研究团队构建序列到结构功能预测流程，并完成尿路致病性大肠杆菌 UTI89 全蛋白组预测
Whole-proteome structure/function prediction in uropathogenic <i>E. coli</i> reveals previously missed host-microbe and microbe-phage interaction pathways
研究团队整合蛋白质结构与功能预测方法，搭建了一条从一级序列出发预测结构与功能的完整流程，并对尿路致病性大肠杆菌模型菌株 E. coli UTI89 的全部蛋白做了预测。基于预测功能的全基因组富集分析，作者给出了该菌中注释不足蛋白可能参与的生物学机制，并通过 UTI89_C0931 和 ybtS 两个基因的个案分析验证了流程表现。团队还公开了 UTI89 结构与功能数据库，供研究者查询未注释蛋白的潜在角色。作者指出，多数计算方法依赖与已注释蛋白的同源性，而不少蛋白缺少可识别的同源物，限制了这类方法的效力。
来源：PLOS Genetics · journals.plos.org
by Chunxiang Peng, Henry Schreiber, Chengxin Zhang, Quancheng Liu, Scott Hultgren, Lydia Freddolino
The rapid advancement of high-throughput sequencing technologies has vastly increased the number of known protein sequences, but the experimental characterization of their structures and functions lags behind. This gap in knowledge impedes our understanding of biological mechanisms of these proteins, hinders the interpretation of high-throughput experiments, and exposes a significant challenge in modern biology: deducing the structural and functional information of proteins based on their sequences. Most computational approaches rely on homology with well-annotated proteins, yet many proteins lack identifiable homologues, reducing the power of this approach. Here, we integrated cutting-edge protein structure and function prediction methods to develop a complete sequence-structure-function pipeline that predicts structures and functions based on primary sequences. We applied this pipeline to predict the structure and function of all proteins in Escherichia coli UTI89, a model strain of uropathogenic E. coli. Based on the predicted functions, we performed enrichment analysis on the whole genome and revealed the possible roles and related biological mechanisms of poorly annotated proteins in this organism. Moreover, the performance of our pipeline was further validated through detailed case studies of the UTI89_C0931 and ybtS genes. Finally, we compiled the UTI89 structure and function database (https://seq2fun.dcmb.med.umich.edu/UTI89), offering it as a crucial resource to aid researchers in elucidating the roles of unannotated proteins. This database aims to bridge critical knowledge gaps in microbial pathogenicity and resistance, enhancing our capacity to tackle emerging health threats.