Analysis and Mining of Protein Backbone Mirror Structures

Abstract

With the rapid development of structural biology and computational biology, in-depth research on protein structure has become the key to understanding the essence of life activities. The mirror structure of the protein main chain, as a special structural form, its mining work not only helps to reveal the relationship between the structure and function of proteins, but also provides new ideas for drug design and protein engineering. The study of its mirror symmetry provides a brand-new perspective for revealing the chiral constraints and evolutionary laws of biomolecules. Based on advanced structural analysis algorithms and data mining techniques, this paper systematically mines the main chain mirror isomers of natural proteins in the Protein Database (PDB), breaking through the limitations of traditional research on the chirality of side chains. By establishing an image generation model based on Z-axis coordinate inversion, efficient and accurate comparison of the main chain image structure has been achieved. This study constructed the first database of protein main chain mirror isomers (MirrorPDB) and open-sourced the mirror analysis toolkit, providing data and methodological support for the design of chiral drugs and the development of protein folding theory. It has opened up a new way for the in-depth exploration of protein structure. The proposed mining method is expected to become an important tool for analyzing the relationship between the complex structure and function of proteins, which is of great significance for promoting theoretical and applied research in related fields.