{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T15:55:17Z","timestamp":1774626917923,"version":"3.50.1"},"reference-count":114,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T00:00:00Z","timestamp":1774396800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Chinese Academy of Sciences President\u2019s International Fellowship Initiative","award":["2024PG0002"],"award-info":[{"award-number":["2024PG0002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Life"],"abstract":"<jats:p>The escalating antimicrobial resistance (AMR) crisis necessitates the development of innovative anti-infectives with novel mechanisms of action. Nevertheless, research on natural products remains constrained by low-throughput screening and limited mechanistic insights. Artificial intelligence (AI) is catalyzing a pivotal paradigm shift\u2014from the mere isolation of active compounds to precisely deciphering their modes of action. This review highlights AI\u2019s transformative role in bridging ethnopharmacological knowledge and modern pharmacology to decode the mechanisms of plant-derived anti-infectives. Case studies on berberine, baicalein, danshensu derivatives, and rosmarinic acid derivatives from Coleus amboinicus illustrate AI\u2019s capacity to map traditional therapeutic concepts to specific pathways (e.g., biofilm inhibition, inflammasome modulation) and to predict precise binding interactions and pharmacophores with high precision. Leveraging statistical correlations between ethnobotanical usage patterns and chemical similarity, we propose a \u201cKnowledge\u2013Data\u2013Mechanism\u201d three-layer framework centered on deep mechanistic insight. Integrating Chinese initiatives, such as the CNDR (China\u2019s National Drug Repository) database and the TCM-AI platform, with global traditional medicine wisdom, this strategy provides an actionable roadmap for modernizing anti-infective discovery. Validated applications of this paradigm have demonstrated order-of-magnitude acceleration in mechanistic characterization, rapidly yielding structurally novel agents with well-defined, target-specific actions\u2014a critical advancement in addressing the urgent global threat of antimicrobial resistance.<\/jats:p>","DOI":"10.3390\/life16040540","type":"journal-article","created":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T10:07:13Z","timestamp":1774433233000},"page":"540","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AI-Driven Plant-Derived Anti-Infectives: Integrating Traditional Wisdom into Precision Medicine Against AMR"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-5295-4642","authenticated-orcid":false,"given":"Zhiwu","family":"Yin","sequence":"first","affiliation":[{"name":"Netclass Technology Inc., Shanghai 200072, China"},{"name":"Academy for Smart Health and Longevity R&D, University of Saint Joseph, Macao SAR, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7961-3488","authenticated-orcid":false,"given":"Changbin","family":"Chen","sequence":"additional","affiliation":[{"name":"Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai 201203, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5331-022X","authenticated-orcid":false,"given":"Xing","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China"}]},{"given":"Wenhao","family":"Luo","sequence":"additional","affiliation":[{"name":"Academy for Smart Health and Longevity R&D, University of Saint Joseph, Macao SAR, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5086-059X","authenticated-orcid":false,"given":"Paulo","family":"Quaresma","sequence":"additional","affiliation":[{"name":"Computer Science Department, School of Sciences and Technology, University of \u00c9vora, Rua Rom\u00e3o Ramalho 59, 7000-671 \u00c9vora, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1439-7906","authenticated-orcid":false,"given":"Jianbiao","family":"Dai","sequence":"additional","affiliation":[{"name":"Netclass Technology Inc., Shanghai 200072, China"},{"name":"Academy for Smart Health and Longevity R&D, University of Saint Joseph, Macao SAR, China"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,25]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2025). Global Antibiotic Resistance Surveillance Report 2025: Summary, WHO."