Proteins are the base component that make all living organisms function. They are made up of amino acids and are responsible for the structure, function, and regulation of organisms’ tissues and organs. They can exist alone or as part of a multi-unit structure. They interact
with other proteins to form stable or transient complexes. Protein function, such as transporting signals or converting energy, is determined by its structure, therefore being critical that we understand protein complexes at the cellular level. Chemical cross-linking combined with mass spectrometry
is an established method in protein chemistry to explain lowresolution 3D protein structures and interacting sequences in protein complexes. Chemical cross-linking of a protein enables scientists to understand how the protein folds, whereas intermolecular cross-linking between different proteins
enables to determine which components interact and how and where they physically contact each other. Mass spectrometry is used to acquire distance information and distance constraints within a molecule. The challenge is to how to best take advantage of the information provided by these methods
utilizing novel visualization analytics that can help explore much more detailed information on protein structure than traditional biomechanical methods, such as the Edman degradation which sequentially removes one residue at a time and the structures are observed through chromatographic procedures.
data resulting from chemical cross-linking in most cases come in a raw format that makes it hard for the user to absorb the data and get a bigger picture of the existing interactions as well as getting a close insight on smaller reactions. This has motivated the department of Bioinformatics
at the University of Arkansas at Little Rock to develop an algorithm named “X-Linked Peptide Mapping” that allows the analysis of the data and identify interacting peptides (short chains of amino acids) in an easier, more accurate way avoiding the limitations mentioned before.
Since the field of chemical cross-linking mass spectrometry of protein-protein interactions hasn’t been explored visually in a comprehensive way before, the results encouraged us at the Emerging Analytics Center at the University of Arkansas at Little Rock to develop an interactive web
application that allows the user to visualize the results of the analysis including 2D information representations as well as 3D structural modeling representation of the interactions,. This paper presents preliminary research in this area, including the development of a prototype immersive
environment to explore the molecular structures.