quickARSC: standalone package and web interface for profiling elemental stoichiometry of proteomes.

Area of Science:

• Bioinformatics
• Computational Biology
• Biochemistry

Background:

• Elemental composition analysis is crucial for understanding protein function and evolution.
• Previous methods for calculating elemental composition per amino acid residue side chain (ARSC) were often complex or inaccessible.

Purpose of the Study:

• To introduce quickARSC, a user-friendly command-line tool for computing ARSC from amino acid sequences.
• To provide a web interface for accessing, filtering, visualizing, and downloading pre-computed ARSC data for a large prokaryotic dataset.

Main Methods:

• Development of a command-line tool (quickARSC) for ARSC calculation.
• Creation of a web interface linked to a database of pre-computed N-ARSC, C-ARSC, and S-ARSC values.
• Curated data for 143,614 prokaryotic species.

Main Results:

• quickARSC successfully computes elemental composition per amino acid residue side chain.
• The web interface offers comprehensive data access and analysis functionalities.
• Pre-computed ARSC data for a substantial number of prokaryotic species is now readily available.

Conclusions:

• quickARSC simplifies and standardizes ARSC computation.
• The associated web interface democratizes access to valuable biochemical data for prokaryotic species.
• This resource will aid research in microbial genomics, proteomics, and evolutionary biology.