Prediction of T-Cell Epitope
- 1 January 2007
- journal article
- review article
- Published by Japanese Pharmacological Society in Journal of Pharmacological Sciences
- Vol. 105 (4) , 299-316
- https://doi.org/10.1254/jphs.cr0070056
Abstract
The prevailing methods to predict T-cell epitopes are reviewed. Motif matching, matrix, support vector machine (SVM), and empirical scoring function methods are mainly reviewed; and the thermodynamic integration (TI) method using all-atom molecular dynamics (MD) simulation is mentioned briefly. The motif matching method appeared first and developed with the increased understanding of the characteristic structure of MHC-peptide complexes, that is, pockets aligned in the groove and corresponding residues fitting on them. This method is now becoming outdated due to the insufficiency and inaccuracy of information. The matrix method, the generalization of interaction between pockets of MHC and residues of bound peptide to all the positions in the groove, is the most prevalent one. Efficiency of calculation makes this method appropriate to scan for candidates of T-cell epitopes within whole expressed proteins in an organ or even in a body. A large amount of experimental binding data is necessary to determine a matrix. SVM is a relative of the artificial neural network, especially direct generalization of a linear Perceptron. By incorporating non-binder data and adopting encoding that reflects the physical properties of amino acids, its performance becomes quite high. Empirical scoring functions apparently seem to be founded on a physical basis. However, the estimates directly derived from the method using only structural data are far from practical use. Through regression with binding data of a series of ligands and receptors, this method predicts binding affinity with appropriate accuracy. The TI method using MD requires only structural data and a general atomic parameter, that is, force field, and hence theoretically most consistent; however, the extent of perturbation, inaccuracy of the force field, the necessity of an immense amount of calculations, and continued difficulty of sampling an adequate structure hamper the application of this method in practical use.Keywords
This publication has 88 references indexed in Scilit:
- T Cell Receptor Recognition via Cooperative Conformational PlasticityJournal of Molecular Biology, 2006
- Peptide recognition by the T cell receptor: comparison of binding free energies from thermodynamic integration, Poisson–Boltzmann and linear interaction energy approximationsPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2005
- The interpretation of protein structures: Estimation of static accessibilityPublished by Elsevier ,2004
- Comparison of all atom, continuum, and linear fitting empirical models for charge screening effect of aqueous medium surrounding a protein moleculeThe Journal of Chemical Physics, 2002
- Replica-exchange molecular dynamics method for protein foldingChemical Physics Letters, 1999
- Structural Phase Transition of Di-Block PolyampholyteMolecular Simulation, 1999
- Identification of a common docking topology with substantial variation among different TCR–peptide–MHC complexesCurrent Biology, 1998
- SWISS‐MODEL and the Swiss‐Pdb Viewer: An environment for comparative protein modelingElectrophoresis, 1997
- Empirical Scale of Side-Chain Conformational Entropy in Protein FoldingJournal of Molecular Biology, 1993
- Statistical analysis of the physical properties of the 20 naturally occurring amino acidsProtein Journal, 1985