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Li, S., Zhou, Y., Yan, Y., Qin, Y., Weng, Q., and Sun, L. (2024). Structure-Based Virtual Screening, ADMET Properties Prediction and Molecular Dynamics Studies Reveal Potential Inhibitors of Mycoplasma pneumoniae HPrK\/P. Life, 14.","DOI":"10.3390\/life14060657"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/S1473-3099(17)30753-3","article-title":"Discovery, Research, and Development of New Antibiotics: The WHO Priority List of Antibiotic-Resistant Bacteria and Tuberculosis","volume":"18","author":"Tacconelli","year":"2018","journal-title":"Lancet Infect. Dis."},{"key":"ref_4","first-page":"1342","article-title":"Artificial Intelligence in Natural Products Research","volume":"23","author":"Yuan","year":"2025","journal-title":"Chin. J. Nat. Med."},{"key":"ref_5","first-page":"1377","article-title":"Identification of Natural Product-Based Drug Combination (NPDC) Using Artificial Intelligence","volume":"23","author":"Niu","year":"2025","journal-title":"Chin. J. Nat. Med."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"726","DOI":"10.1038\/s41570-021-00313-1","article-title":"Towards the Sustainable Discovery and Development of New Antibiotics","volume":"5","author":"Miethke","year":"2021","journal-title":"Nat. Rev. Chem."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"770","DOI":"10.1021\/acs.jnatprod.9b01285","article-title":"Natural Products as Sources of New Drugs over the Nearly Four Decades from 01\/1981 to 09\/2019","volume":"83","author":"Newman","year":"2020","journal-title":"J. Nat. Prod."},{"key":"ref_8","unstructured":"Flora of China Editorial Committee (2004). Flora of China, Science Press."},{"key":"ref_9","first-page":"1358","article-title":"Advancing Network Pharmacology with Artificial Intelligence: The Next Paradigm in Traditional Chinese Medicine","volume":"23","author":"Shao","year":"2025","journal-title":"Chin. J. Nat. Med."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Owumi, S., Olanlokun, J.O., Wu, B., Duro-Ladipo, A.M., Oyelere, S.E., Khan, S.I., and Oyelere, A.K. (2024). Elucidation of the Active Agents in a West African Ground Herbal Medicine Formulation That Elicit Antimalarial Activities in In Vitro and In Vivo Models. Molecules, 29.","DOI":"10.3390\/molecules29235658"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1007\/s12231-025-09647-z","article-title":"Random Patterns of Medicinal Plants on a Phylogeny Do Not Imply Random Selections of Medicinal Plants","volume":"79","author":"Yessoufou","year":"2025","journal-title":"Econ. Bot."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1002\/ppp3.10566","article-title":"Phylogeny and Bioprospecting: The Diversity of Medicinal Plants Used in Cancer Management","volume":"7","author":"Thompson","year":"2025","journal-title":"Plants People Planet"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"e2100880118","DOI":"10.1073\/pnas.2100880118","article-title":"Functional Genomics and Metabolomics Advance the Ethnobotany of the Samoan Traditional Medicine \u201cMatalafi\u201d","volume":"118","author":"Woolner","year":"2021","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1038\/s41573-020-00114-z","article-title":"Natural Products in Drug Discovery: Advances and Opportunities","volume":"20","author":"Atanasov","year":"2021","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4673","DOI":"10.1007\/s00210-024-03622-6","article-title":"Natural products as drug leads: Exploring their potential in drug discovery and development","volume":"398","author":"Singh","year":"2025","journal-title":"Naunyn Schmiedebergs Arch. Pharmacol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e70146","DOI":"10.1002\/ctm2.70146","article-title":"Engineering the Future of Medicine: Natural Products, Synthetic Biology and Artificial Intelligence for Next-Generation Therapeutics","volume":"15","author":"Bode","year":"2025","journal-title":"Clin. Transl. Med."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"108833","DOI":"10.1016\/j.pharmthera.2025.108833","article-title":"Recent Advances in Target Identification Technology of Natural Products","volume":"269","author":"Liu","year":"2025","journal-title":"Pharmacol. Ther."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"100316","DOI":"10.1016\/j.ibmed.2025.100316","article-title":"Artificial Intelligence for Natural Product Drug Discovery and Development: Current Landscape, Applications, and Future Directions","volume":"12","author":"Othman","year":"2025","journal-title":"Intell. Based Med."