MOLECULAR DYNAMICS SIMULATIONS OF BIOLOGICAL MACROMOLECULES: APPLICATIONS TO STRUCTURAL VACCINOLOGY AND PEPTIDE DESIGN
type: CreativeWork
description: 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 underst…
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 underst…
author: G. Scarabelli
language: eng
keywords: epitope prediction, folding, unfolding, Settore CHIM/06 - Chimica Organica
date published: 2010-12-15
date modified: 2026-07-27T20:19:17Z
provider: Università degli Studi di Milano
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Università degli Studi di Milano

PropertyValue
property ID: Handle
value: http://hdl.handle.net/2434/150154

PropertyValue
property ID: DOI
value: 10.13130/scarabelli-guido_phd2010-12-15