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Subcellular pH and predicted pH‐dependent features of proteins
Author(s) -
Chan Pedro,
Lovrić Josip,
Warwicker Jim
Publication year - 2006
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200500534
Subject(s) - isoelectric point , golgi apparatus , organelle , pi , stability (learning theory) , proteomics , subcellular localization , chemistry , biochemistry , biology , cytoplasm , endoplasmic reticulum , enzyme , computer science , machine learning , gene
A characteristic of two‐dimensional proteomics gels is a general bimodal distribution of isoelectric (p I ) values. Discussion of this feature has focussed on the balance of acidic and basic ionisable residues, and potential relationships between p I distributions and organism classification or protein subcellular location. Electrostatics calculations on a set of protein structures with known subcellular location show that predicted folded state p I are similar to those calculated from sequence alone, but adjusted according to a general stabilising effect from interactions between ionisable groups. Bimodal distributions dominate both p I and the predicted pH of maximal stability. However, there are significant differences between these features. The average pH of maximal stability generally follows organelle pH. Average p I values are well removed from organelle pH in most subcellular environments, consistent with the view that proteins have evolved to carry (on average) net charge in a given subcellular location, and relevant to discussion of solubility in crowded environments. Correlation of the predicted pH of maximum stability with subcellular pH suggests an evolutionary pressure to adjust folded state interactions according to environment. Finally, our analysis of ionisable group contributions to stability suggests that Golgi proteins have the largest such term, although this dataset is small.

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