Recent development of computational resources for new antibiotics discovery.

Understanding a complex working mechanism of biosynthetic gene clusters (BGCs) encoding secondary metabolites is a key to discovery of new antibiotics. Computational resources continue to be developed in order to better process increasing volumes of genome and chemistry data, and thereby better understand BGCs. In this context, this review highlights recent advances in computational resources for secondary metabolites with emphasis on genome mining, compound identification and dereplication as well as databases. We also introduce an updated version of Secondary Metabolite Bioinformatics Portal (SMBP; http://www.secondarymetabolites.org), which we previously released as a curated gateway to all the computational tools and databases useful for discovery and engineering of secondary metabolites.

[1]  Tilmann Weber,et al.  The secondary metabolite bioinformatics portal: Computational tools to facilitate synthetic biology of secondary metabolite production , 2016, Synthetic and systems biotechnology.

[2]  Michael A. Skinnider,et al.  Genomic charting of ribosomally synthesized natural product chemical space facilitates targeted mining , 2016, Proceedings of the National Academy of Sciences.

[3]  George Papadatos,et al.  The ChEMBL database in 2017 , 2016, Nucleic Acids Res..

[4]  Oliver Kohlbacher,et al.  SANDPUMA: ensemble predictions of nonribosomal peptide chemistry reveal biosynthetic diversity across Actinobacteria , 2017, Bioinform..

[5]  Valérie Leclère,et al.  Norine, the knowledgebase dedicated to non-ribosomal peptides, is now open to crowdsourcing , 2015, Nucleic Acids Res..

[6]  Kai Blin,et al.  Improved Lanthipeptide Detection and Prediction for antiSMASH , 2014, PloS one.

[7]  Neetika Nath,et al.  CASSIS and SMIPS: promoter-based prediction of secondary metabolite gene clusters in eukaryotic genomes , 2015, Bioinform..

[8]  Tilmann Weber,et al.  The evolution of genome mining in microbes - a review. , 2016, Natural product reports.

[9]  Chad W. Johnston,et al.  Polyketide and nonribosomal peptide retro-biosynthesis and global gene cluster matching. , 2016, Nature chemical biology.

[10]  Christopher J. Schwalen,et al.  A new genome-mining tool redefines the lasso peptide biosynthetic landscape , 2016, Nature chemical biology.

[11]  Roger G. Linington,et al.  Insights into Secondary Metabolism from a Global Analysis of Prokaryotic Biosynthetic Gene Clusters , 2014, Cell.

[12]  Tilmann Weber,et al.  Metabolic engineering with systems biology tools to optimize production of prokaryotic secondary metabolites. , 2016, Natural product reports.

[13]  Michael A. Skinnider,et al.  Genomes to natural products PRediction Informatics for Secondary Metabolomes (PRISM) , 2015, Nucleic acids research.

[14]  Stefan Günther,et al.  StreptomeDB 2.0—an extended resource of natural products produced by streptomycetes , 2015, Nucleic Acids Res..

[15]  Editorial: ChemSpider--a tool for Natural Products research. , 2015, Natural product reports.

[16]  Kai Blin,et al.  plantiSMASH: automated identification, annotation and expression analysis of plant biosynthetic gene clusters , 2016, bioRxiv.

[17]  Kai Blin,et al.  antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers , 2013, Nucleic Acids Res..

[18]  Michael A. Skinnider,et al.  PRISM 3: expanded prediction of natural product chemical structures from microbial genomes , 2017, Nucleic Acids Res..

[19]  Priya Gupta,et al.  SBSPKSv2: structure-based sequence analysis of polyketide synthases and non-ribosomal peptide synthetases , 2017, Nucleic Acids Res..

[20]  Debasisa Mohanty,et al.  RiPPMiner: a bioinformatics resource for deciphering chemical structures of RiPPs based on prediction of cleavage and cross-links , 2017, Nucleic Acids Res..

[21]  Yoshiyuki Sakaki,et al.  Genome sequence of an industrial microorganism Streptomyces avermitilis: Deducing the ability of producing secondary metabolites , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[22]  F. Barona-Gómez,et al.  Phylogenomic Analysis of Natural Products Biosynthetic Gene Clusters Allows Discovery of Arseno-Organic Metabolites in Model Streptomycetes , 2016, bioRxiv.

