title: ThioFinder: a web-based tool for the identification of thiopeptide gene clusters in DNA sequences.
abstract: Thiopeptides are a growing class of sulfur-rich, highly modified heterocyclic peptides that are mainly active against Gram-positive bacteria including various drug-resistant pathogens. Recent studies also reveal that many thiopeptides inhibit the proliferation of human cancer cells, further expanding their application potentials for clinical use. Thiopeptide biosynthesis shares a common paradigm, featuring a ribosomally synthesized precursor peptide and conserved posttranslational modifications, to afford a characteristic core system, but differs in tailoring to furnish individual members. Identification of new thiopeptide gene clusters, by taking advantage of increasing information of DNA sequences from bacteria, may facilitate new thiopeptide discovery and enrichment of the unique biosynthetic elements to produce novel drug leads by applying the principle of combinatorial biosynthesis. In this study, we have developed a web-based tool ThioFinder to rapidly identify thiopeptide biosynthetic gene cluster from DNA sequence using a profile Hidden Markov Model approach. Fifty-four new putative thiopeptide biosynthetic gene clusters were found in the sequenced bacterial genomes of previously unknown producing microorganisms. ThioFinder is fully supported by an open-access database ThioBase, which contains the sufficient information of the 99 known thiopeptides regarding the chemical structure, biological activity, producing organism, and biosynthetic gene (cluster) along with the associated genome if available. The ThioFinder website offers researchers a unique resource and great flexibility for sequence analysis of thiopeptide biosynthetic gene clusters. ThioFinder is freely available at http://db-mml.sjtu.edu.cn/ThioFinder/.
authors.affiliation: State Key Laboratory of Microbial Metabolism, Shanghai Jiaotong University, Shanghai, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Li
authors.forename: Xudong
authors.initials: X
authors.lastname: Qu
authors.forename: Xinyi
authors.initials: X
authors.lastname: He
authors.forename: Lian
authors.initials: L
authors.lastname: Duan
authors.forename: Guojun
authors.initials: G
authors.lastname: Wu
authors.forename: Dexi
authors.initials: D
authors.lastname: Bi
authors.forename: Zixin
authors.initials: Z
authors.lastname: Deng
authors.forename: Wen
authors.initials: W
authors.lastname: Liu
authors.forename: Hong-Yu
authors.initials: HY
authors.lastname: Ou
mesh_terms: D001430:Bacteriocins / Q000235:genetics*; D030541:Databases, Genetic; D055808:Drug Discovery; D005798:Genes, Bacterial; D008390:Markov Chains; D005810:Multigene Family; D010456:Peptides, Cyclic / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods; D012984:Software
chemical_list: D001430:Bacteriocins; D010456:Peptides, Cyclic