Literature DB >> 14871873

Protein isoelectric point as a predictor for increased crystallization screening efficiency.

Katherine A Kantardjieff1, Bernhard Rupp.   

Abstract

MOTIVATION: Increased efficiency in initial crystallization screening reduces cost and material requirements in structural genomics. Because pH is one of the few consistently reported parameters in the Protein Data Bank (PDB), the isoelectric point (pI) of a protein has been explored as a useful indirect predictor for the optimal choice of range and distribution of the pH sampling in crystallization trials.
RESULTS: We have analyzed 9596 unique protein crystal forms from the August 2003 PDB and have found a significant relationship between the calculated pI of successfully crystallized proteins and the difference between pI and reported pH at which they were crystallized. These preferences provide strong prior information for the design of crystallization screening experiments with significantly increased efficiency and corresponding reduction in material requirements, leading to potential cost savings of millions of US$ for structural genomics projects involving high-throughput crystallographic structure determination. AVAILABILITY: A prototype example of a screen design and efficiency estimator program, CrysPred, is available at http://www-structure.llnl.gov/cryspred/

Mesh:

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Year:  2004        PMID: 14871873     DOI: 10.1093/bioinformatics/bth066

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  36 in total

1.  Crystallization of nepenthesin I using a low-pH crystallization screen.

Authors:  Karla Fejfarová; Alan Kádek; Hynek Mrázek; Jiří Hausner; Vyacheslav Tretyachenko; Tomáš Koval'; Petr Man; Jindřich Hašek; Jan Dohnálek
Journal:  Acta Crystallogr F Struct Biol Commun       Date:  2016-01-01       Impact factor: 1.056

2.  Formulation screening by differential scanning fluorimetry: how often does it work?

Authors:  Marko Ristic; Nicholas Rosa; Shane A Seabrook; Janet Newman
Journal:  Acta Crystallogr F Struct Biol Commun       Date:  2015-09-23       Impact factor: 1.056

3.  A strategy for selecting the pH of protein solutions to enhance crystallization.

Authors:  Chen Yan Zhang; Zi Qing Wu; Da Chuan Yin; Bo Ru Zhou; Yun Zhu Guo; Hui Meng Lu; Ren Bin Zhou; Peng Shang
Journal:  Acta Crystallogr Sect F Struct Biol Cryst Commun       Date:  2013-06-29

4.  Carboxylic acids in crystallization of macromolecules: learning from successful crystallization experiments.

Authors:  Lesa R Offermann; John Z He; Nicholas J Mank; William T Booth; Maksymilian Chruszcz
Journal:  J Struct Funct Genomics       Date:  2014-01-23

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Authors:  Haruki Hasegawa; John Wendling; Feng He; Egor Trilisky; Riki Stevenson; Heather Franey; Francis Kinderman; Gary Li; Deirdre Murphy Piedmonte; Timothy Osslund; Min Shen; Randal R Ketchem
Journal:  J Biol Chem       Date:  2011-04-04       Impact factor: 5.157

Review 6.  Optimization of crystallization conditions for biological macromolecules.

Authors:  Alexander McPherson; Bob Cudney
Journal:  Acta Crystallogr F Struct Biol Commun       Date:  2014-10-31       Impact factor: 1.056

Review 7.  Introduction to protein crystallization.

Authors:  Alexander McPherson; Jose A Gavira
Journal:  Acta Crystallogr F Struct Biol Commun       Date:  2013-12-24       Impact factor: 1.056

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Authors:  Essam Kotb
Journal:  World J Microbiol Biotechnol       Date:  2014-03-08       Impact factor: 3.312

9.  Isolation of a putative virulence agent, cytotoxic serine-elastase, from a newly isolated Pseudomonas aeruginosa ZuhP13.

Authors:  Essam Kotb; Yehia A El-Zawahry; Ghadeer E Saleh
Journal:  J Biosci       Date:  2019-03       Impact factor: 1.826

10.  Flanking signal and mature peptide residues influence signal peptide cleavage.

Authors:  Khar Heng Choo; Shoba Ranganathan
Journal:  BMC Bioinformatics       Date:  2008-12-12       Impact factor: 3.169

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