Literature DB >> 16522794

Computer-aided NMR assay for detecting natively folded structural domains.

Takayuki Hondoh1, Atsushi Kato, Shigeyuki Yokoyama, Yutaka Kuroda.   

Abstract

Structural genomics projects require strategies for rapidly recognizing protein sequences appropriate for routine structure determination. For large proteins, this strategy includes the dissection of proteins into structural domains that form stable native structures. However, protein dissection essentially remains an empirical and often a tedious process. Here, we describe a simple strategy for rapidly identifying structural domains and assessing their structures. This approach combines the computational prediction of sequence regions corresponding to putative domains with an experimental assessment of their structures and stabilities by NMR and biochemical methods. We tested this approach with nine putative domains predicted from a set of 108 Thermus thermophilus HB8 sequences using PASS, a domain prediction program we previously reported. To facilitate the experimental assessment of the domain structures, we developed a generic 6-hour His-tag-based purification protocol, which enables the sample quality evaluation of a putative structural domain in a single day. As a result, we observed that half of the predicted structural domains were indeed natively folded, as judged by their HSQC spectra. Furthermore, two of the natively folded domains were novel, without related sequences classified in the Pfam and SMART databases, which is a significant result with regard to the ability of structural genomics projects to uniformly cover the protein fold space.

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Year:  2006        PMID: 16522794      PMCID: PMC2242495          DOI: 10.1110/ps.051880406

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  42 in total

Review 1.  Target selection for structural genomics.

Authors:  S E Brenner
Journal:  Nat Struct Biol       Date:  2000-11

Review 2.  Structural proteomics: prospects for high throughput sample preparation.

Authors:  D Christendat; A Yee; A Dharamsi; Y Kluger; M Gerstein; C H Arrowsmith; A M Edwards
Journal:  Prog Biophys Mol Biol       Date:  2000       Impact factor: 3.667

3.  A quantitative, high-throughput screen for protein stability.

Authors:  S Ghaemmaghami; M C Fitzgerald; T G Oas
Journal:  Proc Natl Acad Sci U S A       Date:  2000-07-18       Impact factor: 11.205

4.  Cellular quality control screening to identify amino acid pairs for substituting the disulfide bonds in immunoglobulin fold domains.

Authors:  Yoshihisa Hagihara; Tomoki Matsuda; Noboru Yumoto
Journal:  J Biol Chem       Date:  2005-05-03       Impact factor: 5.157

5.  Improvement of domain linker prediction by incorporating loop-length-dependent characteristics.

Authors:  Takanori Tanaka; Shigeyuki Yokoyama; Yutaka Kuroda
Journal:  Biopolymers       Date:  2006       Impact factor: 2.505

6.  Effect of experimental conditions on the analysis of sodium dodecyl sulphate polyacrylamide gel electrophoresis separated proteins by matrix-assisted laser desorption/ ionisation mass spectrometry.

Authors:  M Galvani; E Bordini; C Piubelli; M Hamdan
Journal:  Rapid Commun Mass Spectrom       Date:  2000       Impact factor: 2.419

7.  Structural genomics projects in Japan.

Authors:  S Yokoyama; H Hirota; T Kigawa; T Yabuki; M Shirouzu; T Terada; Y Ito; Y Matsuo; Y Kuroda; Y Nishimura; Y Kyogoku; K Miki; R Masui; S Kuramitsu
Journal:  Nat Struct Biol       Date:  2000-11

8.  Rapid evaluation and optimization of recombinant protein production using GFP tagging.

Authors:  E Rücker; G Schneider; K Steinhäuser; R Löwer; J Hauber; R H Stauber
Journal:  Protein Expr Purif       Date:  2001-02       Impact factor: 1.650

9.  From genes to proteins: high-throughput expression and purification of the human proteome.

Authors:  J S Albala; K Franke; I R McConnell; K L Pak; P A Folta; B Rubinfeld; A H Davies; G G Lennon; R Clark
Journal:  J Cell Biochem       Date:  2000-10-20       Impact factor: 4.429

10.  A computationally directed screen identifying interacting coiled coils from Saccharomyces cerevisiae.

Authors:  J R Newman; E Wolf; P S Kim
Journal:  Proc Natl Acad Sci U S A       Date:  2000-11-21       Impact factor: 11.205

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  13 in total

1.  Exploring subdomain cooperativity in T4 lysozyme I: structural and energetic studies of a circular permutant and protein fragment.

Authors:  Jason Cellitti; Manuel Llinas; Nathaniel Echols; Elizabeth A Shank; Blake Gillespie; Ester Kwon; Scott M Crowder; Frederick W Dahlquist; Tom Alber; Susan Marqusee
Journal:  Protein Sci       Date:  2007-03-30       Impact factor: 6.725

Review 2.  The impact of extremophiles on structural genomics (and vice versa).

Authors:  Francis E Jenney; Michael W W Adams
Journal:  Extremophiles       Date:  2007-06-13       Impact factor: 2.395

3.  IS-Dom: a dataset of independent structural domains automatically delineated from protein structures.

Authors:  Teppei Ebina; Yuki Umezawa; Yutaka Kuroda
Journal:  J Comput Aided Mol Des       Date:  2013-05-29       Impact factor: 3.686

4.  Fast H-DROP: A thirty times accelerated version of H-DROP for interactive SVM-based prediction of helical domain linkers.

Authors:  Tambi Richa; Soichiro Ide; Ryosuke Suzuki; Teppei Ebina; Yutaka Kuroda
Journal:  J Comput Aided Mol Des       Date:  2016-12-27       Impact factor: 3.686

5.  H-DROP: an SVM based helical domain linker predictor trained with features optimized by combining random forest and stepwise selection.

Authors:  Teppei Ebina; Ryosuke Suzuki; Ryotaro Tsuji; Yutaka Kuroda
Journal:  J Comput Aided Mol Des       Date:  2014-06-26       Impact factor: 3.686

6.  ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly.

Authors:  Yan Wang; Jian Wang; Ruiming Li; Qiang Shi; Zhidong Xue; Yang Zhang
Journal:  Nucleic Acids Res       Date:  2017-07-03       Impact factor: 16.971

7.  Multi-head attention-based U-Nets for predicting protein domain boundaries using 1D sequence features and 2D distance maps.

Authors:  Sajid Mahmud; Zhiye Guo; Farhan Quadir; Jian Liu; Jianlin Cheng
Journal:  BMC Bioinformatics       Date:  2022-07-19       Impact factor: 3.307

8.  Mathematical model for empirically optimizing large scale production of soluble protein domains.

Authors:  Eisuke Chikayama; Atsushi Kurotani; Takanori Tanaka; Takashi Yabuki; Satoshi Miyazaki; Shigeyuki Yokoyama; Yutaka Kuroda
Journal:  BMC Bioinformatics       Date:  2010-03-01       Impact factor: 3.169

9.  DoBo: Protein domain boundary prediction by integrating evolutionary signals and machine learning.

Authors:  Jesse Eickholt; Xin Deng; Jianlin Cheng
Journal:  BMC Bioinformatics       Date:  2011-02-01       Impact factor: 3.169

10.  Propeptide-mediated inhibition of cognate gingipain proteinases.

Authors:  N Laila Huq; Christine A Seers; Elena C Y Toh; Stuart G Dashper; Nada Slakeski; Lianyi Zhang; Brent R Ward; Vincent Meuric; Dina Chen; Keith J Cross; Eric C Reynolds
Journal:  PLoS One       Date:  2013-06-10       Impact factor: 3.240

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