p53 is arguably one of the most important tumor suppressor proteins in humans. In almost 50% of all human cancers, p53 is found to be nonfunctional mostly due to single point mutations. The primary goals of this proposal are to gain a detailed understanding of the effect of most-frequent p53 cancer mutations on the protein structure and dynamics, and to leverage a novel computational methodology that identifies small molecules able to reactivate destabilized p53 cancer mutants?a method that represents a promising new approach to drug discovery.
We aim to extend our understanding of the structural dynamics of truncated and full-length p53 with state- of-the-art molecular dynamics simulations in order to discovery novel druggable pockets that have not yet been experimentally characterized. Subsequently we plan to use this new structural information to identify small molecules with novel mechanisms of action and reveal new potential therapeutic avenues targeting this vital transcription factor.
p53 is arguably one of the most important tumor suppressor proteins in humans, as it is mutated in over 50% of human cancers. We intend to use computational simulations to get unseen views into how p53 moves and what it looks like, in order to find new druggable pockets that we can target with small molecules in order to reactivate the mutant protein and stop tumor progression.