Ligand Binding Prediction Using Protein Structure Graphs and Residual Graph Attention Networks Article Swipe
Mohit Pandey
,
Mariia Radaeva
,
Hazem Mslati
,
Olivia Garland
,
Michael Fernández
,
Martin Ester
,
Artem Cherkasov
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/molecules27165114
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/molecules27165114
Computational prediction of ligand–target interactions is a crucial part of modern drug discovery as it helps to bypass high costs and labor demands of in vitro and in vivo screening. As the wealth of bioactivity data accumulates, it provides opportunities for the development of deep learning (DL) models with increasing predictive powers. Conventionally, such models were either limited to the use of very simplified representations of proteins or ineffective voxelization of their 3D structures. Herein, we present the development of the PSG-BAR (Protein Structure Graph-Binding Affinity Regression) approach that utilizes 3D structural information of the proteins along with 2D graph representations of ligands. The method also introduces attention scores to selectively weight protein regions that are most important for ligand binding. Results: The developed approach demonstrates the state-of-the-art performance on several binding affinity benchmarking datasets. The attention-based pooling of protein graphs enables identification of surface residues as critical residues for protein–ligand binding. Finally, we validate our model predictions against an experimental assay on a viral main protease (Mpro)—the hallmark target of SARS-CoV-2 coronavirus.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/molecules27165114
- https://www.mdpi.com/1420-3049/27/16/5114/pdf?version=1660214839
- OA Status
- gold
- Cited By
- 19
- References
- 63
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4290998851
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Raw OpenAlex JSON
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https://openalex.org/W4290998851Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/molecules27165114Digital Object Identifier
- Title
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Ligand Binding Prediction Using Protein Structure Graphs and Residual Graph Attention NetworksWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
-
2022-08-11Full publication date if available
- Authors
-
Mohit Pandey, Mariia Radaeva, Hazem Mslati, Olivia Garland, Michael Fernández, Martin Ester, Artem CherkasovList of authors in order
- Landing page
-
https://doi.org/10.3390/molecules27165114Publisher landing page
- PDF URL
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https://www.mdpi.com/1420-3049/27/16/5114/pdf?version=1660214839Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://www.mdpi.com/1420-3049/27/16/5114/pdf?version=1660214839Direct OA link when available
- Concepts
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Computational biology, Drug discovery, Pooling, Ligand (biochemistry), Graph, Computer science, Protein ligand, Target protein, Chemistry, Artificial intelligence, Machine learning, Biology, Biochemistry, Theoretical computer science, Receptor, GeneTop concepts (fields/topics) attached by OpenAlex
- Cited by
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19Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4, 2024: 10, 2023: 4, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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63Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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