Authors: Shawna Thomas, Lydia Tapia, Chinwe Ekenna, Hsin-Yi (Cindy) Yeh, Nancy M. Amato

Venue: Association for the Advancement of Artificial Intelligence (AAAI) Workshop
DOI:
Link to Publication

Abstract:
Protein folding plays an essential role in protein function and stability. Despite the explosion in our knowledge of structural and functional data, our understanding of protein folding is still very limited. In addition, methods such as folding core identification are gaining importance with the increased desire to engineer proteins with particular functions and efficiencies. However, defining the folding core can be challenging for both experiment and simulation. In this work, we use rigidity analysis to effectively sample and model the protein's energy landscape and identify the folding core. Our results show that rigidity analysis improves the accuracy of our approximate landscape models and produces landscape models that capture the subtle folding differences between protein G and its mutants, NuG1 and NuG2. We then validate our folding core identification against known experimental data and compare to other simulation tools. In addition to correlating well with experiment, our method can suggest other components of structure that have not been identified as part of the core because they were not previously measured experimentally. 

@inproceedings{Thomas-rafpma-2013, 
 address = {Bellevue, Washington, USA}, 
 author = {Shawna Thomas and Lydia Tapia and Chinwe Ekenna and Hsin-Yi (Cindy) Yeh and Nancy M. Amato }, 
 booktitle = {AAAI Workshop on Artificial Intelligence and Robotics Methods in Computational Biology}, 
 month = {July}, 
 pages = {38-43}, 
 title = {Rigidity Analysis for Protein Motion and Folding Core Identification}, 
 volume = {WS-13-06}, 
 year = {2013} 
}