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STRIDER: Steric hindrance and metal coordination identifier
L Ponoop Prasad Patro1, Thenmalarchelvi Rathinavelan1
1Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana State 502285, India.
Computational Biology and Chemistry
|May 5, 2022
Summary
STRIDER is a web tool that identifies steric hindrance and metal coordination in biomolecular structures. It validates modeled structures and aids in understanding molecular interactions for various biological applications.
Area of Science:
- Computational Biology
- Structural Biology
- Biochemistry
Background:
- Biomolecular structural knowledge is crucial for understanding biological processes and diseases.
- In silico modeling is essential for biomacromolecule design, docking, and conformational analysis.
- Experimental techniques like cryo-electron microscopy provide structural insights, requiring validation methods.
Purpose of the Study:
- To introduce STRIDER, a web user interface (WUI) for estimating steric hindrance and metal coordination.
- To provide a tool for validating the accuracy of modeled biomolecular structures.
- To facilitate the analysis of molecular interactions in various computational biology applications.
Main Methods:
- STRIDER utilizes van der Waals radii to calculate pairwise inter- and intra-molecular steric hindrances for 117 elements.
- It identifies and reports coordination patterns for 64 metals interactively.
- The tool generates PyMOL session files for offline visualization of interactions.
Main Results:
- STRIDER accurately estimates steric hindrance and metal coordination in biomolecular structures.
- It provides conformer-wise interaction patterns, addressing sampling issues in flexible docking and protein folding.
- The tool accepts any chemical structure in PDB format via Cartesian coordinates.
Conclusions:
- STRIDER is a valuable tool for biomolecular structure validation and analysis.
- It enhances in silico modeling by providing detailed interaction insights.
- The tool supports diverse applications including virtual screening and understanding disease mechanisms.
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