{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Jenkinson CB"],"funding":["National Institute of Allergy and Infectious Diseases","NIAID NIH HHS"],"pagination":["kuad045"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10734572"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["50(1)"],"pubmed_abstract":["Secondary metabolites (SMs) are biologically active small molecules, many of which are medically valuable. Fungal genomes contain vast numbers of SM biosynthetic gene clusters (BGCs) with unknown products, suggesting that huge numbers of valuable SMs remain to be discovered. It is challenging, however, to identify SM BGCs, among the millions present in fungi, that produce useful compounds. One solution is resistance gene-guided genome mining, which takes advantage of the fact that some BGCs contain a gene encoding a resistant version of the protein targeted by the compound produced by the BGC. The bioinformatic signature of such BGCs is that they contain an allele of an essential gene with no SM biosynthetic function, and there is a second allele elsewhere in the genome. We have developed "],"journal":["Journal of industrial microbiology & biotechnology"],"pubmed_title":["Computer-aided, resistance gene-guided genome mining for proteasome and HMG-CoA reductase inhibitors."],"pmcid":["PMC10734572"],"funding_grant_id":["R21 AI156320","R21AI156320"],"pubmed_authors":["Oakley BR","Zhong C","Podgorny AR","Jenkinson CB"],"additional_accession":[]},"is_claimable":false,"name":"Computer-aided, resistance gene-guided genome mining for proteasome and HMG-CoA reductase inhibitors.","description":"Secondary metabolites (SMs) are biologically active small molecules, many of which are medically valuable. Fungal genomes contain vast numbers of SM biosynthetic gene clusters (BGCs) with unknown products, suggesting that huge numbers of valuable SMs remain to be discovered. It is challenging, however, to identify SM BGCs, among the millions present in fungi, that produce useful compounds. One solution is resistance gene-guided genome mining, which takes advantage of the fact that some BGCs contain a gene encoding a resistant version of the protein targeted by the compound produced by the BGC. The bioinformatic signature of such BGCs is that they contain an allele of an essential gene with no SM biosynthetic function, and there is a second allele elsewhere in the genome. We have developed ","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Feb","modification":"2025-04-19T11:36:23.608Z","creation":"2025-02-19T01:46:14.031Z"},"accession":"S-EPMC10734572","cross_references":{"pubmed":["38061800"],"doi":["10.1093/jimb/kuad045"]}}