Predicting protein-ligand binding residues with deep convolutional neural networks

BMC Bioinformatics
Yifeng CuiXikun Wang

Abstract

Ligand-binding proteins play key roles in many biological processes. Identification of protein-ligand binding residues is important in understanding the biological functions of proteins. Existing computational methods can be roughly categorized as sequence-based or 3D-structure-based methods. All these methods are based on traditional machine learning. In a series of binding residue prediction tasks, 3D-structure-based methods are widely superior to sequence-based methods. However, due to the great number of proteins with known amino acid sequences, sequence-based methods have considerable room for improvement with the development of deep learning. Therefore, prediction of protein-ligand binding residues with deep learning requires study. In this study, we propose a new sequence-based approach called DeepCSeqSite for ab initio protein-ligand binding residue prediction. DeepCSeqSite includes a standard edition and an enhanced edition. The classifier of DeepCSeqSite is based on a deep convolutional neural network. Several convolutional layers are stacked on top of each other to extract hierarchical features. The size of the effective context scope is expanded as the number of convolutional layers increases. The long-distance depe...Continue Reading

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Citations

Jul 12, 2018·Journal of Computer-aided Molecular Design·Jocelyn SunseriDavid Ryan Koes
Jun 4, 2019·Briefings in Bioinformatics·Mengying SunFei Wang
Sep 29, 2020·Scientific Reports·Jordan J ClarkHeather A Carlson
Dec 24, 2019·Briefings in Bioinformatics·Qiang ShiZhidong Xue
Jul 1, 2020·Frontiers in Bioengineering and Biotechnology·Liu LiuShuang Xu
Mar 7, 2020·Computational and Structural Biotechnology Journal·Jingtian ZhaoLe Zhang
Jan 7, 2020·Seminars in Cancer Biology·Naiem T IssaSivanesan Dakshanamurthy
Apr 10, 2021·Emerging Topics in Life Sciences·Nitu SinghKinshuk Raj Srivastava
Apr 20, 2021·Journal of Chemical Information and Modeling·Antonina L NazarovaPankaj Rajak
Aug 11, 2021·Journal of Chemical Information and Modeling·Rishal AggarwalU Deva Priyakumar
Jul 6, 2021·Current Opinion in Structural Biology·Clemens RauerChristine A Orengo

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Methods Mentioned

BETA
interaction prediction
protein folding
feature extraction
RSA

Software Mentioned

enDCS
COACH
NMT
en
Aug
DCS
SITA
DeepCSeqSite
TASSER Suite
ConCavity

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