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. 2007 Jul;35(Web Server issue):W465-72.
doi: 10.1093/nar/gkm353. Epub 2007 Jun 6.

iPDA: integrated protein disorder analyzer

Affiliations

iPDA: integrated protein disorder analyzer

Chung-Tsai Su et al. Nucleic Acids Res. 2007 Jul.

Abstract

This article presents a web server iPDA, which aims at identifying the disordered regions of a query protein. Automatic prediction of disordered regions from protein sequences is an important problem in the study of structural biology. The proposed classifier DisPSSMP2 is different from several existing disorder predictors by its employment of position-specific scoring matrices with respect to physicochemical properties (PSSMP), where the physicochemical properties adopted here especially take the disorder propensity of amino acids into account. The web server iPDA integrates DisPSSMP2 with several other sequence predictors in order to investigate the functional role of the detected disordered region. The predicted information includes sequence conservation, secondary structure, sequence complexity and hydrophobic clusters. According to the proportion of the secondary structure elements predicted, iPDA dynamically adjusts the cutting threshold of determining protein disorder. Furthermore, a pattern mining package for detecting sequence conservation is embedded in iPDA for discovering potential binding regions of the query protein, which is really helpful to uncovering the relationship between protein function and its primary sequence. The web service is available at http://biominer.bime.ntu.edu.tw/ipda and mirrored at http://biominer.cse.yzu.edu.tw/ipda.

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Figures

Figure 1.
Figure 1.
iPDA employs seven sequence analyzers and provides utilities for discovering sequence motifs and extracting missing residues in PDB structures.
Figure 2.
Figure 2.
The system flow of the proposed two-stage classifier DisPSSMP2. In both stages, an efficient package for constructing RBFN, named QuickRBF (16), is employed to build the classifier.
Figure 3.
Figure 3.
(A) The result page of iPDA on protein GCN4_YEAST (P03069). (B) One pattern derived by WildSpan identifies nine important residues for DNA binding (PDB structure used: 1YSA).
Figure 4.
Figure 4.
(A) The result of P10408 (SECA_ECOLI). (B) The 10 residues predicted by both WildSpan and DisPSSMP2 are plotted as red sticks on the structure of a homologous protein, SECA_BACSU (P28366). Other 12 WildSpan predicted residues that either provides inter-molecular interactions to ADP or intra-molecular interactions with each other and/or the previous 10 residues are plotted as yellow sticks. Distances smaller than 5 Å are shown in blue dotted lines (PDB structure used: 1M74).
Figure 5.
Figure 5.
(A) The partial result of iPDA on protein P53_HUMAN (P04637). (B) The partial conservation plot of ClustalW and WildSpan, after invoking the second run of pattern mining on the first predicted disordered region. (C) The discovered conserved segment ‘FxxLW’ contains three important residues for MDM2 binding, where chain B is a short polypeptide of p53 and chain A is the protein MDM2 (PDB structure used: 1YCQ).

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