Protein homodimers structure prediction based on deep neural network
https://doi.org/10.37661/1816-0301-2020-17-2-44-53
Abstract
Structural prediction of protein-protein complexes has important application in such domains as modeling of biological processes and drug design. Homodimers (complexes which consist of two identical proteins) are the most common type of protein complexes in nature but there is still no universal algorithm to predict their 3D structures. Experimental techniques to identify the structure of protein complex require enormous amount of time and resources, and each method has its own limitations. Recently Deep Neural Networks allowed to predict structures of individual proteins greatly prevailing in accuracy over other algorithmic approaches. Building on the idea of this approach, we developed an algorithm to model the 3D structure of homodimer based on deep learning. It consists of two major steps: at the first step a protein complex contact map is predicted with the deep convolutional neural network, and the second stage is used to predict 3D structure of homodimer based on obtained contact map and optimization procedure. The use of the neural network in combination with optimization procedure based on gradient descent method allowed to predict structures for protein homodimers. The suggested approach was tested and validated on a dataset of protein homodimers from Protein Data Bank (PDB). The developed procedure could be also used for evaluating protein homodimer models as one of the stages in drug compounds developing.
About the Authors
A. Y. Hadarovich
The United Institute of Informatics Problems of the National Academy of Sciences of Belarus; Belarusian State University
Belarus
Belarus
Anna Y. Hadarovich, Researcher
Minsk
A. A. Kalinouski
The United Institute of Informatics Problems of the National Academy of Sciences of Belarus
Belarus
Belarus
Alexander A. Kalinouski, Researcher
Minsk
A. V. Tuzikov
The United Institute of Informatics Problems of the National Academy of Sciences of Belarus
Belarus
Belarus
Alexander V. Tuzikov, Corresponding Member, Dr. Sci. (Phys.-Math.), Professor, General Director
Minsk
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Review
For citations:
Hadarovich A.Y., Kalinouski A.A., Tuzikov A.V. Protein homodimers structure prediction based on deep neural network. Informatics. 2020;17(2):44-53. (In Russ.) https://doi.org/10.37661/1816-0301-2020-17-2-44-53
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