Proteins are the workhorses of the cell, carrying their functional role through interactions with other molecules. Many protein-protein interactions (PPI) are mediated by short peptide motifs – which are hard to inhibit with traditional small molecules. Peptide-based drugs can potentially inhibit PPIs involved in disease pathways.<br/><br/>Assessing how peptides bind is difficult due to their inherent flexibility and ability to bind through different binding modes. Particularly, predicting bound conformations of peptides that fold upon binding with computational tools has been a grand challenge. Here we combine chemical shift data information from NMR carried out by our collaborators on several peptide/protein pairs with our Bayesian inference approach (MELD, Modeling Employing Limited Data), to determine bound structures in atomic details. Our studies on several peptides interacting with the ET domain of bromodomain protein families reveals distinct binding patters for the peptide sequences studied.

Determining structures and binding modes in peptide-protein binding through chemical shift perturbation and MELDxMD simulations

ACS Spring Meeting 2021

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