ProFeatMap: a highly customizable tool for 2D feature representation of protein sets

Area of Science:

• Proteomics and bioinformatics
• Computational biology
• Molecular biology

Background:

• Omics studies generate large protein and gene lists.
• Analyzing these lists globally is challenging due to a lack of visualization tools.
• Understanding protein feature architecture is crucial in biological studies.

Purpose of the Study:

• To present ProFeatMap, a Python-based website for visualizing protein feature architectures.
• To enable simultaneous visualization of features for large sets of proteins.
• To facilitate the exploration and classification of protein families based on shared features.

Main Methods:

• ProFeatMap accepts UniProt accession codes to define protein sets.
• It extracts annotated features (domains, repeats, disorder, PTMs) from databases like UniProt and InterPro.
• Features are visualized on a customizable 2D map, with customizable shapes and colors based on data.

Main Results:

• ProFeatMap generates publication-quality 2D maps displaying protein feature organization.
• The tool allows for sorting protein lists based on homologous feature content.
• It aids in identifying feature redundancy and patterns within large protein families.

Conclusions:

• ProFeatMap provides an intuitive solution for global inspection of protein feature architectures.
• The tool enhances biological insights by revealing previously overlooked feature patterns.
• ProFeatMap is freely available online with accessible source code.