{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T19:23:24Z","timestamp":1775330604154,"version":"3.50.1"},"reference-count":63,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T00:00:00Z","timestamp":1748995200000},"content-version":"vor","delay-in-days":34,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"National Institute of Allergy and Infectious Diseases of the National Institutes of Health","award":["R01 AI111965"],"award-info":[{"award-number":["R01 AI111965"]}]},{"name":"National Health and Medical Research Council of Australia","award":["APP1127948"],"award-info":[{"award-number":["APP1127948"]}]},{"name":"National Health and Medical Research Council of Australia","award":["APP1144652"],"award-info":[{"award-number":["APP1144652"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Antimicrobial peptides (AMPs) are short peptides that play critical roles in diverse biological processes and exhibit functional activities against target organisms. While numerous methods have demonstrated the effectiveness of deep neural networks for AMP identification using sequence features; nevertheless, higher-level peptide characteristics\u2014such as 3D structure and geometric surface features\u2014have not been comprehensively explored. To address this gap, we introduce the SSFGM-Model (Sequence, Structure, Surface, Graph, and Geometric-based Model), a novel framework that integrates multiple feature types to enhance AMP identification. The model represents each peptide sequence as a graph, where nodes are characterized by amino acid features derived from ProteinBERT, ESM-2, and One-hot embeddings. Graph convolutional networks and an attention mechanism are employed to capture high-order structural and sequential relationships. Additionally, surface geometry and physicochemical properties are processed using a geometric neural network. Finally, a feature fusion strategy combines the outputs from these subnetworks to enable robust AMP identification. Extensive benchmarking experiments demonstrate that the SSFGM-Model outperforms current state-of-the-art methods. An ablation study further confirms the critical role of sequence, structural, and surface features in AMP identification. The key contribution of this work is the innovative integration of multiple levels of peptide characteristics and the combination of geometric and graph neural networks. This approach provides a more comprehensive understanding of the sequence-structure\u2013function relationship of peptides, paving the way for more accurate AMP prediction. The SSFGM-Model has a significant potential for applications in the discovery and design of novel AMP-based therapeutics. The source code is publicly available at https:\/\/github.com\/ggcameronnogg\/SSFGM-Model.<\/jats:p>","DOI":"10.1093\/bib\/bbaf261","type":"journal-article","created":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T05:15:32Z","timestamp":1749014132000},"source":"Crossref","is-referenced-by-count":9,"title":["Multimodal geometric learning for antimicrobial peptide identification by leveraging alphafold2-predicted structures and surface features"],"prefix":"10.1093","volume":"26","author":[{"given":"Zehua","family":"Sun","sequence":"first","affiliation":[{"name":"Department of Materials Science and Engineering, Faculty of Engineering, Monash University , 20 Research Way, New Horizons, Clayton, Victoria 3800 ,","place":["Australia"]},{"name":"Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Wellington Rd, Clayton, Melbourne, VIC 3800 ,","place":["Australia"]}]},{"given":"Jing","family":"Xu","sequence":"additional","affiliation":[{"name":"Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Wellington Rd, Clayton, Melbourne, VIC 3800 ,","place":["Australia"]},{"name":"Monash Data Futures Institute, Monash University , Wellington Rd, Clayton, Melbourne, VIC 3800 ,","place":["Australia"]}]},{"given":"Yumeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Wellington Rd, Clayton, Melbourne, VIC 3800 ,","place":["Australia"]},{"name":"Monash Data Futures Institute, Monash University , Wellington Rd, Clayton, Melbourne, VIC 3800 ,","place":["Australia"]}]},{"given":"Yiwen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University , 553 St Kilda Road, Melbourne, VIC 3004 ,","place":["Australia"]}]},{"given":"Zhikang","family":"Wang","sequence":"additional","affiliation":[{"name":"Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Wellington Rd, Clayton, Melbourne, VIC 3800 ,","place":["Australia"]},{"name":"Monash Data Futures Institute, Monash University , Wellington Rd, Clayton, Melbourne, VIC 3800 ,","place":["Australia"]}]},{"given":"Xiaoyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Wellington Rd, Clayton, Melbourne, VIC 3800 ,","place":["Australia"]},{"name":"Monash Data Futures Institute, Monash University , Wellington Rd, Clayton, Melbourne, VIC 3800 ,","place":["Australia"]}]},{"given":"Shanshan","family":"Li","sequence":"additional","affiliation":[{"name":"Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University , 553 St Kilda Road, Melbourne, VIC 3004 ,","place":["Australia"]}]},{"given":"Yuming","family":"Guo","sequence":"additional","affiliation":[{"name":"Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University , 553 St Kilda Road, Melbourne, VIC 3004 ,","place":["Australia"]}]},{"given":"Hsin Hui","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Materials Science and Engineering, Faculty of Engineering, Monash University , 20 Research Way, New Horizons, Clayton, Victoria 3800 ,","place":["Australia"]},{"name":"Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Wellington Rd, Clayton, Melbourne, VIC 3800 ,","place":["Australia"]}]},{"given":"Jiangning","family":"Song","sequence":"additional","affiliation":[{"name":"Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Wellington Rd, 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