Efficient modelling and validation of cryptic protein binding sites for drug discovery

用于药物发现的神秘蛋白质结合位点的有效建模和验证

• 批准号: EP/P011306/1
• 负责人: Francesco Luigi Gervasio
• 金额: $ 34.7万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FP011306%2F1
• 关键词: Efficient; modelling; validation; cryptic; protein

Over 75% of disease-involved proteins cannot be readily targeted by conventional chemical biology approaches. New approaches are needed to increase the scope of molecular medicine. Cryptic binding pockets, i.e. pockets that transiently form in a folded protein, but are not apparent in the crystal structure of the unliganded apo-form, offer outstanding opportunities to target proteins otherwise deemed 'undruggable' and are thus of considerable interest in academia and the pharmaceutical industry. Unfortunately, not only they are notoriously difficult to identify, but also the molecular mechanism by which they form is still debated. The aim of this collaborative project is to address the knowledge gaps and develop an efficient computational platform based on atomistic molecular simulations to systematically detect druggable cryptic pockets in targets of biopharmaceutical interest. The platform will build on our successful experience in developing and applying enhanced-sampling simulation algorithms to molecular recognition, and will be extensively tested on validated drug targets harbouring cryptic sites. The computational results will be further validated on novel targets by a combination of experiments in collaboration with an industrial partner (UCB).

超过75%的疾病相关蛋白质不能通过常规化学生物学方法容易地靶向。需要新的方法来扩大分子医学的范围。隐蔽结合口袋，即在折叠蛋白质中瞬时形成但在未配体的脱辅基形式的晶体结构中不明显的口袋，为靶向蛋白质提供了极好的机会，否则被认为是“不可药用的”，因此在学术界和制药工业中引起了相当大的兴趣。不幸的是，它们不仅难以识别，而且它们形成的分子机制仍然存在争议。这个合作项目的目的是解决知识差距，并开发一个基于原子分子模拟的高效计算平台，以系统地检测生物制药目标中的可药用隐藏口袋。该平台将建立在我们在开发和应用增强采样模拟算法进行分子识别方面的成功经验基础上，并将在经过验证的含有隐蔽位点的药物靶标上进行广泛测试。计算结果将通过与工业合作伙伴（UCB）合作的实验组合在新目标上进一步验证。

项目成果

SWISH-X, an expanded approach to detect cryptic pockets in proteins and at protein-protein interfaces

SWISH-X，一种检测蛋白质中和蛋白质-蛋白质界面上的隐秘口袋的扩展方法

• DOI: 10.1101/2023.11.03.565527
• 发表时间: 2023
• 作者: Borsatto A