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DispHScan: A Multi-Sequence Web Tool for Predicting Protein Disorder as a Function of pH.

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Disordered proteins undergo pH-dependent conformational changes. A new tool, DispHScan, predicts these transitions in large protein datasets, aiding research into protein function and disease.

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bioinformaticsconditional disorderpHprotein structuresequence analysis

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Structural Biology

Background:

  • Proteins face environmental fluctuations impacting their structure and function.
  • Intrinsically disordered proteins (IDPs) are particularly sensitive to pH-induced conformational changes.
  • Previous methods limited proteome-wide analysis of pH-dependent transitions.

Purpose of the Study:

  • To develop a computational tool for predicting pH-induced disorder-order transitions in proteins.
  • To enable large-scale analysis of context-dependent conformational changes in protein sequences.
  • To facilitate the screening of protein mutants for pH-sensitivity.

Main Methods:

  • Development of DispHScan, a computational tool for pH-dependent disorder prediction.
  • Exploitation of charge-hydrophobicity diagrams to model pH effects on protein conformation.
  • Implementation of a web server for user-friendly analysis of multiple protein sequences.

Main Results:

  • DispHScan accurately predicts pH-induced disorder-order transitions in large protein datasets.
  • The tool identifies context-dependent conformational switches influenced by solution pH.
  • Enables proteome-wide analysis and mutant screening for pH-modulated protein behavior.

Conclusions:

  • DispHScan is the first tool for predicting pH-induced disorder-order transitions in large protein datasets.
  • This tool offers new insights into the role of conditional disorder in physiology and pathology.
  • The freely available web server supports academic research without registration.