加速和自动化自由能量扰动 绝对约束自由能量计算与RED-E函数
Runduo Liu1, Wenchao Li1, Yufen Yao1
1School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou 510006, China.
Journal of chemical information and modeling
|December 4, 2023
概括
这项研究介绍了在平衡位置 (RED-E) 的控制能量分布函数,以准确预测结合亲和力. 这种方法自动化了控制选择,加速了药物设计的自由能量计算.
科学领域:
- 计算化学是一种计算化学.
- 分子建模分子建模
- 药物发现 药物发现
背景情况:
- 准确预测结合亲缘关系对于基于结构的药物设计至关重要,但仍然具有挑战性.
- 基于自由能量扰动的绝对结合自由能量 (FEP-ABFE) 是有前途的,但在自动控制参数化方面面临障碍.
- 经验限制的确定是非自动化的,导致数值不稳定性和阻碍FEP-ABFE应用程序.
研究的目的:
- 开发一种自动化和可靠的方法,用于在FEP-ABFE计算中选择安全装置参数.
- 为了应对经验约束的决定的挑战,并提高约束亲和力预测的效率.
- 为了使FEP-ABFE在药物发现中大规模应用.
主要方法:
- 导出了控制器添加过程中能量差异的概率分布的分析表达式,称为RED-E函数.
- 开发了一种基于RED-E功能的自动限制选择方法.
- 使用模拟来验证RED-E功能和自动选择方法.
主要成果:
- RED-E函数准确地描述了能量差异的概率分布,当在平衡时添加限制时.
- 拟议的自动限制选择方法确保自由状态和受限制状态之间的高相间重叠.
- 通过新方法实现的2λ扰动方法,与标准的12-λ方法相比,实现了近6倍的加速.
- RED-E函数提供了对FEP过程中非高斯行为的分析洞察.
结论:
- RED-E功能和自动控制选择显著提高了FEP-ABFE的可靠性和效率.
- 这种方法促进了FEP-ABFE在实践药物发现中的大规模应用.
- 这项研究为克服计算药物设计的先前局限性提供了一条途径.
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