通过模板引导的组合对接策略来预测蛋白质 - 连接体结构
Keqiong Zhang1, Qilong Wu1, Sheng-You Huang1
1School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Proteins
|October 6, 2025
概括
本研究介绍了一个模板引导的集体对接策略,用于CASP16.16中的蛋白质-连接体结构预测. 这种新的方法在38个团队中获得了第4名的排名,证明了它在预测带结合姿势方面的有效性.
科学领域:
- 计算生物学是一种计算生物学.
- 结构生物学是结构生物学.
- 药物发现 药物发现
背景情况:
- 结构预测技术的批判性评估 (CASP) 在CASP15.5中引入了蛋白质连接体复合体结构预测.
- CASP16将这一类别扩展到制药超级目标,每个超级目标都包含一个具有多个连接体的蛋白质.
研究的目的:
- 在CASP16.16中开发和评估用于连接体 (LG) 任务的模板导向组合对接策略.
- 为了利用最近在蛋白质结构预测方面的进展,改进蛋白质 - 连接体复合体建模.
主要方法:
- 使用MODELER,AlphaFold3和AlphaFold-Multimer生成的结构组合.
- 在蛋白质数据库 (PDB) 中搜索了使用序列身份,配体相似性和最大共同子结构 (MCS) 的模板.
- 采用LSalign用于3D连接体对齐,XDock和MDock用于没有模板的预测,以及ITScore用于能源评估.
主要成果:
- 开发的方法在38个参与CASP16 LG任务的团队中排名第四.
- 模板引导组合对接策略在蛋白质-连接体结构预测方面被证明是有效的.
- 成功整合多个结构预测工具和基于模板的方法.
结论:
- 模板导向组合对接策略是用于蛋白质-连接体复杂结构预测的强有力的方法.
- 这种方法对药物发现和开发管道有很大的前景.
- 在CASP16中的表现验证了该战略在推进结构生物学技术方面的潜力.
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