Multi-ego: A Structure-based Framework for Molecular Simulations

Efficient and accurate molecular simulations remain a key challenge in computational structural biology. Recently, we introduced multi-eGO, a hybrid structure-based approach that addresses this need by integrating information from classical molecular dynamics (MD) simulations into a simplified potential via a Bayesian approach. This combination results in a versatile framework that maintains atomic resolution while reducing computational cost. In this seminar, I will present the broad potential of multi- eGO for modeling diverse biomolecular processes. Using examples ranging from ligand binding and protein folding to self-assembly, I will illustrate how our framework achieves an effective balance between speed and accuracy. I will also discuss ongoing refinements that extend its applicability to a wide range of systems, including well-structured proteins and intrinsically disordered peptides, opening up avenues previously inaccessible to conventional MD methods. In doing so, multi-eGO advances the use of structure-based frameworks and brings us closer to a realistic computational microscope.