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      A Prevalent Peptide-Binding Domain Guides Ribosomal Natural Product Biosynthesis

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          Abstract

          Ribosomally synthesized and posttranslationally modified peptides (RiPPs) are a rapidly growing natural product class. RiPP precursor peptides can undergo extensive enzymatic tailoring, yielding structurally and functionally diverse products, and their biosynthetic logic makes them attractive bioengineering targets. Recent work suggests that unrelated RiPP modifying enzymes contain structurally similar precursor peptide-binding domains. Using profile hidden Markov model comparisons, we discovered related and previously unrecognized peptide-binding domains in proteins spanning the majority of known prokaryotic RiPP classes; thus, we named this conserved domain the RiPP precursor peptide recognition element (RRE). Through binding studies, we verify the role of the RRE for three distinct RiPP classes: linear azole-containing peptides, thiopeptides, and lasso peptides. Because numerous RiPP biosynthetic enzymes act on peptide substrates, our findings have powerful predictive value as to which protein(s) drive substrate binding, laying a foundation for further characterization of RiPP biosynthetic pathways and the rational engineering of new peptide-binding activities.

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          Most cited references44

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          Protein homology detection by HMM-HMM comparison.

          Protein homology detection and sequence alignment are at the basis of protein structure prediction, function prediction and evolution. We have generalized the alignment of protein sequences with a profile hidden Markov model (HMM) to the case of pairwise alignment of profile HMMs. We present a method for detecting distant homologous relationships between proteins based on this approach. The method (HHsearch) is benchmarked together with BLAST, PSI-BLAST, HMMER and the profile-profile comparison tools PROF_SIM and COMPASS, in an all-against-all comparison of a database of 3691 protein domains from SCOP 1.63 with pairwise sequence identities below 20%.Sensitivity: When the predicted secondary structure is included in the HMMs, HHsearch is able to detect between 2.7 and 4.2 times more homologs than PSI-BLAST or HMMER and between 1.44 and 1.9 times more than COMPASS or PROF_SIM for a rate of false positives of 10%. Approximately half of the improvement over the profile-profile comparison methods is attributable to the use of profile HMMs in place of simple profiles. Alignment quality: Higher sensitivity is mirrored by an increased alignment quality. HHsearch produced 1.2, 1.7 and 3.3 times more good alignments ('balanced' score >0.3) than the next best method (COMPASS), and 1.6, 2.9 and 9.4 times more than PSI-BLAST, at the family, superfamily and fold level, respectively.Speed: HHsearch scans a query of 200 residues against 3691 domains in 33 s on an AMD64 2GHz PC. This is 10 times faster than PROF_SIM and 17 times faster than COMPASS.
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            Is Open Access

            CDD: conserved domains and protein three-dimensional structure

            CDD, the Conserved Domain Database, is part of NCBI’s Entrez query and retrieval system and is also accessible via http://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml. CDD provides annotation of protein sequences with the location of conserved domain footprints and functional sites inferred from these footprints. Pre-computed annotation is available via Entrez, and interactive search services accept single protein or nucleotide queries, as well as batch submissions of protein query sequences, utilizing RPS-BLAST to rapidly identify putative matches. CDD incorporates several protein domain and full-length protein model collections, and maintains an active curation effort that aims at providing fine grained classifications for major and well-characterized protein domain families, as supported by available protein three-dimensional (3D) structure and the published literature. To this date, the majority of protein 3D structures are represented by models tracked by CDD, and CDD curators are characterizing novel families that emerge from protein structure determination efforts.
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              Evaluation of comparative protein modeling by MODELLER.

              We evaluate 3D models of human nucleoside diphosphate kinase, mouse cellular retinoic acid binding protein I, and human eosinophil neurotoxin that were calculated by MODELLER, a program for comparative protein modeling by satisfaction of spatial restraints. The models have good stereochemistry and are at least as similar to the crystallographic structures as the closest template structures. The largest errors occur in the regions that were not aligned correctly or where the template structures are not similar to the correct structure. These regions correspond predominantly to exposed loops, insertions of any length, and non-conserved side chains. When a template structure with more than 40% sequence identity to the target protein is available, the model is likely to have about 90% of the mainchain atoms modeled with an rms deviation from the X-ray structure of approximately 1 A, in large part because the templates are likely to be that similar to the X-ray structure of the target. This rms deviation is comparable to the overall differences between refined NMR and X-ray crystallography structures of the same protein.

                Author and article information

                Journal
                101231976
                32624
                Nat Chem Biol
                Nat. Chem. Biol.
                Nature chemical biology
                1552-4450
                1552-4469
                3 June 2015
                13 July 2015
                August 2015
                01 February 2016
                : 11
                : 8
                : 564-570
                Affiliations
                [1 ]Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
                [2 ]Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
                [3 ]Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
                Author notes
                [* ]Correspondence and requests for materials should be addressed to: D.A.M., douglasm@ 123456illinois.edu , phone: 1-217-333-1345, fax: 1-217-333-0508
                Article
                NIHMS696112
                10.1038/nchembio.1856
                4509860
                26167873
                7a41c680-1e87-4bbd-acbb-69ae834e977e

                Reprints and permissions information is available online at http://www.nature.com/reprints/index.html

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                Biochemistry
                Biochemistry

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