化学特征和机器学习辅助预测蛋白质-连接物短键的化学特征和机器学习辅助预测蛋白质-连接物短键的化学特征和机器学习辅助预测蛋白质-连接物短键的化学特征和机器学习辅助预测蛋白质-连接物短键的化学特征
Shengmin Zhou1, Yuanhao Liu2, Sijian Wang2
1YDS Pharmatech, Inc., Albany, NY 12226, USA.
Research square
|June 9, 2023
概括
研究人员使用机器学习模型在蛋白质-配体相互作用中确定了短键 (SHB). 该模型通过预测这些密切接触,有助于设计具有增强功能的生物分子和配体.
科学领域:
- 结构生物学 结构生物学
- 生物化学 生化学
- 计算生物学 计算生物学
背景情况:
- 短键 (SHBs) 是通过比它们的范德瓦尔斯半径的总和更接近的供体和受体异质原子来定义的.
- 了解SHB对于阐明蛋白质结构和生物功能至关重要.
- 在蛋白质连接体复合体中描述SHB可以为药物设计和生物分子工程提供信息.
结论:
- MAPSHB-Ligand模型有效地预测了蛋白质 - 配体SHBs.
- 这种预测能力有助于设计新的生物分子和连接体.
- 利用SHB可以导致增强的蛋白质和连接体功能.
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