CHARMM-GUI混合ML/MM构建器用于混合机器学习和分子机械建模和模拟
Florence Szczepaniak1, Donghyuk Suh1, Wonpil Im1
1Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania 18015, United States.
Journal of chemical information and modeling
|March 9, 2026
概括
新的CHARMM-GUI软件可以实现蛋白质 - 连接体复合体的混合机器学习/分子力学 (ML/MM) 模拟. 这种方法使用神经网络潜力 (NNP) 以降低计算成本进行准确的配体建模.
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:
- 机器学习 (ML) 的进步正在彻底改变分子动力学 (MD) 模拟.
- 在量子力学 (QM) 数据上训练的神经网络潜力 (NNP) 为分子描述提供了高精度.
- 混合ML/MM方法将局部区域 (例如联体) 的NNP与系统其余部分的经典分子力学 (MM) 结合起来.
研究的目的:
- 介绍CHARMM-GUI混合ML/MM Builder,这是一个用于自动化混合ML/MM模拟的工具.
- 以降低计算成本,为蛋白质 - 配体复合体实现接近QM的准确性.
- 用应用系统来证明新建厂商的实用性和能力.
主要方法:
- 开发了CHARMM-GUI混合ML/MM构建器.
- 与TorchANI-AMBER和OpenMM-ML集成,用于基于NNP的模拟.
- 支持MACE和ANI神经网络潜力.
- 用于混合ML/MM建模的系统和输入文件的自动生成.
主要成果:
- 成功自动化混合ML/MM模拟设置用于蛋白质 - 连接体复合体.
- 在复合体内对连接体相互作用的近QM精度的证明.
- 与完整的QM方法相比,计算成本显著降低.
- 在溶液或膜环境中进行模拟所需文件的生成.
结论:
- CHARMM-GUI混合ML / MM构建器可方便高效准确地模拟蛋白质 - 连接体复合体.
- 混合方法为药物发现和分子建模提供了一个强大的策略.
- 该工具提高了先进的ML/MM技术在计算化学中的可访问性和应用性.
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