Our Research
Our group works on the definition and implementation of strategies to study complex
biophysical processes on long timescales. Despite the significant advances, our quantitative
understanding of biological function at the molecular and cellular level is still in its relative infancy.
Experimental and theoretical approaches to characterize macromolecular dynamics and function have evolved
dramatically in the last few decades. However, experiment and computation have co-existed with limited feedback.
On one hand, simulations can, in principle, resolve details not accessible to experiment, but are based on
empirical models and, alone, cannot be quantitatively predictive. On the other hand, a wealth of indirect
data on the structure and dynamics of macromolecular complexes is available from thermodynamic and kinetic
measurements on parts of the systems of interest, but there is no way to systematically combine these data
into a structural model.
We design multiscale models, adaptive sampling approaches, and data analysis tools
that allow exploring large regions of a system's free energy landscape. We use data-driven methods for systematic
coarse-graining of macromolecular systems, to bridge molecular and cellular scales. We work on a theoretical
formulation to exploit the complementary information that can be obtained in simulation and experiment, to combine
the approximate but high-resolution structural and dynamical information from computational models with the “exact”
but lower resolution information available from experiments.