CACHE挑战#1:针对LRRK2的WDR域,这是与帕金森病相关的蛋白质
Fengling Li1, Suzanne Ackloo1, Cheryl H Arrowsmith1,2,3
1Structural Genomics Consortium, University of Toronto, Toronto, Ontario M5G 1L7, Canada.
Journal of chemical information and modeling
|November 5, 2024
概括
第一个化学命中探测实验的计算评估 (CACHE) 挑战评估了帕金森病目标LRRK2.2的计算命中探测方法. 机器学习和传统对接显示了类似的结果,突出了难以达到目标的药物发现挑战.
科学领域:
- 药物发现 药物发现 药物发现
- 计算化学计算化学
- 生物化学 生物化学
背景情况:
- 在CACHE挑战基准计算命中发现的进步.
- 首次挑战的重点是LRRK2 WDR域,这是一个没有已知的连接体的困难目标.
研究的目的:
- 评估各种计算方法在识别LRRK2目标潜在药物候选者的有效性.
- 评估当前对具有挑战性的蛋白质标进行计算命中探测的现状.
主要方法:
- 23个计算团队对LRRK2 WDR域进行了虚拟选.
- 选择的化合物在SPR和正交测试中进行了结合亲和力测试.
- 成功的工作流包括分子动力学,碎片对接,生成设计和深度学习.
主要成果:
- 在第1轮中,1955种化合物中有73种与LRRK2结合.
- 在第2轮中,确定了7个具有18-140μM之间的亲和度的化学多样性系列.
- 机器学习方法的性能与传统的对接方法相提并论.
结论:
- 计算式命中探测方法看起来有前途,但在挑战性目标 (如LRRK2.2) 上却很困难.
- 不同的策略,包括ML加速方法,取得了有限的成功.
- 为了有效地发现针对困难目标的药物,还需要进一步的进展.
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