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Niazi, S.K. (2025). Artificial Intelligence in Small-Molecule Drug Discovery: A Critical Review of Methods, Applications, and Real-World Outcomes. Pharmaceuticals, 18.","DOI":"10.3390\/ph18091271"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1016\/j.cell.2020.01.021","article-title":"A Deep Learning Approach to Antibiotic Discovery","volume":"180","author":"Stokes","year":"2020","journal-title":"Cell"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"108642","DOI":"10.1016\/j.biotechadv.2025.108642","article-title":"Current Advancement in AI-Integrated Drug Discovery: Methods and Applications","volume":"83","author":"Mathur","year":"2025","journal-title":"Biotechnol. Adv."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Visan, A.I., and Negut, I. (2024). Integrating Artificial Intelligence for Drug Discovery in the Context of Revolutionizing Drug Delivery. Life, 14.","DOI":"10.3390\/life14020233"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"100102","DOI":"10.1016\/j.pharmr.2025.100102","article-title":"Leading Artificial Intelligence-Driven Drug Discovery Platforms: 2025 Landscape and Global Outlook","volume":"78","author":"Dharmasivam","year":"2026","journal-title":"Pharmacol. Rev."},{"key":"ref_24","first-page":"7","article-title":"Antimicrobial Resistance Crisis: Could Artificial Intelligence Be the Solution?","volume":"11","author":"Liu","year":"2024","journal-title":"Mil. Med. Res."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"e30","DOI":"10.1016\/S0140-6736(20)30304-4","article-title":"Baricitinib as Potential Treatment for 2019-nCoV Acute Respiratory Disease","volume":"395","author":"Richardson","year":"2020","journal-title":"Lancet"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1038\/s41587-024-02143-0","article-title":"A Small-Molecule TNIK Inhibitor Targets Fibrosis in Preclinical and Clinical Models","volume":"43","author":"Ren","year":"2025","journal-title":"Nat. Biotechnol."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Manan, A., Baek, E., Ilyas, S., and Lee, D. (2025). Digital Alchemy: The Rise of Machine and Deep Learning in Small-Molecule Drug Discovery. Int. J. Mol. Sci., 26.","DOI":"10.3390\/ijms26146807"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1038\/nrd.2017.111","article-title":"Opportunities and Challenges in Phenotypic Drug Discovery: An Industry Perspective","volume":"16","author":"Moffat","year":"2017","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1038\/nrd3480","article-title":"How Were New Medicines Discovered?","volume":"10","author":"Swinney","year":"2011","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Mihaylova, S., Tsvetkova, A., Georgieva, E., and Vankova, D. (2024). Bioactive Phyto-Compounds with Antimicrobial Effects and AI: Results of a Desk Research Study. Microorganisms, 12.","DOI":"10.3390\/microorganisms12061055"},{"key":"ref_31","first-page":"1329","article-title":"Applications of Artificial Intelligence in the Research of Molecular Mechanisms of Traditional Chinese Medicine Formulas","volume":"23","author":"Chen","year":"2025","journal-title":"Chin. J. Nat. Med."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1186\/s13020-025-01226-7","article-title":"Integrating Knowledge Graphs with Ancient Chinese Medicine Classics: Challenges and Future Prospects of Multi-Agent System Convergence","volume":"20","author":"Xiang","year":"2025","journal-title":"Chin. Med."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1186\/s13321-020-00479-8","article-title":"Could Graph Neural Networks Learn Better Molecular Representation for Drug Discovery? A Comparison Study of Descriptor-Based and Graph-Based Models","volume":"13","author":"Jiang","year":"2021","journal-title":"J. Cheminform."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"4386","DOI":"10.1021\/acs.molpharmaceut.7b01137","article-title":"Adversarial Threshold Neural Computer for Molecular de Novo Design","volume":"15","author":"Putin","year":"2018","journal-title":"Mol. Pharm."},{"key":"ref_35","first-page":"18249","article-title":"The Convolution Exponential and Generalized Sylvester Flows","volume":"33","author":"Hoogeboom","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1038\/s42256-020-00236-4","article-title":"Drug Discovery with Explainable Artificial Intelligence","volume":"2","author":"Grisoni","year":"2020","journal-title":"Nat. Mach. Intell."