Department of Biology, Brooklyn College of the City University of New York, Brooklyn, NY, USA.
The Biochemistry Ph.D. Program, The Graduate Center of the City University of New York, New York, NY, USA.
Methods Mol Biol. 2022;2364:363-425. doi: 10.1007/978-1-0716-1661-1_19.
Proteomic analyses have become an essential part of the toolkit of the molecular biologist, given the widespread availability of genomic data and open source or freely accessible bioinformatics software. Tools are available for detecting homologous sequences, recognizing functional domains, and modeling the three-dimensional structure for any given protein sequence, as well as for predicting interactions with other proteins or macromolecules. Although a wealth of structural and functional information is available for many cytoskeletal proteins, with representatives spanning all of the major subfamilies, the majority of cytoskeletal proteins remain partially or totally uncharacterized. Moreover, bioinformatics tools provide a means for studying the effects of synthetic mutations or naturally occurring variants of these cytoskeletal proteins. This chapter discusses various freely available proteomic analysis tools, with a focus on in silico prediction of protein structure and function. The selected tools are notable for providing an easily accessible interface for the novice while retaining advanced functionality for more experienced computational biologists.
蛋白质组学分析已成为分子生物学家工具包的重要组成部分，因为基因组数据广泛可用，并且有开源或免费的生物信息学软件。现在有工具可用于检测同源序列、识别功能域以及为任何给定的蛋白质序列建模三维结构，还可用于预测与其他蛋白质或大分子的相互作用。尽管有大量的结构和功能信息可用于许多细胞骨架蛋白，其中有代表横跨所有主要亚家族的成员，但大多数细胞骨架蛋白仍然部分或完全没有特征。此外，生物信息学工具为研究这些细胞骨架蛋白的合成突变或自然发生的变体的影响提供了一种手段。本章讨论了各种免费的蛋白质组学分析工具，重点是蛋白质结构和功能的计算机预测。所选工具的显著特点是为新手提供了一个易于访问的界面，同时为更有经验的计算生物学家保留了高级功能。
