3DVizSNP: a tool for rapidly visualizing missense mutations identified in high throughput experiments in iCn3D.
BMC Bioinformatics
; 24(1): 244, 2023 Jun 09.
Article
em En
| MEDLINE
| ID: mdl-37296383
ABSTRACT
BACKGROUND:
High throughput experiments in cancer and other areas of genomic research identify large numbers of sequence variants that need to be evaluated for phenotypic impact. While many tools exist to score the likely impact of single nucleotide polymorphisms (SNPs) based on sequence alone, the three-dimensional structural environment is essential for understanding the biological impact of a nonsynonymous mutation.RESULTS:
We present a program, 3DVizSNP, that enables the rapid visualization of nonsynonymous missense mutations extracted from a variant caller format file using the web-based iCn3D visualization platform. The program, written in Python, leverages REST APIs and can be run locally without installing any other software or databases, or from a webserver hosted by the National Cancer Institute. It automatically selects the appropriate experimental structure from the Protein Data Bank, if available, or the predicted structure from the AlphaFold database, enabling users to rapidly screen SNPs based on their local structural environment. 3DVizSNP leverages iCn3D annotations and its structural analysis functions to assess changes in structural contacts associated with mutations.CONCLUSIONS:
This tool enables researchers to efficiently make use of 3D structural information to prioritize mutations for further computational and experimental impact assessment. The program is available as a webserver at https//analysistools.cancer.gov/3dvizsnp or as a standalone python program at https//github.com/CBIIT-CGBB/3DVizSNP .Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Biologia Computacional
/
Mutação de Sentido Incorreto
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
BMC Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Estados Unidos