Cruz Leonardo Magalhães, Trefflich Sheyla, Weiss Vinícius Almir, Castro Mauro Antônio Alves
Department of Biochemistry and Molecular Biology, Federal University of Paraná (UFPR), Curitiba, PR, Brazil.
Sector of Professional and Technological Education, Federal University of Paraná (UFPR), Curitiba, PR, Brazil.
Methods Mol Biol. 2017;1654:55-75. doi: 10.1007/978-1-4939-7231-9_5.
Protein function is a concept that can have different interpretations in different biological contexts, and the number and diversity of novel proteins identified by large-scale "omics" technologies poses increasingly new challenges. In this review we explore current strategies used to predict protein function focused on high-throughput sequence analysis, as for example, inference based on sequence similarity, sequence composition, structure, and protein-protein interaction. Various prediction strategies are discussed together with illustrative workflows highlighting the use of some benchmark tools and knowledge bases in the field.
蛋白质功能是一个在不同生物学背景下可能有不同解释的概念，通过大规模“组学”技术鉴定出的新型蛋白质的数量和多样性带来了越来越多的新挑战。在本综述中，我们探讨了目前用于预测蛋白质功能的策略，重点是高通量序列分析，例如基于序列相似性、序列组成、结构和蛋白质 - 蛋白质相互作用的推断。讨论了各种预测策略，并结合说明性工作流程，突出了该领域一些基准工具和知识库的使用。