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"344522","DOI":"10.1016\/j.aca.2025.344522","article-title":"Machine Learning-Assisted Affinity Ultrafiltration for Bioactive Natural Products Discovery: Application to Screening of Neuraminidase Inhibitors from Medicinal Herbs","volume":"1374","author":"Chen","year":"2025","journal-title":"Anal. Chim. Acta"},{"key":"ref_38","unstructured":"Ramsundar, B., Eastman, P., Walters, P., and Pande, V. (2019). Deep Learning for the Life Sciences: Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More, O\u2019Reilly Media."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1038\/nchembio.1199","article-title":"Target Identification and Mechanism of Action in Chemical Biology and Drug Discovery","volume":"9","author":"Schenone","year":"2013","journal-title":"Nat. Chem. Biol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.bbamem.2013.04.028","article-title":"Surface Plasmon Resonance Spectroscopy for Characterisation of Membrane Protein-Ligand Interactions and Its Potential for Drug Discovery","volume":"1838","author":"Patching","year":"2014","journal-title":"Biochim. Biophys. Acta Biomembr."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1016\/j.neuron.2018.08.011","article-title":"Molecular Dynamics Simulation for All","volume":"99","author":"Hollingsworth","year":"2018","journal-title":"Neuron"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.pharmthera.2016.01.010","article-title":"Target Identification of Natural and Traditional Medicines with Quantitative Chemical Proteomics Approaches","volume":"162","author":"Wang","year":"2016","journal-title":"Pharmacol. Ther."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1038\/nri.2017.76","article-title":"Single-Cell RNA Sequencing to Explore Immune Cell Heterogeneity","volume":"18","author":"Papalexi","year":"2018","journal-title":"Nat. Rev. Immunol."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Kind, T., and Fiehn, O. (2007). Seven Golden Rules for Heuristic Filtering of Molecular Formulas Obtained by Accurate Mass Spectrometry. BMC Bioinf., 8.","DOI":"10.1186\/1471-2105-8-105"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.cbpa.2016.12.006","article-title":"Frontiers of High-Throughput Metabolomics","volume":"36","author":"Zampieri","year":"2017","journal-title":"Curr. Opin. Chem. Biol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"eaaw8412","DOI":"10.1126\/scitranslmed.aaw8412","article-title":"Off-Target Toxicity Is a Common Mechanism of Action of Cancer Drugs Undergoing Clinical Trials","volume":"11","author":"Lin","year":"2019","journal-title":"Sci. Transl. Med."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1038\/nrd.2017.232","article-title":"Automating Drug Discovery","volume":"17","author":"Schneider","year":"2018","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1038\/nature25978","article-title":"Planning Chemical Syntheses with Deep Neural Networks and Symbolic AI","volume":"555","author":"Segler","year":"2018","journal-title":"Nature"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"937","DOI":"10.1080\/17460441.2021.1915982","article-title":"Critical Assessment of AI in Drug Discovery","volume":"16","author":"Walters","year":"2021","journal-title":"Expert Opin. Drug Discov."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1038\/s41392-023-01339-1","article-title":"TCMBank-the Largest TCM Database Provides Deep Learning-Based Chinese-Western Medicine Exclusion Prediction","volume":"8","author":"Lv","year":"2023","journal-title":"Signal Transduct. Target. Ther."},{"key":"ref_51","unstructured":"Chen, K.X., Jiang, H.L., and Ji, R.Y. (2000). Computer-Aided Drug Design, Shanghai Scientific and Technical Publishers."},{"key":"ref_52","first-page":"1047","article-title":"Leveraging Microbial Natural Products for Pharmaceutical Innovation: A Vision of Inspiration and Future Prospects","volume":"23","author":"Yang","year":"2025","journal-title":"Chin. J. Nat. Med."},{"key":"ref_53","first-page":"1","article-title":"TCM Network Pharmacology: A New Trend towards Combining Computational, Experimental and Clinical Approaches","volume":"19","author":"Wang","year":"2021","journal-title":"Chin. J. Nat. Med."