ReaLigands:一个从实验中培养的配体库,旨在用于分子计算催化剂设计
Shu-Sen Chen1, Zack Meyer1, Brendan Jensen1
1Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84604 United States.
Journal of chemical information and modeling
|November 21, 2023
概括
本研究介绍了ReaLigands库,这是一个来自晶体结构的3万多个连接体的集合. 这个资源通过提供易于获得的,可合成的配体选项来加速计算催化剂设计.
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
- 催化剂是一种催化剂.
背景情况:
- 计算催化剂设计需要确定最佳的金属-连接体组合,以达到所需的反应性和选择性.
- 在评估用于实验验证的计算提出的配体的合成性方面存在重大障碍.
研究的目的:
- 在计算催化剂设计中解决连接物合成能力的挑战.
- 介绍ReaLigands库,一个实验验证的连接体的全面数据库.
主要方法:
- 开发了RealLigands库,通过使用修改的深度首先搜索算法从晶体结构中提取>30,000个连接物.
- 使用在量子化学特征上训练的机器学习模型将电荷分配给连接体.
- 采用主要成分分析 (PCA) 和统一的多重近似和投影 (UMAP) 来进行连接体分析和分类.
主要成果:
- 该RealLigands库包含多样化的单,双,三和较大的连接体,按连接性和性排序.
- PCA和UMAP分析揭示了三联体类别内的结构多样性和相互连接.
- 通过快速生成Rh-化乙烯迁移插入反应中的750个双联体的反应障碍物来证明图书馆的实用性.
结论:
- 在ReaLigands图书馆显著促进了计算催化剂设计的翻译到实验实践.
- 该资源通过提供精心策划的一组可合成的连接体来加速新型催化剂的发现和优化.
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