Molecular simulations allow researchers to obtain complementary data with respect to experimental studies and to overcome some of their limitations. Current experimental techniques do not allow to observe the full dynamics of a protein at atomic detail. In return, experiments provide the structures, i.e. the spatial atomic positions, for numerous biomolecular systems, which are often used as starting point for simulation studies. In order to predict, to explain and to understand experimental results, researchers have developed a variety of biomolecular representations and algorithms. They allow to simulate the dynamic behavior of macromolecules at different scales, ranging from detailed models using quantum mechanics or classical molecular mechanics to more approximate representations. These simulations are often controlled a priori by complex and empirical settings. Most researchers visualise the result of their simulation once the computation is finished. Such post-simulation analysis often makes use of specific molecular user interfaces, by reading and visualising the molecular 3D configuration at each step of the simulation. This approach makes it difficult to interact with a simulation in progress. When a problem occurs, or when the researcher does not achieve to observe the predicted behavior, the simulation must be restarted with other settings or constraints. This can result in the waste of an important number of compute cycles, as some simulations last for a long time: several days to weeks may be required to reproduce a short timespan, a few nanoseconds, of molecular reality. Moreover, several biomolecular processes, like folding or large conformational changes of proteins, occur on even longer timescales that are inaccessible to current simulation techniques. It can thus be necessary to impose empirical constraints in order to accelerate a simulation and to reproduce

Proteins take on their function in the cell by interacting with other proteins or biomolecular complexes. To study this process, computational methods, collectively named protein docking, are used to predict the position and orientation of a protein ligand when it is bound to a protein receptor or enzyme, taking into account chemical or physical criteria. This process is intensively studied to discover new biological functions for proteins and to better understand how these macromolecules take on these functions at the molecular scale. Pharmaceutical research also employs docking techniques for a variety of purposes, most notably in the virtual screening of large databases of available chemicals to select likely molecular candidates for drug design. The basic hypothesis of our work is that Virtual Reality (VR) and multimodal interaction can increase efficiency in reaching and analysing docking solutions, in addition to fully a computational docking approach. To this end, we conducted an ergonomic analysis of the protein–protein current docking task as it is carried out today. Using these results, we designed an immersive and multimodal application where VR devices, such as the three-dimensional mouse and haptic devices, are used to interactively manipulate two proteins to explore possible docking solutions. During this exploration, visual, audio, and haptic feedbacks are combined to render and evaluate chemical or physical properties of the current docking configuration.

Le docking de protéines in-silico est la détermination de la structure 3d des complexes protéiques à l'échelle atomique, qui permet de mieux comprendre la fonction biologique de ces complexes.Dans le cadre du projet ANR CoRSAIRe, notre hypothèse est que les interactions multimodales en Réalité Virtuelle (RV) sont susceptibles d'améliorer la rapidité de ces dockings. A cet effet, nous avons conduit une analyse ergonomique afin d'identifier les besoins des biologistes sur les systèmes de docking actuels. Puis nous avons conçu un modèle et une application immersive et multimodale dans laquelle les rendus visuel, audio et haptique sont combinés pour transmettre les informations nécessaires à ce type d'activité.ABSTRACT.Protein docking studies how proteins combine with each other in 3d, in order to better understand their biological functions.The basic hypothesis of the french research projet CoR-SAIRe is that Virtual Reality (VR) multimodal interactions can increase efficiency in reaching docking solutions.To this end, we have conducted an ergonomic analysis of the protein-protein current docking task.Using these results, we have designed an immersive and multimodal application where visual, audio and haptic feedbacks are combined to communicate biological information, help manipulating proteins and exploring possible solutions of assembly.