4.6 Article

Development of a TSR-Based Method for Protein 3-D Structural Comparison With Its Applications to Protein Classification and Motif Discovery

期刊

FRONTIERS IN CHEMISTRY
卷 8, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fchem.2020.602291

关键词

protein structure comparison; triangular spatial relationship; structure motifs; protein classification; protein structure and function relation; protein secondary structure; molecular dynamics simulation; protein conformational change

资金

  1. Louisiana Board of Regents [LEQSF(2015-18)-RD-B-06]

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Development of protein 3-D structural comparison methods is crucial for understanding protein functions, but existing methods have limitations. Researchers have developed a novel method based on Triangular Spatial Relationship (TSR), which accurately quantifies structural similarity and provides deeper insights into proteases and kinases.
Development of protein 3-D structural comparison methods is important in understanding protein functions. At the same time, developing such a method is very challenging. In the last 40 years, ever since the development of the first automated structural method, similar to 200 papers were published using different representations of structures. The existing methods can be divided into five categories: sequence-, distance-, secondary structure-, geometry-based, and network-based structural comparisons. Each has its uniqueness, but also limitations. We have developed a novel method where the 3-D structure of a protein is modeled using the concept of Triangular Spatial Relationship (TSR), where triangles are constructed with the C-alpha atoms of a protein as vertices. Every triangle is represented using an integer, which we denote as key, A key is computed using the length, angle, and vertex labels based on a rule-based formula, which ensures assignment of the same key to identical TSRs across proteins. A structure is thereby represented by a vector of integers. Our method is able to accurately quantify similarity of structure or substructure by matching numbers of identical keys between two proteins. The uniqueness of our method includes: (i) a unique way to represent structures to avoid performing structural superimposition; (ii) use of triangles to represent substructures as it is the simplest primitive to capture shape; (iii) complex structure comparison is achieved by matching integers corresponding to multiple TSRs. Every substructure of one protein is compared to every other substructure in a different protein. The method is used in the studies of proteases and kinases because they play essential roles in cell signaling, and a majority of these constitute drug targets. The new motifs or substructures we identified specifically for proteases and kinases provide a deeper insight into their structural relations. Furthermore, the method provides a unique way to study protein conformational changes. In addition, the results from CATH and SCOP data sets clearly demonstrate that our method can distinguish alpha helices from beta pleated sheets and vice versa. Our method has the potential to be developed into a powerful tool for efficient structure-BLAST search and comparison, just as BLAST is for sequence search and alignment.

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