Visuelle Analyse von Protein-Ligand Interaktionen

• Antragsteller: Professor Dr. Michael Krone; Professor Dr. Timo Ropinski
• Fachliche Zuordnung: Strukturbiologie ; Bild- und Sprachverarbeitung, Computergraphik und Visualisierung, Human Computer Interaction, Ubiquitous und Wearable Computing
• Förderung: Förderung von 2018 bis 2022
• Projektkennung: Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 391088465

• Erstellungsjahr: 2023

Zusammenfassung der Projektergebnisse

We were able to make significant contributions to the fields of visualization and learning related to protein structures and their interactions with ligands and other small molecules. While our original project proposal was focusing solely on visualization, machine learning has emerged as an important area of research also in this domain during the project duration. Hence, we decided to include this emerging field into our research. The results we obtained within the project have lead to 19 peer-reviewed articles, which have been published at toplevel venues in the fields of machine learning and visualization (e.g., ICRL, TVCG, CGF). Most of these publications have been co-authored by national and international project partners, some of which have collaborated with us on the methodical developments, while others were application domain scientists who provided valuable input and feedback, and helped us to evaluate our newly developed methods. The methods we developed within the project allow domain experts to investigate protein-ligand interactions and other aspects related to protein function in more detail, more efficiently, and with higher accuracy compared to previous methods. The combination of basic research for the development of novel algorithms and techniques and application-oriented research to support domain experts in their analysis tasks with newly developed visual analysis applications, which we pursued throughout the project, was a driving factor for our success. The international nature of the project enabled us, despite some setbacks resulting from the COVID pandemic, to further tighten the connections between the three partner institutions (UUlm, UTue, MasarykU). Our collaborations on project-relevant research topics and the regular discussions among the project partners led to a mutual benefit and enrichment with respect to the overall results beyond the joint publications, as it also influenced and shaped the individual achievements of the groups. It has also led to joint efforts beyond the topic of the project.

Projektbezogene Publikationen (Auswahl)

• A General Illumination Model for Molecular Visualization. Computer Graphics Forum, 37(3), 367-378.
  Hermosilla, P.; Vázquez, P.; Vinacua, A. & Ropinski, T.
  
• Improving perception of molecular surface visualizations by incorporating translucency effects. In: EG Workshop on Visual Computing for Biology and Medicine. 2018, pp. 185–195
  Hermosilla Casajús, P., Maisch, S., Vázquez Alcocer, P. P., Ropinski, T.
  
• A Massively Parallel CUDA Algorithm to Compute and Visualize the Solvent Excluded Surface for Dynamic Molecular Data. In: Workshop on Molecular Graphics and Visual Analysis of Molecular Data. EG, 2019, pp. 1–9
  Schäfer, M., Krone, M.
  
• A User Interaction Design for Object Manipulation via Eye Tracking in Virtual Reality. In: IEEE VR 2019 Workshop on Novel Input Devices and Interaction Techniques (NIDIT). 2019
  Groß, A., Becher, M., Reina, G., Ertl, T., Krone, M.
  
• Hybrid Visualization of Protein-Lipid and Protein-Protein Interaction. In: EG Workshop on Visual Computing for Biology and Medicine. 2019, pp. 213–223
  Alharbi, N., Krone, M., Chavent, M., Laramee, R. S.
  
• Interactive CPU-based Ray Tracing of Solvent Excluded Surfaces. In: EG Workshop on Visual Computing for Biology and Medicine. 2019, pp. 239–251
  Rau, T., Zahn, S., Krone, M., Reina, G., Ertl, T.
  
• LoD PLI: Level of Detail for Visualizing Time-Dependent, Protein-Lipid Interaction. In: 10th International Conference on Information Visualization Theory and Applications. 2019
  Alharbi, N., Krone, M., Chavent, M., Laramee, R. S.
  
• Molecular Graphics: Bridging Structural Biologists and Computer Scientists. Structure, 27(11), 1617-1623.
  Martinez, Xavier; Krone, Michael; Alharbi, Naif; Rose, Alexander S.; Laramee, Robert S.; O'Donoghue, Sean; Baaden, Marc & Chavent, Matthieu
  
• Molecular Sombreros: Abstract Visualization of Binding Sites within Proteins. In: EG Workshop on Visual Computing for Biology and Medicine. 2019, pp. 225–237
  Schatz, K., Krone, M., Bauer, T., Ferrario, V., Pleiss, J., Ertl, T.
  
• QuickSES: A Library for Fast Computation of Solvent Excluded Surfaces. In: Workshop on Molecular Graphics and Visual Analysis of Molecular Data. 2019, pp. 11–15
  Martinez, X., Krone, M., Baaden, M.
  
• Visualization of Large Molecular Trajectories. IEEE Transactions on Visualization and Computer Graphics, 25(1), 987-996.
  Duran, David; Hermosilla, Pedro; Ropinski, Timo; Kozlikova, Barbora; Vinacua, Alvar & Vazquez, Pere-Pau
  
• A perceptually optimised bivariate visualisation scheme for high-dimensional fold-change data. Advances in Data Analysis and Classification, 15(2), 463-480.
  Müller, André; Lausser, Ludwig; Wilhelm, Adalbert; Ropinski, Timo; Platzer, Matthias; Neumann, Heiko & Kestler, Hans A.
  
• Analyzing Protein Similarity by Clustering Molecular Surface Maps. In VCBM (pp. 103-114).
  Schatz, K.; Frieß, F.; Schäfer, M.; Ertl, T. & Krone, M.
  
• Intrinsic-extrinsic convolution and pooling for learning on 3d protein structures
  Hermosilla, P., Schäfer, M., Lang, M., Fackelmann, G., Vázquez, P. P., Kozlíková, B., Krone, M., Ritschel, T., Ropinski, T.
  
• Real-Time Visualization of 3D Amyloid-Beta Fibrils from 2D Cryo-EM Density Maps. In: VCBM. 2020, pp. 115–125
  Kniesel, H., Ropinski, T., Hermosilla, P.
  
• The moving target of visualization software for an increasingly complex world. Computers & Graphics, 87, 12-29.
  Reina, Guido; Childs, Hank; Matković, Krešimir; Bühler, Katja; Waldner, Manuela; Pugmire, David; Kozlíková, Barbora; Ropinski, Timo; Ljung, Patric; Itoh, Takayuki; Gröller, Eduard & Krone, Michael
  
• Analyzing the similarity of protein domains by clustering Molecular Surface Maps. Computers & Graphics, 99 (2021, 10), 114-127.
  Schatz, Karsten; Frieß, Florian; Schäfer, Marco; Buchholz, Patrick C.F.; Pleiss, Jürgen; Ertl, Thomas & Krone, Michael
  
• Visual Analysis of Large‐Scale Protein‐Ligand Interaction Data. Computer Graphics Forum, 40(6), 394-408.
  Schatz, Karsten; Franco‐Moreno, Juan José; Schäfer, Marco; Rose, Alexander S.; Ferrario, Valerio; Pleiss, Jürgen; Vázquez, Pere‐Pau; Ertl, Thomas & Krone, Michael
  
• Contrastive representation learning for 3d protein structures
  Hermosilla, P., Ropinski, T.
  
• Learning Human Viewpoint Preferences from Sparsely Annotated Models. Computer Graphics Forum, 41(6), 453-466.
  Hartwig, S.; Schelling, M.; Onzenoodt, C. v.; Vázquez, P.‐P.; Hermosilla, P. & Ropinski, T.