A Way for Finding Ligands for New Binding Sites
Author:
Affiliation:
1. Institute of Biomedical Chemistry, Moscow, Russia
2. Institute of Biomedical Chemistry, Moscow, Russia; Pirogov Russian National Research Medical University, Moscow, Russia
Abstract
Publisher
Institute of Biochemistry
Subject
General Medicine
Reference25 articles.
1. Shin W.-H., Christoffer C.W., Kihara D. (2017) In silico structure-based approaches to discover protein-protein interaction-targeting drugs. Methods, 131, 22�32.
2. Kandel J., Tayara H., Chong K.T. (2021) PUResNet: prediction of protein-ligand binding sites using deep residual neural network. J. Cheminform., 13(1), 65.
3. Wang K., Zhou R., Li Y., Li M. (2021) DeepDTAF: a deep learning method to predict protein�ligand binding affinity. Brief. Bioinform., 22(5), bbab072.
4. Zhao J., Cao Y., Zhang L. (2020) Exploring the computational methods for protein-ligand binding site prediction. Comput. Struct. Biotechnol. J., 18, 417�426.
5. Roche D., Brackenridge D., McGuffin L. (2015) Proteins and their interacting partners: an introduction to protein�ligand binding site prediction methods. Int. J. Mol. Sci., 16(12), 29829�29842.
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