2026-10-10T12:20:21Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33781118 2026-09-15T09:12:28Z category_1 category_4 category_19 category_21 category_873 category_734 category_64 category_132 category_134 portal_63 item_type_3 month_year_09_2026

An AI-Driven Chemogenomics Knowledgebase for Human-Transmissible Pathogens: A Platform for Antimicrobial Drug Discovery Jiaxiong Kang (24919799) Lei Zhu (16642) Haibo Li (629817) Xiangyu Xie (16521023) Cong Liu (66219) Zhiwei Feng (117939) Yi Wang (32470) Ouyang Mo (24919802) Chengsu Wang (24919805) Xinzi Li (24919808) Ying Xue (12144) Haibin Liu (403499) Qin Ouyang (1328301) Biophysics Biochemistry Pharmacology Biotechnology Chemical Sciences not elsewhere classified Biological Sciences not elsewhere classified Cancer Infectious Diseases Virology vero e6 cells scale virtual screening large language model http :// cgai four approved drugs computational prediction performance driven chemogenomics knowledgebase antimicrobial drug discovery findings establish hpm potential target protein ckb enables large target identification chemogenomic knowledgebase drug repurposing two anti transmissible pathogens specific resource proteomic data novel scaffolds largest domain lab validations interactive queries integrating bio including 13 global biosecurity experimentally validated critical threat consolidating chemical chemical information bioactive molecules affinity assays 287 associated 267 microorganisms 2 replication 2 nucleoprotein Emerging infectious diseases (EIDs) pose a critical threat to global biosecurity. Integrating bio/chemical information and artificial intelligence would bring new strategies for antimicrobial drug discovery. Herein, the Human Pathogenic Microorganisms Chemogenomics Knowledgebase (HPM-CKB) is presented as the largest domain-specific resource, consolidating chemical, genetic, and proteomic data on human-transmissible pathogens, together with multiple computational functional modules. The current release covers 7876 pathogenic proteins from 267 microorganisms (including 13,914 protein 3D structures) and 234,287 associated with bioactive molecules. HPM-CKB enables large-scale virtual screening, target identification, and drug repurposing, and integrates a large language model (LLM) for interactive queries. The computational prediction performance of HPM-CKB is corroborated by known inhibitors targeting SARS-CoV-2 replicase polyprotein 1ab. In wet-lab validations, four approved drugs (cefixime, ceftazidime, saquinavir, and rilapladib) identified via virtual screening show binding activity to SARS-CoV-2 nucleoprotein in affinity assays and inhibit SARS-CoV-2 replication in Vero E6 cells, demonstrating HPM-CKB’s potential in drug repurposing. Meanwhile, two anti-Staphylococcus aureus lead compounds with novel scaffolds (CYC-HXL-9124 and CYC-HXL-9126) are identified via deep learning, and the potential target protein, cell division protein FtsZ, is subsequently prioritized using HPM-CKB (http://cgai.asia/g/pathogenDB) and experimentally validated by affinity assays. Collectively, these findings establish HPM-CKB as both a chemogenomic knowledgebase and a systematic drug development platform against EIDs. 2026-09-15T00:00:00Z Dataset Dataset 10.1021/acs.jcim.6c02102.s006 https://figshare.com/articles/dataset/An_AI-Driven_Chemogenomics_Knowledgebase_for_Human-Transmissible_Pathogens_A_Platform_for_Antimicrobial_Drug_Discovery/33781118 CC BY-NC 4.0