Optimization Online


Prediction of the binding affinities of peptides to class II MHC using a regularized thermodynamic model

Andrew J. Bordner (bordner.andrew***at***mayo.edu)
Hans D. Mittelmann (mittelmann***at***asu.edu)

Abstract: The binding of peptide fragments of extracellular peptides to class II MHC is a crucial event in the adaptive immune response. Each MHC allotype generally binds a distinct subset of peptides and the enormous number of possible peptide epitopes prevents their complete experimental characterization. Computational methods can utilize the limited experimental data to predict the binding affinities of peptides to class II MHC. These methods have applications in vaccine design and in understanding autoimmune disorders. We have developed the Regularized Thermodynamic Average, or RTA, method for predicting the affinities of peptides binding to class II MHC. RTA accounts for all possible peptide binding conformations using a thermodynamic average and includes a parameter constraint for regularization to improve accuracy on novel data. RTA was shown to achieve higher accuracy, as measured by AUC, than SMM-align on the same data for all 17 MHC allotypes examined. The method also correctly predicted the peptide binding register of 17 out of 18 peptide-MHC complexes. Finally, we found that suboptimal peptide binding registers, which are often ignored in other prediction methods, made significant contributions of at least 50% of the total binding energy for approximately 20% of the peptides.


Category 1: Applications -- Science and Engineering (Biomedical Applications )

Citation: BMC Bioinformatics 2010, 11:41

Download: [PDF]

Entry Submitted: 08/07/2009
Entry Accepted: 08/10/2009
Entry Last Modified: 08/30/2013

Modify/Update this entry

  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository


Coordinator's Board
Classification Scheme
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Optimization Society