评估用于评估抗体结合 afinities 的计算策略
Ida Autiero1, Damiano Buratto2, Fengyi Guo3
1Department of Biomedical Sciences, Institute of Biostructures and Bioimaging, National Research Council (CNR), Napoli 80145, Italy.
Journal of chemical theory and computation
|October 23, 2025
概括
均衡分子力学Poisson-Boltzmann表面积 (MMPBSA) 计算比不均衡方法更好地预测抗体结合亲和力. 结果突出了计算机药物发现和抗体查的系统特定性能.
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:
- 准确的结合亲和度评估对于识别有效的候选药物至关重要.
- 计算方法对于预测绑定亲和关系至关重要,但需要大量资源.
- 抗体-标相互作用是治疗开发的关键.
研究的目的:
- 为了比较不同的计算方法来计算抗体-结合能.
- 评估分子力学Poisson-Boltzmann表面积 (MMPBSA) 和Rosetta力场计算与实验数据的准确性.
- 确定影响具有约束力的能源计算方法性能的因素.
主要方法:
- 使用平衡分子力学Poisson-Boltzmann表面积 (MMPBSA) 和平均力不平衡潜力的结合能计算的比较分析.
- 研究增强的采样技术,特别是与MMPBSA结合的复制交换分子动力学.
- 对针对CXCR2的酸的抗体的实验性结合亲和力数据的验证.
- 罗塞塔探测器对抗体-结合能量的预测力场性能的评估.
主要成果:
- 平衡MMPBSA计算显示,与非平衡方法相比,与实验结合亲和关系的一致性更好.
- 与MMPBSA进行复制交换分子动力学,以更高的计算成本提供了适度的准确性改进.
- 罗塞塔的力场计算与实验结合数据没有相关性.
- 鉴定出高抗体强度和主导的疏水性相互作用是某些方法的潜在限制因素.
结论:
- 均衡MMPBSA对于这种特定的抗体标系统来说,是一种比不均衡方法更可靠的方法.
- 方法性能是系统依赖的,强调需要在药物发现中仔细选择.
- 结果为优化体抗体查策略和计算结合能量的计算提供了见解.
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