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Modeling an Enzyme Active Site using Molecular Visualization Freeware
Published on: December 25, 2021
Recognition of active and inactive catalytic triads: A template based approach
Vikas Gupta1, N A Udaya Prakash, V Lakshmi
1Bioinformatics Centre, (Centre of Excellence in Structural Biology and Bio-computing), Indian Institute of Science, Bangalore 560 012, India.
International Journal of Biological Macromolecules
|January 27, 2010
Summary
Predicting protein function is crucial. This study introduces a method using a catalytic triad (Serine-Histidine-Aspartic acid) template to identify proteolytic proteins within the Protein Data Bank (PDB), focusing on active site geometry and interactions.
Area of Science:
- Biochemistry
- Structural Biology
- Computational Biology
Background:
- Protein sequence and structure databases are vital for determining protein function.
- Identifying the catalytic nature of proteins is essential for understanding biological processes.
Purpose of the Study:
- To develop a method for predicting the proteolytic activity of proteins using a catalytic triad template.
- To differentiate active from inactive proteins based on specific interactions within the catalytic triad.
Main Methods:
- Utilized a geometrically optimized active site template based on the Serine-Histidine-Aspartic acid catalytic triad.
- Analyzed bond angles and hydrogen bond distances within the catalytic triad.
- Assessed solvent accessibility of active sites.
Main Results:
- A specific bond angle range (115-140 degrees) for Serine-Histidine interaction is critical for proteolytic activity.
- Defined hydrogen bond distance ranges for Serine-Histidine and Histidine-Aspartic acid interactions.
- Active proteins typically exhibit solvent accessibility in the range of 10-16 Ų.
Conclusions:
- A geometrically optimized catalytic triad template can accurately predict proteolytic function.
- These findings are applicable to various catalytic triads and aid in protein function prediction.
- The method provides a selective tool for identifying active enzymes from structural data.
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