This thesis work is splitted into two parts. The first one is about a computational method for epitope predictions on antigenic proteins, while the second one is related to the characterization of folding/unfolding processes of small natural polypeptides. Starting with the first topic, an increasing number of functional studies of proteins have shown that sequence and structural similarities alone may not be sufficient for reliable prediction of their interaction properties. This is particularly true for proteins recognizing specific antibodies, where the prediction of antibody-binding sites, called epitopes, has proven challenging. The antibody-binding properties of an antigen depend on its structure and related dynamics. Aiming to predict the antibody-binding regions of a protein, we investigate a new approach based on the integrated analysis of the dynamical and energetic properties of antigens, to identify nonoptimized, low-intensity energetic interaction networks in the protein structure isolated in solution. The method is based on the idea that recognition sites may correspond to localized regions with low-intensity energetic couplings with the rest of the protein, which allows them to undergo conformational changes, to be recognized by a binding partner, and to tolerate mutations with minimal energetic expense. Upon analyzing the results on isolated proteins and benchmarking against antibody complexes, it is found that the method successfully identifies binding sites located on the protein surface that are accessible to putative binding partners. The combination of dynamics and energetics can thus discriminate between epitopes and other substructures based only on physical properties. A public web server (BEPPE) has been implemented with MLCE method in order to make it available to the scientific community. Changing topic to folding/unfolding, the analysis of the folding mechanism in peptides adopting well defined secondary structure is fundamental to understand protein folding. Herein, we describe the thermal unfolding of two 15-mer polypeptides (called QK and QK-L10A) homologue to the vascular endothelial growth factor binding region. In particular, on the basis of the temperature dependencies, we characterize the molecules through the combination of spectroscopic (CD and NMR) and computational analyses (MD) highlighting their folding/unfolding steps and how these structures can be used in peptide design.

MOLECULAR DYNAMICS SIMULATIONS OF BIOLOGICAL MACROMOLECULES: APPLICATIONS TO STRUCTURAL VACCINOLOGY AND PEPTIDE DESIGN / G. Scarabelli ; tutor: Laura Belvisi ; cotutor: Giorgio Colombo ; coordinatore: Dominique Roberto. Università degli Studi di Milano, 2010 Dec 15. 23. ciclo, Anno Accademico 2010. [10.13130/scarabelli-guido_phd2010-12-15].

MOLECULAR DYNAMICS SIMULATIONS OF BIOLOGICAL MACROMOLECULES: APPLICATIONS TO STRUCTURAL VACCINOLOGY AND PEPTIDE DESIGN

G. Scarabelli
2010

Abstract

This thesis work is splitted into two parts. The first one is about a computational method for epitope predictions on antigenic proteins, while the second one is related to the characterization of folding/unfolding processes of small natural polypeptides. Starting with the first topic, an increasing number of functional studies of proteins have shown that sequence and structural similarities alone may not be sufficient for reliable prediction of their interaction properties. This is particularly true for proteins recognizing specific antibodies, where the prediction of antibody-binding sites, called epitopes, has proven challenging. The antibody-binding properties of an antigen depend on its structure and related dynamics. Aiming to predict the antibody-binding regions of a protein, we investigate a new approach based on the integrated analysis of the dynamical and energetic properties of antigens, to identify nonoptimized, low-intensity energetic interaction networks in the protein structure isolated in solution. The method is based on the idea that recognition sites may correspond to localized regions with low-intensity energetic couplings with the rest of the protein, which allows them to undergo conformational changes, to be recognized by a binding partner, and to tolerate mutations with minimal energetic expense. Upon analyzing the results on isolated proteins and benchmarking against antibody complexes, it is found that the method successfully identifies binding sites located on the protein surface that are accessible to putative binding partners. The combination of dynamics and energetics can thus discriminate between epitopes and other substructures based only on physical properties. A public web server (BEPPE) has been implemented with MLCE method in order to make it available to the scientific community. Changing topic to folding/unfolding, the analysis of the folding mechanism in peptides adopting well defined secondary structure is fundamental to understand protein folding. Herein, we describe the thermal unfolding of two 15-mer polypeptides (called QK and QK-L10A) homologue to the vascular endothelial growth factor binding region. In particular, on the basis of the temperature dependencies, we characterize the molecules through the combination of spectroscopic (CD and NMR) and computational analyses (MD) highlighting their folding/unfolding steps and how these structures can be used in peptide design.
15-dic-2010
Settore CHIM/06 - Chimica Organica
epitope prediction ; folding ; unfolding
BELVISI, LAURA
ROBERTO, DOMINIQUE MARIE
Doctoral Thesis
MOLECULAR DYNAMICS SIMULATIONS OF BIOLOGICAL MACROMOLECULES: APPLICATIONS TO STRUCTURAL VACCINOLOGY AND PEPTIDE DESIGN / G. Scarabelli ; tutor: Laura Belvisi ; cotutor: Giorgio Colombo ; coordinatore: Dominique Roberto. Università degli Studi di Milano, 2010 Dec 15. 23. ciclo, Anno Accademico 2010. [10.13130/scarabelli-guido_phd2010-12-15].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/150154
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