结合蛋白质结构和连接体构成预测的自动基准测试
Michèle Leemann1,2, Ander Sagasta1,2, Jerome Eberhardt1,2
1Biozentrum, University of Basel, Basel, Switzerland.
Proteins
|October 27, 2023
概括
准确的蛋白质连接体复合体 (PLC) 预测至关重要. 本研究开发了自动基准测试,揭示了当前数据集和评估PLC预测准确性的方法的局限性.
科学领域:
- 计算生物学是一种计算生物学.
- 结构生物信息学 结构生物信息学
- 药物发现 药物发现
背景情况:
- 蛋白质连接体复合体 (PLC) 预测对于理解生物过程和药物开发至关重要.
- 蛋白质结构预测的批判性评估 (CASP15) 强调了PLC预测的重要性,包括受体结构和连接体姿势估计.
- 对PLC预测方法的自动基准测试对于进步至关重要.
研究的目的:
- 为了应对创建用于蛋白质 - 配体复合体 (PLC) 预测的自动基准测试技术的挑战.
- 评估实验确定PLC结构的可靠性作为基本真相.
- 评估PLC预测目标的多样性和难度.
主要方法:
- 使用验证标准评估实验解决的PLC的可靠性.
- 利用PLC与现有综合体的相似性进行多样性和难度评估.
- 开发了一个高质量的数据集用于基准测试,与PDBBind时间分割测试集形成鲜明对比.
- 创建了两个PLC预测特定的评分指标,以区分对接任务.
主要成果:
- 对于全面的PLC评估,PDBBind的时间分割测试集是不够的.
- 最先进的工具在更具代表性的数据集上产生相互矛盾的结果.
- 将连接物重新装入晶体结构要比预测的蛋白质模型要容易得多.
- 引入了用于PLC预测和准确性评估的全自动化管道.
结论:
- 目前用于PLC预测的基准测试实践需要显著改进.
- 对于可靠的PLC预测评估,需要一个强大的,高质量的数据集和适当的指标.
- 开发的自动化管道为预测和评估PLC准确性提供了一种标准化的方法.
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