Increasing the Complexity of Computational Protein Modeling Methodologies for Functional Applications in Biology

Increasing the Complexity of Computational Protein Modeling Methodologies for Functional Applications in Biology PDF Author: Kyle Barlow
Publisher:
ISBN: 9780355386370
Category :
Languages : en
Pages : 99

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Book Description
As the prior state-of-the-art methods for prediction of change in protein-protein interface binding energy post-mutation were not very effective for predicting mutations to side chains other than alanine, I created a new, more general Rosetta method for prediction of these cases. This "flex ddG" method generates and utilizes ensembles of diverse protein conformational states (generated with "backrub" sampling) to predict interface DeltaDeltaG values. Flex ddG is effective for prediction of change in binding free energy post-mutation for mutations to all amino acids, including mutations to alanine, and is particularly effective (when compared to prior methods) for cases of small side chain to large side chain mutations. I show that the method succeeds in these cases due to increased sampling of diverse conformational states, as performance improves (to a threshold) as more diverse states are sampled.