密度功能理论计算和机器学习研究Au3集群和20个天然氨基酸分子之间的相互作用
Jiao Peng1, Li Wang1, Pu Wang1
1Department of Chemistry, Key Laboratory for Green Organic Synthesis and Application of Hunan Province, Key Laboratory of Environmentally Friendly Chemistry and Applications of Ministry of Education, Xiangtan University, Xiangtan, Hunan 411105, China.
ACS omega
|July 3, 2023
概括
黄金集群 (Au3) 与氨基酸在气体和水中的相互作用不同. 一个机器学习模型预测了结合能,揭示了黄金-氨基酸相互作用的关键相互作用因子.
科学领域:
- 计算化学的计算化学
- 材料科学 材料科学 材料科学
- 生物化学 生物化学
背景情况:
- 黄金集群对催化和生物医学应用有兴趣.
- 了解黄金集群与氨基酸等生物分子之间的相互作用至关重要.
研究的目的:
- 研究20种天然氨基酸的中性Au3集群的最佳吸附点和结合能.
- 开发一个机器学习模型来预测约束能量.
- 确定影响Au3-氨基酸相互作用的因素.
主要方法:
- 密度函数理论 (DFT) 对气相和水相的计算.
- 对结合能量的系统研究.
- 渐变增强决策树用于机器学习模型开发.
主要成果:
- 在气相中,Au3与N原子结合;在水中,它与N原子和侧链结合.
- metionin 和cysteine 通过水中的 S 原子表现出更强的结合.
- 机器学习模型准确地预测了结合的吉布斯自由能量 (ΔG).
结论:
- 溶解显著改变了与氨基酸的Au3结合点和强度.
- 含硫的氨基酸 (甲氨酸,氨酸) 具有独特的结合行为.
- 机器学习有效地模拟和解释复杂的Au3-氨基酸相互作用.
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