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"101342","DOI":"10.1016\/j.jpha.2025.101342","article-title":"Quantifying Compatibility Mechanisms in Traditional Chinese Medicine with Interpretable Graph Neural Networks","volume":"15","author":"Zeng","year":"2025","journal-title":"J. Pharm. Anal."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Zhang, G., Jiang, H., Kuai, L., Li, B., Huang, C., Fei, X., and Huang, Z. (2025). KGSD-Net: A Knowledge Graph Syndrome Differentiation Network for Syndrome Classification. Front. Med., 12.","DOI":"10.3389\/fmed.2025.1555781"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1186\/1758-2946-6-13","article-title":"TCMSP: A Database of Systems Pharmacology for Drug Discovery from Herbal Medicines","volume":"6","author":"Ru","year":"2014","journal-title":"J. Cheminform."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.18240\/ijo.2025.11.01","article-title":"Knowledge Graph for Traditional Chinese Medicine Diagnosis and Treatment of Diabetic Retinopathy: Design, Construction, and Applications","volume":"18","author":"Xiao","year":"2025","journal-title":"Int. J. Ophthalmol."},{"key":"ref_58","first-page":"621423","article-title":"Network Pharmacology: A New Approach for Chinese Herbal Medicine Research. Evidence-Based Complement","volume":"2013","author":"Zhang","year":"2013","journal-title":"Altern. Med."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"15835","DOI":"10.1073\/pnas.1202242109","article-title":"Phylogenies Reveal Predictive Power of Traditional Medicine in Bioprospecting","volume":"109","author":"Savolainen","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.jep.2017.01.052","article-title":"Traditional Mediterranean and European Herbal Medicines","volume":"199","author":"Leonti","year":"2017","journal-title":"J. Ethnopharmacol."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Himmelstein, D.S., and Baranzini, S.E. (2015). Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes. PLoS Comput. Biol., 11.","DOI":"10.1371\/journal.pcbi.1004259"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"i457","DOI":"10.1093\/bioinformatics\/bty294","article-title":"Modeling Polypharmacy Side Effects with Graph Convolutional Networks","volume":"34","author":"Zitnik","year":"2018","journal-title":"Bioinformatics"},{"key":"ref_63","first-page":"581","article-title":"Mechanism of Danshen Decoction in the Treatment of Heart Failure Based on Network Pharmacology","volume":"21","author":"Liu","year":"2023","journal-title":"Chin. J. Integr. Med. Cardio-\/Cerebrovasc. Dis."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"110","DOI":"10.3724\/SP.J.1009.2013.00110","article-title":"Traditional Chinese Medicine Network Pharmacology: Theory, Methodology and Application","volume":"11","author":"Li","year":"2013","journal-title":"Chin. J. Nat. Med."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Salian, P.K., Shrisha, H.S., Salian, S., and K, K. (2023, January 22\u201324). MPInet: Medicinal Plants Identification Using Deep Learning. Proceedings of the 2023 7th International Conference on Electronics, Communication and Aerospace Technology (ICECA), Coimbatore, India.","DOI":"10.1109\/ICECA58529.2023.10395327"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"6446","DOI":"10.1038\/s41467-025-60051-6","article-title":"Computational Exploration of Global Venoms for Antimicrobial Discovery with Venomics Artificial Intelligence","volume":"16","author":"Guan","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"4196295","DOI":"10.1155\/bmri\/4196295","article-title":"In Silico Investigation of Phytochemicals from Clinically Tested Herbal Extracts as Potential Dihydrofolate Reductase Inhibitors for Buruli Ulcer","volume":"2025","author":"Mohamed","year":"2025","journal-title":"Biomed Res. Int."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1186\/s13321-016-0130-x","article-title":"Improving Chemical Similarity Ensemble Approach in Target Prediction","volume":"8","author":"Wang","year":"2016","journal-title":"J. Cheminform."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41401-025-01710-8","article-title":"AI-driven breakthroughs in ion channel drug discovery: The future is now","volume":"47","author":"Zheng","year":"2026","journal-title":"Acta Pharmacol. Sin."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1002\/jcc.21334","article-title":"AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading","volume":"31","author":"Trott","year":"2010","journal-title":"J. Comput. Chem."