能否预测可逆共价抑制剂的选择性?
Payal Chatterjee1, Wesley M Botello-Smith1, Han Zhang1
1College of Pharmacy, Western University of Health Sciences , Pomona, California 91766, United States.
Journal of the American Chemical Society
|November 11, 2017
概括
可逆共价抑制剂提供临床益处,但预测它们的结合亲和力是复杂的. 这项研究表明,单独分析共价结合状态往往预测了选择性,尽管非共价相互作用也可能至关重要.
科学领域:
- 计算化学
- 药物发现
- 生物化学
背景情况:
- 可逆共价抑制剂比其他类型的药物具有优势.
- 优化目标选择性需要理解共价和非共价相互作用.
- 由于多步骤的结合过程,预测这些抑制剂的结合亲和力是具有挑战性的.
研究的目的:
- 确定相对结合自由能量和总体可逆共价结合亲和力之间的关系.
- 调查共价结合状态对抑制剂选择性的预测能力.
- 确定非对应相互作用显著影响结合亲和力和动力学的条件.
主要方法:
- 使用双态结合模型分析可逆共价结合.
- 使用 λ 交换分子动态的自由能量扰动 (FEP).
- 对calpain-1和calpain-2的α-ketoamide类型的结合自由能量计算
主要成果:
- 共价结合状态通常预测可逆共价抑制剂的选择性.
- 在某些条件下,非共价结合步骤可能是显著的.
- 共价结合状态和非共价结合状态可能不具有相同的选择性.
结论:
- 分析共价结合状态通常足以预测选择性,但也应考虑非共价贡献.
- 将FEP与QM/MM计算相结合可以改善结合亲和力和动力学的预测.
- 研究结合状态和动力学对于优化可逆共价抑制剂至关重要.
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