Comment on 'Protein isoelectric point as a predictor for increased crystallization screening efficiency'

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Comment on 'Protein isoelectric point as a predictor for increased crystallization screening efficiency'

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 crystalliza...

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Using isoelectric point to determine the pH for initial protein crystallization trials

MOTIVATION The identification of suitable conditions for crystallization is a rate-limiting step in protein structure determination. The pH of an experiment is an important parameter and has the potential to be used in data-mining studies to help reduce the number of crystallization trials required. However, the pH is usually recorded as that of the buffer solution, which can be highly inaccura...

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PIP-DB: the Protein Isoelectric Point database

UNLABELLED A protein's isoelectric point or pI corresponds to the solution pH at which its net surface charge is zero. Since the early days of solution biochemistry, the pI has been recorded and reported, and thus literature reports of pI abound. The Protein Isoelectric Point database (PIP-DB) has collected and collated these data to provide an increasingly comprehensive database for comparison...

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Heterogeneity of hemolytic efficiency and isoelectric point of streptolysin O.

Using thin-layer agarose gel isoelectric focusing overlaid with thin-layer erythrocyte agar plates, we found that crude streptolysin O (SLO) consisted of a variety of hemolytic components with different isoelectric points (pIs) and that the distribution of pIs in crude SLO was different even in samples which were produced from a single strain of Streptococcus pyogenes under similar conditions. ...

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High -density lipoprotein cholesterol as a predictor for diabetes mellitus

Background: Diabetes is a prevalent chronic disease around the world. To evaluate risk of diabetes comprehensively, we developed a score model for the risk prediction with HDL-C as a protective factor. Methods: We extracted physical examination data of 2728 individuals. The data contain 18 demographic and clinical variables. To identify the statistical significant feature variables, the backwa...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2004

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/bth452