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探索SiteMap和SiteFinder的应用程序,以集中加密口袋识别

Yunhui Ge¹, Vineet Pande², Mark J Seierstad¹

¹Computer-Aided Drug Design, Therapeutics Discovery, Janssen Research & Development, 3210 Merryfield Row, San Diego, California 92121, United States.

The journal of physical chemistry. B

|June 21, 2024

概括

识别加密口袋是一个挑战. 这项研究表明,SiteMap和Site Finder工具可以帮助确定潜在的加密口袋,用于进一步的计算分析,从而改善药物发现工作.

科学领域:

计算化学是一种计算化学.
结构生物学是结构生物学.
药物发现药物发现

背景情况:

描述密码口袋,这是蛋白质上的短暂结合点,是困难的.
分子动力学 (MD) 模拟提供了原子细节,但在识别这些难以捉摸的口袋的时间范围内受到限制.
改进的采样方法提高了MD的效率,但需要事先的知识,这对于新的加密口袋来说是不可用的.

研究的目的:

评估SiteMap和SiteFinder的实用性,以确定潜在的加密口袋区域.
将这些工具与用于加密口袋探索的先进计算方法集成.
展示克服加密口袋识别局限性的战略.

主要方法:

应用网站地图和网站搜索器来识别蛋白质的焦点.
利用计算建模和增强的MD采样技术.
从精心策划的数据集 (PocketMiner,Cryptosite Set) 和NKG2D蛋白中对136个已知的加密口袋进行了验证.

主要成果:

网站地图和网站搜索器成功识别了藏有已知的加密口袋的区域.
这些工具为高级计算分析提供了有价值的起点.
综合方法有助于探索潜在的加密结合站点.

结论:

现有的商业工具,如SiteMap和SiteFinder,可以有效地绘制具有加密口袋的区域.
这种方法使得先进的计算建模可以用于加密口袋的表征.
这些发现有助于发现用于药物开发的新型结合部位.

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