Since UDock2 is also designed for educational and popularization of science purposes, we improved the gamification of the molecular docking sequence by providing a more playful experience. We introduce an extended navigation allowing to ease the exploration of molecular complexes by orienting the camera relatively to the molecular surface and user inputs. We provide the ability to study complex molecular systems, especially through the support of multi-body molecular docking thanks to an adapted energy computation scheme. To offer up-to-date features, a complete rewrite has been achieved which comes with several user experience improvements thanks to recent computer graphics strategies. The main UDock features were retained to be integrated into a research workflow with the following extended features: It therefore relies on standard CPU computing strategies and do not use any feature set restricted to modern GPUs. In order to broaden its potential audience, UDock2 is designed to be used on low-end computers. 2014), an intuitive and interactive multi-body protein–protein docking method oriented toward its ease of usability. ![]() In this article, we describe UDock2, the new version of UDock ( Levieux et al. 2020) for the popularization of such methods, combining performance, user-oriented features, and comprehensive feedback for interactive manipulation is still a complicated task. Even though several works presented alternative approaches ( Lu et al. Different interactive docking methods have been released over time that notably suffers from limited usability and/or dependency on proprietary or expensive hardware ( Daunay et al. ![]() The manipulation and visualization of molecular bodies through an ergonomic and intuitive user interface in docking software still represent a challenge. By providing insight into the spatial arrangement of proteins and their binding sites, protein–protein docking simulations offer a valuable tool for understanding the mechanisms underlying complex biological processes. Such simulations have been shown to be effective in ranking the predicted geometries based on their binding energy, calculated using a molecular mechanics force-field ( Meng et al. To explore the geometry of these interactions, researchers have utilized protein–protein docking simulations, which aim to predict the relative position of the involved proteins. ![]() The critical involvement of protein–protein interactions in essential biological processes, including immunity and inflammation, has been well-established ( Braun and Gingras 2012).
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