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Recent advances in artificial intelligence, particularly deep learning, have demonstrated superior performance over traditional empirical and physics-based methods for this task, enabled by the growing availability of structural and experimental affinity data. In this work, we introduce DeepGGL, a deep convolutional neural network that integrates residual connections and an attention mechanism within a geometric graph learning framework. By leveraging multiscale weighted colored bipartite subgraphs, DeepGGL effectively captures fine-grained atom-level interactions in protein-ligand complexes across multiple scales. We benchmarked DeepGGL against established models on CASF-2013 and CASF-2016, where it achieved state-of-the-art performance with significant improvements across diverse evaluation metrics. To further assess robustness and generalization, we tested the model on the CSAR-NRC-HiQ dataset and the PDBbind v2019 holdout set. DeepGGL consistently maintained high predictive accuracy, highlighting its adaptability and reliability for binding affinity prediction in structure-based drug discovery.<\/jats:p>","DOI":"10.1186\/s12859-025-06347-2","type":"journal-article","created":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T09:45:45Z","timestamp":1766051145000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A geometric graph-based deep learning model for drug-target affinity prediction"],"prefix":"10.1186","volume":"27","author":[{"given":"Md Masud","family":"Rana","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Farjana Tasnim","family":"Mukta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duc D.","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,12,18]]},"reference":[{"issue":"1","key":"6347_CR1","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1038\/nprot.2006.28","volume":"1","author":"A Velazquez-Campoy","year":"2006","unstructured":"Velazquez-Campoy A, Freire E. 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