Visual exploration of large normal mode spaces to study protein flexibility. (August 2020)

• Record Type: Journal Article
• Authors: Bedoucha, Pierre; Reuter, Nathalie; Hauser, Helwig; Byška, Jan
• Is Part Of: Computers & graphics. Volume 90(2020)
• Page Start: 73
• Page End: 83
• Publication Date: 2020-08
• Subjects: Normal mode analysis -- Protein flexibility -- Molecular visualization -- Coordinated and multiple views; Computer graphics -- Periodicals; 006.6
• DOI: 10.1016/j.cag.2020.05.025
• Languages: English
• ISSNs: 0097-8493

Abstract

Highlights: Assessment of the tasks for an effective and efficient visual analysis of proteins using normal mode calculation. The design of a new interactive tool for the exploratory analysis of a large number of normal modes and their combinations, based on these tasks. The design of a visualization-based sorting approach, guiding the user to potentially important normal modes or their combinations, easing the exploration of the vast normal modes space. The possibility of performing the analysis only from a single protein conformation. Graphical abstract: Abstract: When studying the function of proteins, biochemists utilize normal mode decomposition to enable the analysis of structural changes on time scales that are too long for molecular dynamics simulation. Such a decomposition yields a high-dimensional parameter space that is too large to be analyzed exhaustively. We present a novel approach to reducing and exploring this vast space through the means of interactive visualization. Our approach enables the inference of relevant protein function from single structure dynamics through protein tunnel analysis while considering normal mode combinations spanning the whole normal modes space. Our solution, based on multiple linked 2D and 3D views, enables the quick and flexible exploration of individual modes and their effect on the dynamics of tunnels with relevance for the protein function. Once an interesting motion is identified, the exploration of possible normal mode combinations is steered via a visualization-based recommendation system. This helps to quickly identify a narrow, yet relevant set of normal modes that can be investigated in detail. Our solution is the result of close cooperation between visualization and the domain. The versatility and efficiency of our approach are demonstrated in several case studies.