Lobanov Michail Yu, Surin Alexey A, Galzitskaya Oxana V
Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Russia.
Faculty of Informatics and Computer Engineering, MIREA-Russian Technological University, 119454 Moscow, Russia.
Int J Mol Sci. 2024 Dec 21;25(24):13680. doi: 10.3390/ijms252413680.
The amino acid composition of proteins depends on many factors. It varies in organisms that are distant in taxonomic position. The amino acid composition of proteins depends on the localization of proteins in cells and tissues and the structure of proteins. The question arises: is it possible to separate different proteomes using only the amino acid composition of proteins? Is it possible to determine, considering only its amino acid composition, to what structural class the protein under study will belong? We have developed a method and a measure that maximally separate two sets of proteins. As a result, we assign each protein an R-value, positive values of which are more characteristic of the first set, and negative ones-of the second. By studying the distribution of R in two sets, we can determine how much these sets differ in composition. Also, when examining a new protein, we can determine if it is more similar to the first set or the second. In this paper, we show that using only amino acid composition, it is possible to separate sets of proteins belonging to different organisms, as well as proteins that differ in function or structure. In all cases, we assign to proteins a measure R that maximally separates the studied sets. This approach can be further used to annotate proteins with unknown functions.
蛋白质的氨基酸组成取决于许多因素。在分类学位置上相距较远的生物体中，其氨基酸组成会有所不同。蛋白质的氨基酸组成取决于蛋白质在细胞和组织中的定位以及蛋白质的结构。问题来了：仅利用蛋白质的氨基酸组成能否分离不同的蛋白质组？仅考虑其氨基酸组成，能否确定所研究的蛋白质属于何种结构类别？我们开发了一种方法和一种度量，能最大程度地分离两组蛋白质。结果，我们为每种蛋白质赋予一个R值，其正值更具第一组的特征，负值则更具第二组的特征。通过研究两组中R值的分布，我们可以确定这两组在组成上的差异程度。此外，在检测一种新蛋白质时，我们可以确定它与第一组还是第二组更相似。在本文中，我们表明仅使用氨基酸组成，就有可能分离属于不同生物体的蛋白质组，以及功能或结构不同的蛋白质。在所有情况下，我们都为蛋白质赋予一个能最大程度分离所研究组别的度量R。这种方法可进一步用于注释功能未知的蛋白质。
