CMU-CS-07-156
Computer Science Department
School of Computer Science, Carnegie Mellon University



CMU-CS-07-156

Detecting Protein-Protein Interaction Decoys
using Fast Free Energy Calculations

Christopher James Langmead*, Hetunandan Kamisetty

October 2007

CMU-CS-07-156.pdf


Keywords: Markov Random Fields, generalized belief propagation, free energy, protein-protein interactions

We present a physics-based method for identifying native configurations of protein-protein interactions amongst a set of nearly native decoys (< 2.0 Å Ca RMSD to the native structure) using a fast new method for performing free energy calculations. The method uses Markov Random Fields to encode the Boltzmann distribution for a given complex, and Generalized Belief Propagation to perform the free energy calculation. Our method is fast, running in a few minutes on a single-processor workstation, making it an attractive alternative to free-energy calculations based molecular dynamics and Monte Carlo simulations, which can require hours or days on multiprocessor machines. The method is also accurate; in an experiment involving 9 targets with an average of 8 nearly native decoys, our method ranks the native structure number one 67% of the time, and in the top three for the remaining cases.

14 pages

*Department of Computer Science and Department of Biological Sciences, Carnegie Mellon University


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