Molecular mechanism of peptide binding to major histocompatibility complex class I molecules in the cellular context

  • Peptide fragments of all cellular proteins are constantly presented at the cell surface, in a complex with MHC (major histocompatibility complex) class I molecules, to cytotoxic T lymphocytes. The recognition of epitopes of viral or tumor origin induces the lysis of the presenting cell, and thus stops the spread of the infection. Not every peptide can bind to class I since each allotype has its own signature binding motif, manifested in the shape, chemical nature, and depth of the pockets of the binding groove into which side chains of the bound peptide protrude. The length of the bound peptide is usually 8-10 amino acids, since the ends of the binding groove are closed. The structure of MHC class I molecules, and the mode of peptide binding at steady-state, are fairly well understood, whereas the dynamical and energy details of the peptide binding to class I are still a challenge. This is mainly because there is no available crystal or NMR structure of an empty class I molecule. Thus, in the absence of definitive experiments, understanding molecular details of the class I folding process and describing the differences between the peptide-bound and the peptide-free form of class I require a computational approach in addition to the biochemical and biophysical approaches. Molecular dynamics (MD) simulation is a valuable computational approach. It applies the rules of classical mechanics to describe the details of folding and interactions at atomistic level. Enhanced sampling methods of MD estimate values of the energy barriers between the different conformational states of proteins. In this work, I have used MD simulations to study the dynamics of class I in different peptide binding states. I have used several biophysical and biochemical assays to validate experimentally the theoretical assumptions. My data suggest a common model for empty class I molecules. In this model, the F pocket region has a prominent effect on the conformational and energy properties of the entire peptide binding site. When the peptide is absent, the F pocket region shows a high configurational entropy. This suggests partial unfolding of this region at longer time scales. The suggested model explains the dependence of a disease associated class I allotypes on the chaperone protein tapasin for binding peptides. Charge repulsion at the bottom of the F pocket region increases the flexibility of this region and destabilizes its conformation. I have also investigated a mutant form of class I in which the two alpha helices that delineate the F pocket are linked by a disulfide bond that mimics the conformational and dynamic effects of the peptide. The data suggest a coupling between peptide and β2m binding to the F pocket region, which supports a folded conformation of class I. The findings of this project demonstrate a method to describe the energy and conformational details of class I/peptide binding. The suggested model identifies parameters from theoretical simulations that can be used to predict the peptide binding behavior of novel or uncharacterized class I molecules. This work illustrates that MD simulations can be used and complemented by experimental approaches to describe the mechanism of ligand-receptor binding.

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Publishing Institution:IRC-Library, Information Resource Center der Jacobs University Bremen
Granting Institution:Jacobs Univ.
Author:Esam Abualrous
Referee:Sebastian Springer, Ulrich Kleinekathöfer, Mathias Winterhalter, Martin Zacharias
Advisor:Sebastian Springer
Persistent Identifier (URN):urn:nbn:de:gbv:579-opus-1001672
Document Type:PhD Thesis
Date of Successful Oral Defense:2015/06/01
Date of First Publication:2015/06/11
Full Text Embargo Until:2016/06/30
Academic Department:Physics & Earth Sciences
PhD Degree:Physics
Focus Area:Health
Library of Congress Classification:Q Science / QH Natural history - Biology / QH301-705.5 Biology (General) / QH324 Methods of research. Technique. Experimental biology / QH324.2 Data processing. Bioinformatics
Call No:Thesis 2015/17

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