Leclère Valérie, Weber Tilmann, Jacques Philippe, Pupin Maude
ProBioGEM, Institut Charles Viollette, Polytech'Lille, University of Lille 1, 59650, Villeneuve d'Ascq, France.
CRIStAL, UMR 9189, Univ Lille, 59650, Villeneuve d'Ascq, France.
Methods Mol Biol. 2016;1401:209-32. doi: 10.1007/978-1-4939-3375-4_14.
This chapter helps in the use of bioinformatics tools relevant to the discovery of new nonribosomal peptides (NRPs) produced by microorganisms. The strategy described can be applied to draft or fully assembled genome sequences. It relies on the identification of the synthetase genes and the deciphering of the domain architecture of the nonribosomal peptide synthetases (NRPSs). In the next step, candidate peptides synthesized by these NRPSs are predicted in silico, considering the specificity of incorporated monomers together with their isomery. To assess their novelty, the two-dimensional structure of the peptides can be compared with the structural patterns of all known NRPs. The presented workflow leads to an efficient and rapid screening of genomic data generated by high throughput technologies. The exploration of such sequenced genomes may lead to the discovery of new drugs (i.e., antibiotics against multi-resistant pathogens or anti-tumors).
本章有助于使用与发现微生物产生的新型非核糖体肽(NRP)相关的生物信息学工具。所描述的策略可应用于草图基因组序列或完全组装的基因组序列。它依赖于合成酶基因的鉴定以及非核糖体肽合成酶(NRPS)结构域结构的解析。在下一步中,考虑到掺入单体的特异性及其异构体,通过计算机预测由这些NRPS合成的候选肽。为了评估它们的新颖性,可以将肽的二维结构与所有已知NRP的结构模式进行比较。所展示的工作流程能够高效、快速地筛选高通量技术生成的基因组数据。对这类测序基因组的探索可能会导致发现新药物(即针对多重耐药病原体的抗生素或抗肿瘤药物)。