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"e13099","DOI":"10.1002\/advs.202513099","article-title":"DualPG-DTA: A Large Language Model-Powered Graph Neural Network Framework for Enhanced Drug-Target Affinity Prediction and Discovery of Novel CDK9 Inhibitors Exhibiting In Vivo Anti-Leukemia Activity","volume":"13","author":"Chen","year":"2026","journal-title":"Adv. Sci."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"eads9530","DOI":"10.1126\/science.ads9530","article-title":"Deep Contrastive Learning Enables Genome-Wide Virtual Screening","volume":"391","author":"Jia","year":"2026","journal-title":"Science"},{"key":"ref_73","unstructured":"Li, S., and Tsinghua University Beijing Institute of Traditional Chinese Medicine Interdisciplinary Research Team (2026, March 19). \u201cNetwork Target-based Intelligent and Quantitative Analysis Technology and System for Traditional Chinese and Western Medicine (UNIQ System)\u201d. Awarded the Jury\u2019s Special Commendation Gold Medal at the 49th Geneva International Exhibition of Inventions, 2024. Available online: https:\/\/www.au.tsinghua.edu.cn\/info\/1133\/3672.htm."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"bbac170","DOI":"10.1093\/bib\/bbac170","article-title":"Decoding multilevel relationships with the human tissue-cell-molecule network","volume":"23","author":"Hou","year":"2022","journal-title":"Brief. Bioinform."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1109\/TCBB.2020.3017547","article-title":"CIPHER-SC: Disease-Gene Association Inference Using Graph Convolution on a Context-Aware Network with Single-Cell Data","volume":"19","author":"Zhang","year":"2022","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1934","DOI":"10.1016\/j.celrep.2019.04.052","article-title":"Dissecting the single-cell transcriptome network underlying gastric premalignant lesions and early gastric cancer","volume":"27","author":"Zhang","year":"2019","journal-title":"Cell Rep."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"3907","DOI":"10.2147\/DDDT.S514193","article-title":"Design and Evaluation of Andrographolide Analogues as SARS-CoV-2 Main Protease Inhibitors: Molecular Modeling and in vitro Studies","volume":"19","author":"Suriya","year":"2025","journal-title":"Drug Des. Dev. Ther."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Peng, X., Guo, R., Guo, F., Wang, Z., Sun, J., Guan, J., Jia, Y., Xu, Y., Huang, Y., and Zhang, M. (2026). Unified Modeling of 3D Molecular Generation via Atomic Interactions with PocketXMol. Cell, in press.","DOI":"10.1016\/j.cell.2026.01.003"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1007\/s13659-025-00521-y","article-title":"Bridging Chemical Space and Biological Efficacy: Advances and Challenges in Applying Generative Models in Structural Modification of Natural Products","volume":"15","author":"Liu","year":"2025","journal-title":"Nat. Prod. Bioprospect."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1038\/s42256-019-0017-4","article-title":"Feedback GAN for DNA optimizes protein functions","volume":"1","author":"Gupta","year":"2019","journal-title":"Nat. Mach. Intell."},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Qadri, Y.A., Shaikh, S., Ahmad, K., Choi, I., Kim, S.W., and Vasilakos, A.V. (2025). Explainable Artificial Intelligence: A Perspective on Drug Discovery. Pharmaceutics, 17.","DOI":"10.3390\/pharmaceutics17091119"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"109740","DOI":"10.1016\/j.compbiomed.2025.109740","article-title":"ABIET: An Explainable Transformer for Identifying Functional Groups in Biological Active Molecules","volume":"187","author":"Pereira","year":"2025","journal-title":"Comput. Biol. Med."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"104067","DOI":"10.1016\/j.drudis.2024.104067","article-title":"Advancing Drug Discovery with Deep Attention Neural Networks","volume":"29","author":"Lavecchia","year":"2024","journal-title":"Drug Discov. Today"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"W5","DOI":"10.1093\/nar\/gkab255","article-title":"ADMETlab 2.0: An Integrated Online Platform for Accurate and Comprehensive Predictions of ADMET Properties","volume":"49","author":"Xiong","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"157491","DOI":"10.1016\/j.phymed.2025.157491","article-title":"iCAM-Net: Interpretable Herb-Disease Association Prediction via Cross-Channel Attention and Molecular Interaction Signals","volume":"148","author":"Zheng","year":"2025","journal-title":"Phytomedicine"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1007\/s10822-025-00637-w","article-title":"Integrated Machine Learning and Deep Learning-Based Virtual Screening Framework Identifies Novel Natural GSK-3\u03b2 Inhibitors for Alzheimer\u2019s Disease","volume":"39","author":"Zhou","year":"2025","journal-title":"J. Comput.