illustrate how appropriate preprocessing of information enables effective exploitation of prior knowledge. We conclude that qualitative statements enabling chemists to focus on promising regions of chemical space are often more impactful than quantitative prediction.
科研通智能强力驱动
Strongly Powered by AbleSci AI