Utilization of AlphaFold2 to Predict MFS Protein Conformations after Selective Mutation

The major facilitator superfamily (MFS) is the largest secondary transporter family and is responsible for transporting a broad range of substrates across the biomembrane. These proteins are involved in a series of conformational changes during substrate transport. To decipher the transport mechanism, it is necessary to obtain structures of these different conformations. At present, great progress has been made in predicting protein structure based on coevolutionary information. In this study, AlphaFold2 was used to predict different conformational structures for 69 MFS transporters of E. coli after the selective mutation of residues at the interface between the N- and C-terminal domains. The predicted structures for these mutants had small RMSD values when compared to structures obtained using X-ray crystallography, which indicates that AlphaFold2 predicts the structure of MSF transporters with high accuracy. In addition, different conformations of other transporter family proteins have been successfully predicted based on mutation methods. This study provides a structural basis to study the transporting mechanism of the MFS transporters and a method to probe dynamic conformation changes of transporter family proteins when performing their function.     

一种基于后缀树的Web访问模式挖掘算法

在Web使用挖掘中，分析用户的行为模式是一个关键的问题。文中提出了一种基于后缀树的最大频繁序列MFS(Maximal Frequent Sequences)的有效挖掘算法，该算法能够从增量数据中动态发现和输出MFS。