-Aided Mol. Des."},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Shah, M., Khan, F., Ahmad, I., Deng, C.L., Perveen, A., Iqbal, A., Nishan, U., Zaman, A., Ullah, R., and Ali, E.A. (2023). Computer-Aided Identification of Mycobacterium Tuberculosis Resuscitation-Promoting Factor B (RpfB) Inhibitors from Gymnema Sylvestre Natural Products. Front. Pharmacol., 14.","DOI":"10.3389\/fphar.2023.1325227"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1109\/TVCG.2025.3633887","article-title":"HypoChainer: A Collaborative System Combining LLMs and Knowledge Graphs for Hypothesis-Driven Scientific Discovery","volume":"32","author":"Shi","year":"2026","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"2068","DOI":"10.1021\/acs.jcim.7b00146","article-title":"Is Multitask Deep Learning Practical for Pharma?","volume":"57","author":"Ramsundar","year":"2017","journal-title":"J. Chem. Inf. Model."},{"key":"ref_90","doi-asserted-by":"crossref","unstructured":"Qin, J., Zhang, S., Pan, Y., Lei, X., Guo, Z., Xie, Q., Huang, K., and Huo, P. (2025). Progress and Application of Activity-Based Protein Profiling for the Discovery of Natural Product Targets. Mol. Divers., ahead of print.","DOI":"10.1007\/s11030-025-11361-w"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"2100","DOI":"10.1038\/nprot.2014.138","article-title":"The Cellular Thermal Shift Assay for Evaluating Drug Target Interactions in Cells","volume":"9","author":"Jafari","year":"2014","journal-title":"Nat. Protoc."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"2201","DOI":"10.1021\/ci100321h","article-title":"Calculations of the free energy of interaction of the c-Fos-c-Jun coiled coil: Effects of the solvation model and the inclusion of polarization effects","volume":"50","author":"Zuo","year":"2010","journal-title":"J. Chem. Inf. Model."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1039\/C9NP00004F","article-title":"Innovative Omics-Based Approaches for Prioritisation and Targeted Isolation of Natural Products\u2014New Strategies for Drug Discovery","volume":"36","author":"Wolfender","year":"2019","journal-title":"Nat. Prod. Rep."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1186\/s13321-025-00962-0","article-title":"Improving Drug Repositioning with Negative Data Labeling Using Large Language Models","volume":"17","author":"Picard","year":"2025","journal-title":"J. Cheminform."},{"key":"ref_95","first-page":"3521","article-title":"Chemical Evolution of Natural Product for Discovery and Mechanistic Exploration of Antibiotic against MRSA","volume":"148","author":"Chen","year":"2026","journal-title":"J. Am. Chem. Soc."},{"key":"ref_96","unstructured":"Li, S. (1982). Compendium of Materia Medica (Bencao Gangmu), People\u2019s Medical Publishing House."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"bbad518","DOI":"10.1093\/bib\/bbad518","article-title":"Network pharmacology: Towards the artificial intelligence-based precision traditional Chinese medicine","volume":"25","author":"Zhang","year":"2023","journal-title":"Brief. Bioinform."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"bbab342","DOI":"10.1093\/bib\/bbaa342","article-title":"Identify potent SARS-CoV-2 main protease inhibitors via a deep learning-based virtual screening approach","volume":"22","author":"Li","year":"2021","journal-title":"Brief. Bioinform."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"7761","DOI":"10.1038\/s41467-024-52061-7","article-title":"Artificial Intelligence-Accelerated Virtual Screening Platform for Drug Discovery","volume":"15","author":"Zhou","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"6303","DOI":"10.1080\/07391102.2024.2424940","article-title":"Computational Screening of Phytocompounds from C. Amboinicus Identifies Potential Inhibitors of Influenza A (H3N2) Virus by Targeting Hemagglutinin","volume":"43","author":"Hemavathi","year":"2025","journal-title":"J. Biomol. Struct. Dyn."