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。

IF 13.1 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Guangshun Wang,Cindy Schmidt,Xia Li,Zhe Wang
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引用次数: 0

摘要

全球抗生素耐药性问题是推动宿主防御抗菌肽(amp)发展成为新一代抗生素的动力。为了促进这一发展,我们报告了抗菌肽数据库版本6 (APD6),其中包括(i)整合的数据库平台,(ii)最全面的AMP信息管道(AMPIP),以及(iii)扩展的功能轮。截至2025年3月18日,APD6平台保存了5188个肽的记录,其中包括3306个天然肽,1380个合成肽和239个预测肽,并对每组进行了系统的分类方案。基于改进的数据集,我们提出了关于天然amp的最新观点和发现。天然amp为肽设计和预测潜在amp提供了基础数据集。虽然目前人工智能对抗菌肽的预测仅限于活性和溶血,但APD6提供了新的阳性和阴性数据集(如pH、盐、血清效应和耐药性),用于构建先进的人工智能预测模型,以识别更强效的抗生素。AMPIP涵盖了从肽发现,体外/体内活性和毒性数据到临床试验的信息。此外,APD6(可在https://aps.unmc.edu上获得)包含一个扩展的肽功能轮(例如抗癌和抗糖尿病),允许开发抗生素领域以外的肽疗法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
Nucleic Acids Research
Nucleic Acids Research 生物-生化与分子生物学
CiteScore
27.10
自引率
4.70%
发文量
1057
审稿时长
2 months
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.
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