|Project Leader: Piotr Setny, PhD||Project period: 2015 - 2021|
|Project funding: EMBO (Installation Grant)|
It is widely accepted that water affects structure, dynamics and thus function of biomolecules. The magnitude of its contributions to free energy landscape of proteins or nucleic acids remains unknown, while its proper accounting is essential to understand and control biomolecular machines. A reason for the scarcity of quantitative information regarding hydration effects is the lack of experimental techniques allowing to disentangle solute-solvent interactions from dominant bulk effects. Fortunately, the advent of computer technology permitting simulations that cover microseconds of protein evolution in explicit solvent, enough to gain insight into functional time scales, grants access to those previously unexplored aspects of macromolecular (thermo)dynamics. In my lab I am applying computational techniques with the aim to: – quantitatively explore the influence of hydration effects on macromolecular free energy landscape, answering questions such: How large are differences in hydration free energy between distinct functional states of macromolecules compared to changes in internal energy? Do naturally occurring motions result in minimal changes in solvation or rather they involve compensation between strongly varying hydration and internal forces? Is the range of such motions determined by structure stretching or by increasing costs of opening to the solvent? – investigate the role of individual water molecules buried in protein structures for their stability, conformational dynamics, and pathways of allosteric communication, based on the intriguing case of protein kinases whose crystallographic structures reveal a number of internal water molecules at positions better preserved across the family than amino acid types in many functionally important locations, – develop a novel, computationally effective approach to modelling hydration effects and predicting their thermodynamic outcome based on discrete solvent representation and mean field approach.
Biomolecular Modelling Group