Nerpa: A Tool for Discovering Biosynthetic Gene Clusters of Bacterial Nonribosomal Peptides

Abstract

Microbial natural products are a major source of bioactive compounds for drug discovery. Among these molecules, nonribosomal peptides (NRPs) represent a diverse class of natural products that include antibiotics, immunosuppressants, and anticancer agents. Recent breakthroughs in natural product discovery have revealed the chemical structure of several thousand NRPs. However, biosynthetic gene clusters (BGCs) encoding them are known only for a few hundred compounds. Here, we developed Nerpa, a computational method for the high-throughput discovery of novel BGCs responsible for producing known NRPs. After searching 13,399 representative bacterial genomes from the RefSeq repository against 8368 known NRPs, Nerpa linked 117 BGCs to their products. We further experimentally validated the predicted BGC of ngercheumicin from Photobacterium galatheae via mass spectrometry. Nerpa supports searching new genomes against thousands of known NRP structures, and novel molecular structures against tens of thousands of bacterial genomes. The availability of these tools can enhance our understanding of NRP synthesis and the function of their biosynthetic enzymes.

BioCAT: Search for biosynthetic gene clusters producing nonribosomal peptides with known structure

“…Although GARLIC had a higher specificity, in general, NRP to BGC matching quality obtained on the BioCAT results turned out to be higher than the GARLIC quality. The Nerpa tool [18] recently published and based on the same external software has shown similar general matching quality and as well as BioCAT overperformed GARLIC. However, it should be noted here that BioCAT was designed to be more sensitive than specific, unlike Nerpa which has shown high matching specificity but moderate sensitivity.…”

“…Additionally, the method was compared with the Nerpa tool published recently [18] . The same dataset of 984 genome/BGC pairs was analyzed with Nerpa.…”

“…In addition, we showed the applicability of BioCAT on several external data, including complete genomes as well as draft ones. Finally, we compared the BioCAT pipeline with the GARLIC tool [6] and Nerpa [18] which have a similar functionality.…”

Carbon-nitrogen bond formation to construct novel polyketide-indole hybrids from the indole-3-carbinol exposed culture of Daldinia eschscholzii

“…Natural products are the major source of lead compounds for drug development and represent the majority of small-molecule drugs that were already on the market [ 25 , 26 ]. However, due to the repeated discovery of known compounds, the hit rate of new skeletal compounds come down every year since the study of streptomyces metabolites reached its summit in the 1970s [ 27 ].…”

NPOmix: a machine learning classifier to connect mass spectrometry fragmentation data to biosynthetic gene clusters

“…Recently, some approaches and tools have been created to connect specialized metabolites (known and cryptic MS/MS spectra) to their biosynthetic gene clusters, such as Pattern-based Genome Mining (7, 8), MetaMiner (9), DeepRiPP (10), NRPquest (11), NRPminer (12), GNP (13) and NPLinker (14), recently reviewed by Van der Hooft et al ., 2020 (15). Nerpa (16) and GARLIC (17) can connect structures to BGCs; structures are normally represented in the SMILES (Simplified Molecular-Input Line-Entry System) format, a type of computer-readable annotation language for chemical structures. However, most of these tools are neither high throughput, nor efficient, or can only be used for a particular class of BGC (e.g., peptides or BGCs homologous to known BGCs).…”