Mut-Map: Comprehensive Computational Pipeline for Structural Mapping and Analysis of Cancer-Associated Mutations

Area of Science:

• Computational Biology
• Structural Biology
• Genomics

Background:

• Understanding genetic mutations' impact on protein structure is crucial for cancer research and targeted therapies.
• Accurately mapping mutations to protein structures and analyzing their functional effects presents a significant challenge.

Purpose of the Study:

• To introduce Mut-Map, a computational pipeline for integrating cancer mutation data with protein structural information.
• To enable detailed analysis of how mutations affect protein function by examining structural contexts.

Main Methods:

• Mut-Map integrates mutation data (Catalogue Of Somatic Mutations In Cancer) with structural data (Protein Data Bank, AlphaFold).
• The pipeline maps mutations to structures, renumbers residues, assesses disorder, and visualizes effects on functional regions like DNA interfaces and binding sites.

Main Results:

• A case study on the TP53 gene identified frequent mutations at the DNA-binding interface, offering insights into cancer progression.
• The pipeline successfully elucidates the structural implications of cancer-associated mutations.

Conclusions:

• Mut-Map provides a valuable resource for understanding cancer mutation impacts on protein structure and function.
• This approach facilitates the development of targeted therapies and advances knowledge of protein structure-function relationships.