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Characterization of surface binding sites in glycoside hydrolases: A computational study
Samaneh Samaei-Daryan1, Bahram Goliaei1, Azadeh Ebrahim-Habibi2,3
1Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Journal of Molecular Recognition : JMR
|March 16, 2017
Summary
This study computationally analyzed carbohydrate surface binding sites (SBSs) in enzymes. Findings reveal SBSs are hydrophilic, with binding modes influenced by site structure and ligand size, impacting interactions.
Area of Science:
- Biochemistry
- Structural Biology
- Computational Chemistry
Background:
- Carbohydrate surface binding sites (SBSs) are crucial for enzyme function.
- Understanding SBSs' structural and physicochemical properties is key to enzyme mechanism elucidation.
Purpose of the Study:
- To computationally investigate the structural and physicochemical properties of enzyme SBSs.
- To classify SBSs based on shape and analyze ligand binding modes.
- To correlate SBS structural features with physicochemical properties and interaction types.
Main Methods:
- Collected 85 SBSs from 44 enzymes across 119 Protein Data Bank (PDB) files.
- Classified SBSs into flat surfaces (A), clefts (B), and cavities (C) based on shape.
- Performed molecular docking to refine classification and analyze ligand binding.
- Calculated physicochemical properties using YASARA Structure.
Main Results:
- SBSs are predominantly hydrophilic, with charge varying based on ligand size and cutoff.
- Type B SBSs (clefts) exhibited the highest average solvent-accessible surface area.
- Hydrophobic interactions were more prevalent than hydrogen bonds, linked to aromatic residues and carbohydrate interactions.
- Ligand binding modes were dependent on the structural type of the SBS.
Conclusions:
- Enzyme SBSs exhibit diverse structural and physicochemical properties influencing ligand binding.
- The classification based on shape provides insights into ligand positioning and interaction preferences.
- Computational approaches, including molecular docking, are valuable for characterizing enzyme-ligand interactions.
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