All-atom computer simulations which cover the
biologically relevant timescales
Our drug discovery protocols are based on original reaction path sampling and data reduction algorithms, developed through more than a decade of research at the Physics Department of Trento University. This line of investigation is inspired by the conviction that the quest for overcoming the existing limitations of computational biochemistry should not be limited to building increasingly powerful supercomputers. To access the biologically relevant timescales we need a new generation of algorithms, possibly based on more advanced and powerful mathematical frameworks.
Following this guiding principle, we are developing and implementing innovative reaction path sampling algorithms based on the mathematical framework of Path Integration and Stochastic Calculus. Our data reduction protocols are derived from Nobel Prize-winning concepts which define the so-called Renormalization Group Theory, originally introduced to study critical phenomena in condensed matter physics, combined with the notion of Effective Field Theory, a pivotal concept in contemporary nuclear and particle physics.
The software we develop implements these innovative in silico technologies and enables us to provide the complete characterization of very complex and rare biomolecular transitions, such as protein folding, misfolding and allosteric transitions using state-of-the-art microscopic models (all-atom force fields).