Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
Leibniz Institute for Natural Product Research and Infection Biology-Hans-Knöll-Institute, 07745 Jena, Germany.
Nucleic Acids Res. 2017 Jul 3;45(W1):W36-W41. doi: 10.1093/nar/gkx319.
Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding the production of such compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally synthesized and post-translationally modified peptides cluster products, reporting of sequence similarity to proteins encoded in experimentally characterized gene clusters on a per-protein basis and a domain-level alignment tool for comparative analysis of trans-AT polyketide synthase assembly line architectures. Additionally, several usability features have been updated and improved. Together, these improvements make antiSMASH up-to-date with the latest developments in natural product research and will further facilitate computational genome mining for the discovery of novel bioactive molecules.
许多抗生素、化疗药物、作物保护剂和食品防腐剂都源自细菌、真菌或植物产生的分子。近年来,基因组挖掘方法已被广泛用于识别和描述编码这些化合物产生的生物合成基因簇。自 2011 年以来,“抗生素和次级代谢产物分析外壳 - antiSMASH”一直作为一个网络服务器和独立工具,协助研究人员高效地完成这一任务。在这里,我们介绍了经过全面更新的 antiSMASH 版本 4,它增加了几个新功能,包括使用 ClusterFinder 方法或新集成的 CASSIS 算法预测基因簇边界,基于新的 SANDPUMA 算法改进非核糖体肽合成酶腺苷酸化结构域的底物特异性预测,改进萜烯和核糖体合成及翻译后修饰肽簇产物的预测,基于每个蛋白质报告与实验表征基因簇中编码的蛋白质的序列相似性,以及用于比较分析跨 AT 聚酮合酶装配线结构的域级对齐工具。此外,还更新和改进了几个可用性功能。总的来说,这些改进使 antiSMASH 跟上了天然产物研究的最新发展,并将进一步促进计算基因组挖掘,以发现新的生物活性分子。