Institute for Advanced Simulation (IAS)

Computational Biomedicine (IAS-5 / INM-9)

Graph-based algorithms for dynamic hydrogen-bond networks

Dynamic hydrogen(H)-bonds and hydrogen-bond networks provide proteins with structural plasticity required for function. Proteins for which dynamic H-bond networks are particularly important for function include protonation-coupled membrane receptors and transporters. In such proteins, it is commonly thought that extended networks of protein and protein-water H-bonds assemble transiently to establish allosteric communication between distinct regions of the protein, to bind and conduct protons. The dynamic nature of such networks, and the relatively large size of many membrane receptors and transporters of direct interest to human health and disease, raise the challenges of how to compute and analyze efficiently the H-bond interaction networks, how to rank the relative importance of protein groups for allosteric protein couplings, and how to begin to predict titratable protein sidechains where protonation change might occur during protein function.

We develop graph-based algorithms to compute H-bond networks from datasets of protein structures from structural biology and from numerical simulations. We apply these algorithms to decipher the role of dynamical H-bond networks in the reaction mechanisms of protonation-coupled proteins and peptides.