Visualization of large molecular trajectories

The analysis of protein-ligand interactions is a time-intensive task. Researchers have to analyze multiple physico-chemical properties of the protein at once and combine them to derive conclusions about the protein-ligand interplay. Typically, several charts are inspected, and 3D animations can be p...

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Detalles Bibliográficos
Autores: Duran Rosich, David, Hermosilla Casajús, Pedro, Ropinski, Timo, Kozliková, Barbora, Vinacua Pla, Álvaro|||0000-0001-8984-4311, Vázquez Alcocer, Pere Pau|||0000-0003-4638-4065
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/123129
Acceso en línea:https://hdl.handle.net/2117/123129
https://dx.doi.org/10.1109/TVCG.2018.2864851
Access Level:acceso abierto
Palabra clave:Molecular structure -- Data processing
Information visualization
Three dimensional imaging
Molecular visualization
Simulation inspection
Long trajectories
Estructura molecular -- Informàtica
Visualització de la informació
Infografia tridimensional
Àrees temàtiques de la UPC::Informàtica::Infografia
Descripción
Sumario:The analysis of protein-ligand interactions is a time-intensive task. Researchers have to analyze multiple physico-chemical properties of the protein at once and combine them to derive conclusions about the protein-ligand interplay. Typically, several charts are inspected, and 3D animations can be played side-by-side to obtain a deeper understanding of the data. With the advances in simulation techniques, larger and larger datasets are available, with up to hundreds of thousands of steps. Unfortunately, such large trajectories are very difficult to investigate with traditional approaches. Therefore, the need for special tools that facilitate inspection of these large trajectories becomes substantial. In this paper, we present a novel system for visual exploration of very large trajectories in an interactive and user-friendly way. Several visualization motifs are automatically derived from the data to give the user the information about interactions between protein and ligand. Our system offers specialized widgets to ease and accelerate data inspection and navigation to interesting parts of the simulation. The system is suitable also for simulations where multiple ligands are involved. We have tested the usefulness of our tool on a set of datasets obtained from protein engineers, and we describe the expert feedback.