{"title":"APD6:扩展抗菌肽数据库,通过部署前所未有的信息管道来促进研究和开发。","authors":"Guangshun Wang,Cindy Schmidt,Xia Li,Zhe Wang","doi":"10.1093/nar/gkaf860","DOIUrl":null,"url":null,"abstract":"The global antibiotic resistance issue constitutes a driving force for developing host defense antimicrobial peptides (AMPs) into a new generation of antibiotics. To facilitate this development, we report the antimicrobial peptide database version 6 (APD6) with (i) the consolidated database platform, (ii) the most comprehensive AMP information pipeline (AMPIP), and (iii) the expanded wheel of function. As of 18 March 2025, the APD6 platform housed records for 5188 peptides, including 3306 natural, 1380 synthetic, and 239 predicted AMPs with systematic classification schemes for each group. Based on the refined dataset, we present an updated view and findings on natural AMPs. Natural AMPs provide a fundamental dataset for peptide design and predicting potential AMPs. While current artificial intelligence prediction of AMPs is limited to activity and hemolysis, the APD6 provides new positive and negative datasets (e.g. pH, salt, serum effects, and resistance) for building advanced AI prediction models to identify more robust antibiotics. The AMPIP covers information ranging from peptide discovery, in vitro/in vivo activity and toxicity data, to clinical trials. In addition, the APD6 (available at https://aps.unmc.edu) contains an expanded wheel of peptide functions (e.g. anticancer and antidiabetic), allowing for developing peptide therapeutics outside the antibiotic arena.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"24 1","pages":""},"PeriodicalIF":13.1000,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"APD6: the antimicrobial peptide database is expanded to promote research and development by deploying an unprecedented information pipeline.\",\"authors\":\"Guangshun Wang,Cindy Schmidt,Xia Li,Zhe Wang\",\"doi\":\"10.1093/nar/gkaf860\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The global antibiotic resistance issue constitutes a driving force for developing host defense antimicrobial peptides (AMPs) into a new generation of antibiotics. To facilitate this development, we report the antimicrobial peptide database version 6 (APD6) with (i) the consolidated database platform, (ii) the most comprehensive AMP information pipeline (AMPIP), and (iii) the expanded wheel of function. As of 18 March 2025, the APD6 platform housed records for 5188 peptides, including 3306 natural, 1380 synthetic, and 239 predicted AMPs with systematic classification schemes for each group. Based on the refined dataset, we present an updated view and findings on natural AMPs. Natural AMPs provide a fundamental dataset for peptide design and predicting potential AMPs. While current artificial intelligence prediction of AMPs is limited to activity and hemolysis, the APD6 provides new positive and negative datasets (e.g. pH, salt, serum effects, and resistance) for building advanced AI prediction models to identify more robust antibiotics. The AMPIP covers information ranging from peptide discovery, in vitro/in vivo activity and toxicity data, to clinical trials. In addition, the APD6 (available at https://aps.unmc.edu) contains an expanded wheel of peptide functions (e.g. anticancer and antidiabetic), allowing for developing peptide therapeutics outside the antibiotic arena.\",\"PeriodicalId\":19471,\"journal\":{\"name\":\"Nucleic Acids Research\",\"volume\":\"24 1\",\"pages\":\"\"},\"PeriodicalIF\":13.1000,\"publicationDate\":\"2025-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nucleic Acids Research\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/nar/gkaf860\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nucleic Acids Research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/nar/gkaf860","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
APD6: the antimicrobial peptide database is expanded to promote research and development by deploying an unprecedented information pipeline.
The global antibiotic resistance issue constitutes a driving force for developing host defense antimicrobial peptides (AMPs) into a new generation of antibiotics. To facilitate this development, we report the antimicrobial peptide database version 6 (APD6) with (i) the consolidated database platform, (ii) the most comprehensive AMP information pipeline (AMPIP), and (iii) the expanded wheel of function. As of 18 March 2025, the APD6 platform housed records for 5188 peptides, including 3306 natural, 1380 synthetic, and 239 predicted AMPs with systematic classification schemes for each group. Based on the refined dataset, we present an updated view and findings on natural AMPs. Natural AMPs provide a fundamental dataset for peptide design and predicting potential AMPs. While current artificial intelligence prediction of AMPs is limited to activity and hemolysis, the APD6 provides new positive and negative datasets (e.g. pH, salt, serum effects, and resistance) for building advanced AI prediction models to identify more robust antibiotics. The AMPIP covers information ranging from peptide discovery, in vitro/in vivo activity and toxicity data, to clinical trials. In addition, the APD6 (available at https://aps.unmc.edu) contains an expanded wheel of peptide functions (e.g. anticancer and antidiabetic), allowing for developing peptide therapeutics outside the antibiotic arena.
期刊介绍:
Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.