Information-Based Torsion Angle Potential for Proteins and Applications
Rata, Ionel
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/72401
Description
Title
Information-Based Torsion Angle Potential for Proteins and Applications
Author(s)
Rata, Ionel
Issue Date
2009
Doctoral Committee Chair(s)
Jakobsson, Eric
Department of Study
Center for Biophysics and Computational Biology
Discipline
Biophysics and Computational Biology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Biophysics, General
Abstract
Statistical potentials offer a significant bioinformation-based alternative to physical potentials in protein structure prediction and design. As an introduction we survey the aspects and methods involved in the derivation and applicability of various statistical potentials. The statistical potential created in this work is based on a reduced protein representation described by the residue sequence and the backbone structure including the Cbeta atoms. This potential has two components constructed separately. The component characterizes the protein interactions between the neighboring residues along the sequence. As structural variables we use the principal internal degrees of freedom, which are the backbone ϕ and psi dihedral angles corresponding to each residue. We quantify the correlation between every pair of adjacent dihedrals (ϕi, psii) and (psii, ϕ i+1) in the context of local residue sequence (Ri--1, Ri, Ri+1) by extracting and processing the related information from a database of protein loops structures. We focus in detail on an important application of our local potential: the sequence design of peptidic inhibitors for HIV-1 protease. The second component of our statistical potential is designed mainly for assessing the "non-local" protein interactions and is obtained from a distance-based potential applied to our particular protein representation. In association with an adequate search technique we find an efficient way to assemble the two parts of our statistical potential, which appropriately combines both local and non-local contributions. We successfully apply the resulting method to the protein loop modeling.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
