Li Jing-Jing, Huang De-Shuang, Wang Bing, Chen Pen
Intelligent Computing Lab, Institute of Intelligent Machines, Chinese Academy of Sciences, He Fei An Hui, PR China.
Int J Biol Macromol. 2006 May 30;38(3-5):241-7. doi: 10.1016/j.ijbiomac.2006.02.024. Epub 2006 Apr 4.
Identifying protein-protein interfaces is crucial for structural biology. Because of the constraints in wet experiments, many computational methods have been proposed. Without knowing any information about the partner chains, a new method of predicting protein-protein interaction interface residues purely based on evolutionary information in heterocomplexes is proposed here. Unlike traditional approaches using multiple sequence alignment profiles to represent the conservation level for each residue, we make predictions based on the concept of residue conservation scores so that the dimension of the feature vector for each residue can be drastically reduced, at least 20 times less than conventional methods. Based on the representation approach, a simple linear discriminant function is used to make predictions, so the computational complexity of the whole prediction procedure can also be greatly decreased. By testing our approach on 69 heterocomplex chains, experimental results demonstrate the performance of our approach is indeed superior to current existing methods.
识别蛋白质-蛋白质相互作用界面对于结构生物学至关重要。由于湿实验中的限制，已经提出了许多计算方法。在不知道任何关于伙伴链信息的情况下，本文提出了一种仅基于异源复合物中的进化信息来预测蛋白质-蛋白质相互作用界面残基的新方法。与使用多序列比对谱来表示每个残基保守水平的传统方法不同，我们基于残基保守分数的概念进行预测，从而可以大幅降低每个残基特征向量的维度，至少比传统方法少20倍。基于这种表示方法，使用简单的线性判别函数进行预测，因此整个预测过程的计算复杂度也可以大大降低。通过在69条异源复合物链上测试我们的方法，实验结果表明我们方法的性能确实优于现有方法。
