Since the dawn of the computer age, scientists have designed devices to represent molecular structures and developed tools to simulate their dynamic behavior in silico. To this day, these tools remain central to our understanding of biomolecular phenomena. In contrast to other fields such as fluid mechanics or meteorology, the observation of molecular motions at the atomic level remains a major experimental challenge. Continuous advances in computer graphics and numerical computation, combined with the emergence of humancomputer interaction approaches, led to the methodology of so-called "interactive molecular simulations", characterized by two main features. First, the possibility to visualize a running simulation in interactive time, that is, compatible with human perception. Second, the possibility to manipulate the simulation interactively by imposing a force, changing a biophysical property, or editing runtime parameters on the fly. Such simulations are still little used in computational biology, where it is more common to run a series of offline simulations and then visualize and analyze the results. However, interactive molecular simulation tools promise to handle time-consuming tasks such as the modeling of particularly complex biomolecular structures more efficiently or to support approaches such as Rational Drug Design with regard to pharmaceutical applications.

(1) Background: We developed an algorithm to perform interactive molecular simulations (IMS) of protein alignment in membranes, allowing on-the-fly monitoring and manipulation of such molecular systems at various scales. (2) Methods: UnityMol, an advanced molecular visualization software; MDDriver, a socket for data communication; and BioSpring, a Spring network simulation engine, were extended to perform IMS. These components are designed to easily communicate with each other, adapt to other molecular simulation software, and provide a development framework for adding new interaction models to simulate biological phenomena such as protein alignment in the membrane at a fast enough rate for real-time experiments. (3) Results: We describe in detail the integration of an implicit membrane model for Integral Membrane Protein And Lipid Association (IMPALA) into our IMS framework. Our implementation can cover multiple levels of representation, and the degrees of freedom can be tuned to optimize the experience. We explain the validation of this model in an interactive and exhaustive search mode. (4) Conclusions: Protein positioning in model membranes can now be performed interactively in real time.