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Solvent accessibility in native and isolated domain environments: general features and implications to interface
Mohd Firdaus Raih1, Shandar Ahmad, Rong Zheng
1National Institute for Genomics and Molecular Biology (Interim Laboratory), and School of Biosciences and Biotechnology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Malaysia.
Biophysical Chemistry
|March 29, 2005
Summary
Analyzing protein domains reveals that 18% of residues change solvent accessibility when isolated. This finding impacts predicting protein interactions and structures.
Area of Science:
- Structural biology
- Computational biology
- Biochemistry
Background:
- Protein domains are fundamental units of protein structure and function.
- Understanding how protein domains interact is crucial for deciphering biological processes.
- Solvent accessibility changes can indicate domain interfaces and functional roles.
Purpose of the Study:
- To quantify changes in solvent accessibility for protein domains when isolated versus in a native environment.
- To analyze residue propensities and secondary structure contributions to these accessibility changes.
- To assess the predictability of interface residues from sequence data.
Main Methods:
- Utilized a non-redundant database of 4536 protein structural domains (over 790,000 residues).
- Calculated solvent accessibility for residues in native and isolated domain environments.
- Analyzed residue propensities, secondary structure variations, and residue type impacts on surface area changes.
Main Results:
- Nearly 140,000 (18%) residues exhibited altered solvent accessibility between native and isolated states.
- Helix and strand secondary structures showed greater surface area loss than coils.
- Hydrophobic and uncharged residues experienced greater surface area changes than charged residues.
Conclusions:
- Significant changes in solvent accessibility occur when protein domains are isolated.
- Residue propensities and secondary structures influence these accessibility shifts.
- The findings have implications for predicting protein-protein, protein-ligand, and protein-DNA interactions.