[23]  Victor M. Markowitz,et al.  IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites , 2015, mBio.

[24]  Kai Blin,et al.  antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences , 2011, Nucleic Acids Res..

[25]  Tilmann Weber,et al.  Bioinformatics Tools for the Discovery of New Nonribosomal Peptides. , 2016, Methods in molecular biology.

[26]  Susana P. Gaudêncio,et al.  Dereplication: racing to speed up the natural products discovery process. , 2015, Natural product reports.

[27]  S. Lee,et al.  Metabolic engineering of antibiotic factories: new tools for antibiotic production in actinomycetes. , 2015, Trends in biotechnology.

[28]  Michael A Fischbach,et al.  Computational approaches to natural product discovery. , 2015, Nature chemical biology.

[29]  Chad W. Johnston,et al.  Exploration of Nonribosomal Peptide Families with an Automated Informatic Search Algorithm. , 2015, Chemistry & biology.

[30]  Faiza Hanif Waghu,et al.  CAMPR3: a database on sequences, structures and signatures of antimicrobial peptides , 2015, Nucleic Acids Res..

[31]  Kristian Fog Nielsen,et al.  Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking , 2016, Nature Biotechnology.

[32]  Carla S. Jones,et al.  Minimum Information about a Biosynthetic Gene cluster. , 2015, Nature chemical biology.

[33]  Neha Garg,et al.  Dereplication of peptidic natural products through database search of mass spectra , 2016, Nature chemical biology.

[34]  Renzo Kottmann,et al.  The antiSMASH database, a comprehensive database of microbial secondary metabolite biosynthetic gene clusters , 2016, Nucleic Acids Res..

[35]  Christoph Steinbeck,et al.  ChEBI in 2016: Improved services and an expanding collection of metabolites , 2015, Nucleic Acids Res..

[36]  B. Barrell,et al.  Complete genome sequence of the model actinomycete Streptomyces coelicolor A3(2) , 2002, Nature.

[37]  Kai Blin,et al.  antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters , 2015, Nucleic Acids Res..

[38]  A. Aharoni,et al.  The PhytoClust tool for metabolic gene clusters discovery in plant genomes , 2016, bioRxiv.

[39]  Xia Li,et al.  APD3: the antimicrobial peptide database as a tool for research and education , 2015, Nucleic Acids Res..

[40]  Michael A. Skinnider,et al.  An automated Genomes-to-Natural Products platform (GNP) for the discovery of modular natural products , 2015, Nature Communications.

[41]  Kai Blin,et al.  antiSMASH 4.0—improvements in chemistry prediction and gene cluster boundary identification , 2017, Nucleic Acids Res..

[42]  Stefan Günther,et al.  SeMPI: a genome-based secondary metabolite prediction and identification web server , 2017, Nucleic Acids Res..

[43]  Kai Blin,et al.  CRISPy-web: An online resource to design sgRNAs for CRISPR applications , 2016, Synthetic and systems biotechnology.

[44]  Kai Blin,et al.  The Antibiotic Resistant Target Seeker (ARTS), an exploration engine for antibiotic cluster prioritization and novel drug target discovery , 2017, Nucleic Acids Res..

[45]  I-Min A. Chen,et al.  IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes , 2016, Nucleic Acids Res..

[46]  Y. Dufresne,et al.  Norine: A powerful resource for novel nonribosomal peptide discovery , 2015, Synthetic and systems biotechnology.

[47]  Tilmann Weber,et al.  In silico tools for the analysis of antibiotic biosynthetic pathways. , 2014, International journal of medical microbiology : IJMM.

[48]  Yoshiyuki Sakaki,et al.  Complete genome sequence and comparative analysis of the industrial microorganism Streptomyces avermitilis , 2003, Nature Biotechnology.

[49]  Chad W. Johnston,et al.  Dereplicating nonribosomal peptides using an informatic search algorithm for natural products (iSNAP) discovery , 2012, Proceedings of the National Academy of Sciences.