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3DVizSNP: a tool for rapidly visualizing missense mutations identified in high throughput experiments in iCn3D
Michael Sierk1, Shashikala Ratnayake2, Manoj M Wagle3,4,5
1Computational Genomics and Bioinformatics Branch, Center for Biomedical Informatics and Information Technology, National Cancer Institute, NIH, Rockville, MD, 20852, USA. michael.sierk@nih.gov.
BMC Bioinformatics
|June 9, 2023
Summary
3DVizSNP visualizes nonsynonymous mutations using 3D structures, aiding researchers in prioritizing genetic variants for cancer research. This tool enhances the assessment of mutation impact by integrating structural data, improving variant interpretation.
Area of Science:
- Genomic research
- Bioinformatics
- Structural biology
Background:
- Genomic research generates numerous sequence variants requiring phenotypic impact assessment.
- Existing tools primarily analyze single nucleotide polymorphisms (SNPs) based on sequence alone.
- Understanding the 3D structural context is crucial for evaluating nonsynonymous mutation effects.
Purpose of the Study:
- To present 3DVizSNP, a program for rapid visualization of nonsynonymous missense mutations.
- To enable the assessment of mutation impact using 3D structural information.
- To facilitate the prioritization of mutations for further analysis.
Main Methods:
- 3DVizSNP utilizes the web-based iCn3D visualization platform.
- The program leverages Python, REST APIs, and can be run locally or via a webserver.
- It automatically retrieves experimental or predicted protein structures (AlphaFold) for variant context.
Main Results:
- 3DVizSNP enables rapid screening of SNPs based on their local structural environment.
- The tool visualizes mutations and assesses changes in structural contacts.
- It integrates with iCn3D for advanced structural analysis.
Conclusions:
- 3DVizSNP empowers researchers to efficiently use 3D structural data for mutation prioritization.
- The tool supports computational and experimental impact assessments.
- Accessible as a webserver and standalone Python program.
Keywords:
Genomic variationMutation prioritizationPhenotype impactProtein structureSingle nucleotide polymorphismsStructural bioinformaticsMore Related Videos
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