sGAL: a computational method for finding surface exposed sites in proteins suitable for Cys-mediated cross-linking
G Andrew Woolley1, En-shiun Lee, Fuzhong Zhang
1Department of Chemistry, University of Toronto 80 St. George Street, Toronto, ON M5S 3H6, Canada. awoolley@chem.utoronto.ca
Bioinformatics (Oxford, England)
|October 19, 2006
Summary
sGAL is a software tool that identifies suitable protein sites for chemical cross-linking. It predicts residue pairs within a desired cross-linker length, avoiding steric hindrance for accurate experimental design.
Area of Science:
- Computational biology
- Structural biology
- Biochemistry
Background:
- Chemical cross-linking is a valuable technique for studying protein structure and interactions.
- Identifying suitable cross-linking sites computationally can streamline experimental design.
Purpose of the Study:
- To develop a computational tool, sGAL, for predicting suitable protein sites for chemical cross-linking.
- To facilitate the selection of residue pairs for cross-linking experiments based on proximity and accessibility.
Main Methods:
- sGAL processes protein structure files (PDB format).
- It simulates cysteine (Cys) mutations by truncating residues to their gamma atoms.
- Calculates exposed surface area and residue-pair separations for user-defined cross-linker lengths.
- Filters pairs based on steric interference by analyzing atom contacts along the cross-linker path.
Main Results:
- sGAL identifies residue pairs with gamma atom separations within the specified range.
- The program effectively filters out pairs likely to experience steric hindrance.
- Provides a list of potential cross-linking sites for experimental validation.
Conclusions:
- sGAL is an effective computational tool for predicting protein cross-linking sites.
- The software aids in selecting optimal residue pairs, reducing experimental trial and error.
- Enhances the efficiency of structural biology studies utilizing chemical cross-linking.
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