标杆管理
对接(动物)
机器学习
人工智能
一般化
计算机科学
训练集
数据挖掘
数据科学
集合(抽象数据类型)
数据建模
计算模型
数据收集
实验数据
作者
Linlong Jiang,Ke Zhang,Kai Zhu,Ying Wang,Yu Kang,Tingjun Hou
标识
DOI:10.1021/acs.jcim.5c01399
摘要
structures. For antibody-antigen docking, AlphaFold3 remains the most accurate method (top-5 success rate: 31.78%) and substantially outperforms AlphaFold-Multimer in modeling the CDR-H3 loop. In OOD generalization tests, all DL-based models exhibit markedly reduced performance on the PPCBench data set. Overall, our work establishes a unified benchmarking framework that enables systematic evaluation of docking methods across diverse tasks and provides critical insights into the strengths and limitations of current docking strategies, thereby informing future developments in protein-protein docking research.
科研通智能强力驱动
Strongly Powered by AbleSci AI