Computer Science > Machine Learning
arXiv:2406.09346 (cs)
[Submitted on 13 Jun 2024 (v1), last revised 25 Jun 2024 (this version, v2)]
Title:Scoreformer: A Surrogate Model For Large-Scale Prediction of Docking Scores
Authors:Álvaro Ciudad,Adrián Morales-Pastor,Laura Malo,Isaac Filella-Mercè,Victor Guallar,Alexis Molina
View a PDF of the paper titled Scoreformer: A Surrogate Model For Large-Scale Prediction of Docking Scores, by \'Alvaro Ciudad and 5 other authors
View PDFHTML (experimental)Abstract:In this study, we present ScoreFormer, a novel graph transformer model designed to accurately predict molecular docking scores, thereby optimizing high-throughput virtual screening (HTVS) in drug discovery. The architecture integrates Principal Neighborhood Aggregation (PNA) and Learnable Random Walk Positional Encodings (LRWPE), enhancing the model's ability to understand complex molecular structures and their relationship with their respective docking scores. This approach significantly surpasses traditional HTVS methods and recent Graph Neural Network (GNN) models in both recovery and efficiency due to a wider coverage of the chemical space and enhanced performance. Our results demonstrate that ScoreFormer achieves competitive performance in docking score prediction and offers a substantial 1.65-fold reduction in inference time compared to existing models. We evaluated ScoreFormer across multiple datasets under various conditions, confirming its robustness and reliability in identifying potential drug candidates rapidly.
| Comments: | Accepted at the 1st Machine Learning for Life and Material Sciences Workshop at ICML 2024 |
| Subjects: | Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Biomolecules (q-bio.BM) |
| Cite as: | arXiv:2406.09346 [cs.LG] |
| (orarXiv:2406.09346v2 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2406.09346 arXiv-issued DOI via DataCite |
Submission history
From: Alexis Molina [view email][v1] Thu, 13 Jun 2024 17:31:02 UTC (481 KB)
[v2] Tue, 25 Jun 2024 13:25:08 UTC (498 KB)
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View a PDF of the paper titled Scoreformer: A Surrogate Model For Large-Scale Prediction of Docking Scores, by \'Alvaro Ciudad and 5 other authors
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