Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design

Abstract

Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

α-Glucosidase inhibitors from Chinese bayberry (Morella rubraSieb. et Zucc.) fruit: molecular docking and interaction mechanism of flavonols with different B-ring hydroxylations

“…Adjacent hydroxyl groups on B ring of avonols might increase its electron cloud density, which was benecial for hydrogen atoms donation to form hydrogen bonds easier with active-center residues of a-glucosidase. It was reported that hydrogen bonds formation could help to increase the stability of complex, 51,52 so the inhibitor bound more tightly to enzyme and enhanced its inhibition activity. Therefore, it was proposed that a-glucosidase inhibitory effects of these avonols were enhanced with increase number of hydroxyl groups at their Bring, which was consistent with the results of in vitro enzyme activity test.…”

Advances in protein structure prediction and design

“…In other words, obtaining a sequence with a fully connected network from a sequence with no hydrogen bond network requires that the sequence optimization simulation pass through intermediate sequences with high energies. To address this issue, a side-chain sampling protocol that uses a graphical representation of potential hydrogen bond partners was developed to enumerate all possible side-chain hydrogen bond networks for an input backbone structure [107][108][109] . This method allowed the design of helical oligomers with large numbers of buried polar amino acids and high binding specificities between the protein chains.…”

Modular repeat protein sculpting using rigid helical junctions

“…We then select out the small fraction of the fusions in which the joined DHRs are in contact beyond the superimposed junction helix to reduce flexibility across the junction by requiring that at least two helices from each DHR make contact across the new interface. We also filtered out models with buried unsatisfied hydrogen bonds (13) and then used Rosetta de novo structure prediction calculations to identify sequences strongly specifying the designed structures in silico (Fig. 1D).…”