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"153315","DOI":"10.1016\/j.phymed.2020.153315","article-title":"Systems pharmacological study illustrates the immune regulation, anti-infection, anti-inflammation, and multi-organ protection mechanism of Qing-Fei-Pai-Du decoction in the treatment of COVID-19","volume":"85","author":"Zhao","year":"2021","journal-title":"Phytomedicine"},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"e38052","DOI":"10.1097\/MD.0000000000038052","article-title":"Potential Mechanisms of Traditional Chinese Medicine in Treating Insomnia: A Network Pharmacology, GEO Validation, and Molecular-Docking Study","volume":"103","author":"Liu","year":"2024","journal-title":"Medicine"},{"key":"ref_103","doi-asserted-by":"crossref","unstructured":"Liu, Q., Wang, J., Zhu, Y., and He, Y. (2017). Ontology-Based Systematic Representation and Analysis of Traditional Chinese Drugs against Rheumatism. BMC Syst. Biol., 11.","DOI":"10.1186\/s12918-017-0510-5"},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"D672","DOI":"10.1093\/nar\/gkad1025","article-title":"The Reactome Pathway Knowledgebase 2024","volume":"52","author":"Milacic","year":"2024","journal-title":"Nucleic Acids Res."},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"30531","DOI":"10.1038\/srep30531","article-title":"Evolutionary Prediction of Medicinal Properties in the Genus Euphorbia L","volume":"6","author":"Ernst","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"e15701638364199","DOI":"10.2174\/0115701638364199250123062248","article-title":"Recent Development, Applications, and Patents of Artificial Intelligence in Drug Design and Development","volume":"22","author":"Kumar","year":"2025","journal-title":"Curr. Drug Discov. Technol."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"100095","DOI":"10.1016\/j.pharmr.2025.100095","article-title":"Computational Drug Design in the Artificial Intelligence Era: A Systematic Review of Molecular Representations, Generative Architectures, and Performance Assessment","volume":"78","author":"Abbasi","year":"2026","journal-title":"Pharmacol. Rev."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.cell.2020.02.058","article-title":"Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein","volume":"181","author":"Walls","year":"2020","journal-title":"Cell"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"101282","DOI":"10.1016\/j.lanmic.2025.101282","article-title":"Health Security at Genomic Artificial Intelligence-Antimicrobial Resistance Frontiers in Low-Income Countries","volume":"7","author":"Aruhomukama","year":"2026","journal-title":"Lancet Microbe"},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1021\/cb100294v","article-title":"Identification of Direct Protein Targets of Small Molecules","volume":"6","author":"Lomenick","year":"2011","journal-title":"ACS Chem. Biol."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.chembiol.2012.01.002","article-title":"Mass Spectrometry-Based Proteomics in Preclinical Drug Discovery","volume":"19","author":"Schirle","year":"2012","journal-title":"Chem. Biol."},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"D1383","DOI":"10.1093\/nar\/gkae904","article-title":"ECBD: European chemical biology database","volume":"53","author":"Popr","year":"2025","journal-title":"Nucleic Acids Res."},{"key":"ref_113","unstructured":"(2026, March 16). China Achieves Breakthrough in AI-Driven Drug Discovery. Tibet Online, 22 August 2025, Available online: https:\/\/wxb.xzdw.gov.cn\/wlcb\/wsznl\/202508\/t20250822_598548.html."},{"key":"ref_114","unstructured":"(2026, March 02). AI-Native Pharmaceuticals: A Conversation with Core Scientists of Chai-2. Available online: https:\/\/reportify.ai\/tags\/concept?tagValue=AI-native%20%E5%88%B6%E8%8D%AF."}],"container-title":["Life"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-1729\/16\/4\/540\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T14:44:44Z","timestamp":1774622684000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-1729\/16\/4\/540"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,25]]},"references-count":114,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2026,4]]}},"alternative-id":["life16040540"],"URL":"https:\/\/doi.org\/10.3390\/life16040540","relation":{},"ISSN":["2075-1729"],"issn-type":[{"value":"2075-1729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,25]]}}}