Northwest A&F University, Center of Bioinformatics, Yangling, Shaanxi, 712100, China.
Expert Opin Drug Discov. 2010 Jan;5(1):21-31. doi: 10.1517/17460440903490395.
Virtual screening (VS) coupled with structural biology is a significantly important approach to increase the number and enhance the success of projects in lead identification stage of drug discovery process. Recent advances and future directions in estrogen therapy have resulted in great demand for identifying the potential estrogen receptor (ER) modulators with more activity and selectivity.
This review presents the current state of the art in VS and structure-activity relationship of ER modulators in recent discovery, and discusses the strengths and weaknesses of the technology.
Readers will gain an overview of the current platforms of in silico screening for discovery of ER modulators; they will learn which structural information is significantly correlated with the bioactivity of ER modulators and what novel strategies should be considered for the creation of more effective chemical structures.
With the goal of reducing toxicity and/or improving efficacy, challenges to the successful modeling of endocrine agents are proposed, providing new paradigms for the design of ER inhibitors.
虚拟筛选 (VS) 与结构生物学相结合，是一种非常重要的方法，可以增加药物发现过程中先导识别阶段的项目数量并提高其成功率。最近在雌激素治疗方面的进展和未来方向，导致人们对识别具有更高活性和选择性的潜在雌激素受体 (ER) 调节剂的需求大增。
本篇综述介绍了当前虚拟筛选技术的最新进展以及 ER 调节剂在最近的发现中的构效关系，并讨论了该技术的优缺点。
读者将全面了解当前用于发现 ER 调节剂的计算机筛选平台；他们将了解哪些结构信息与 ER 调节剂的生物活性密切相关，以及应该考虑哪些新策略来创造更有效的化学结构。
为了降低毒性和/或提高疗效，提出了成功模拟内分泌剂的挑战，为 ER 抑制剂的设计提供了新的范例。
