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      antiSMASH 6.0: improving cluster detection and comparison capabilities

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          Abstract

          Many microorganisms produce natural products that form the basis of antimicrobials, antivirals, and other drugs. Genome mining is routinely used to complement screening-based workflows to discover novel natural products. Since 2011, the "antibiotics and secondary metabolite analysis shell—antiSMASH" ( https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free-to-use web server and as a standalone tool under an OSI-approved open-source license. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in bacteria and fungi. Here, we present the updated version 6 of antiSMASH. antiSMASH 6 increases the number of supported cluster types from 58 to 71, displays the modular structure of multi-modular BGCs, adds a new BGC comparison algorithm, allows for the integration of results from other prediction tools, and more effectively detects tailoring enzymes in RiPP clusters.

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          Graphical Abstract

          Here, we present version 6 of the secondary/specialized metabolite genome mining platform antiSMASH with improved detection capabilities, a new cluster compare feature and many further improvements.

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          Most cited references41

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          Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

          S Altschul (1997)
          The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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            Fast and sensitive protein alignment using DIAMOND.

            The alignment of sequencing reads against a protein reference database is a major computational bottleneck in metagenomics and data-intensive evolutionary projects. Although recent tools offer improved performance over the gold standard BLASTX, they exhibit only a modest speedup or low sensitivity. We introduce DIAMOND, an open-source algorithm based on double indexing that is 20,000 times faster than BLASTX on short reads and has a similar degree of sensitivity.
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              Pfam: The protein families database in 2021

              Abstract The Pfam database is a widely used resource for classifying protein sequences into families and domains. Since Pfam was last described in this journal, over 350 new families have been added in Pfam 33.1 and numerous improvements have been made to existing entries. To facilitate research on COVID-19, we have revised the Pfam entries that cover the SARS-CoV-2 proteome, and built new entries for regions that were not covered by Pfam. We have reintroduced Pfam-B which provides an automatically generated supplement to Pfam and contains 136 730 novel clusters of sequences that are not yet matched by a Pfam family. The new Pfam-B is based on a clustering by the MMseqs2 software. We have compared all of the regions in the RepeatsDB to those in Pfam and have started to use the results to build and refine Pfam repeat families. Pfam is freely available for browsing and download at http://pfam.xfam.org/.
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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                02 July 2021
                12 May 2021
                12 May 2021
                : 49
                : W1
                : W29-W35
                Affiliations
                The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark , Kgs. Lyngby, Denmark
                The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark , Kgs. Lyngby, Denmark
                Institute of Biology, Leiden University , Leiden, The Netherlands
                Bioinformatics, Lodo Therapeutics , New York, USA
                Institute of Biology, Leiden University , Leiden, The Netherlands
                Netherlands Institute of Ecology (NIOO-KNAW) , Wageningen, The Netherlands
                Institute of Biology, Leiden University , Leiden, The Netherlands
                Bioinformatics Group, Wageningen University , Wageningen, The Netherlands
                The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark , Kgs. Lyngby, Denmark
                Author notes
                To whom correspondence should be addressed. Tel: +45 24 89 61 32; Email: tiwe@ 123456biosustain.dtu.dk
                Correspondence may also be addressed to Marnix. H. Medema. Email: marnix.medema@ 123456wur.nl
                Correspondence may also be addressed to Kai Blin. Email: kblin@ 123456biossutain.dtu.dk
                Author information
                https://orcid.org/0000-0003-3764-6051
                https://orcid.org/0000-0001-8816-4680
                https://orcid.org/0000-0003-0341-1561
                https://orcid.org/0000-0002-2191-2821
                https://orcid.org/0000-0002-8260-5120
                Article
                gkab335
                10.1093/nar/gkab335
                8262755
                33978755
                4bf730e3-fd82-4062-aad4-9cd1f5bd05c9
                © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 April 2021
                : 12 April 2021
                : 22 February 2021
                Page count
                Pages: 7
                Funding
                Funded by: Novo Nordisk Foundation, DOI 10.13039/501100009708;
                Award ID: NNF20CC0035580
                Award ID: NNF16OC0021746
                Funded by: Danish National Research Foundation, DOI 10.13039/501100001732;
                Award ID: DNRF137
                Funded by: ERC, DOI 10.13039/100010663;
                Award ID: 948770-DECIPHER
                Funded by: Netherlands Organization for Scientific Research;
                Award ID: 731.014.206
                Categories
                AcademicSubjects/SCI00010
                Web Server Issue

                Genetics
                Genetics

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