Scope: A Protein Force Field With An Artificial Neural Network Approach to Protein Refinement

<p>Protein folding is the one of the most important topics of research in Biochemistry. The understanding of how a protein folds into its three dimensional shape from its amino acid sequence is of extreme importance in medicine today because proteins play important roles in diseases such as sickle cell anemia, Alzheimer's disease, and Parkinson's disease to name a few. Current protein force fields such as those implemented in CHARMM, AMBER, NAMD, and Xplor-NIH have many individual force terms that include bonded and non-bonded energies. While deemed complete, the use of these traditional force fields in ab initio approaches to protein structure determination has been unsuccessful. In this report, we introduce the software package SCOPE and its utility in evaluating and extending the currently existing force fields. SCOPE is unique in a number of ways, including its examination of protein structure in rotamer space, which leads to a reduction in dimensionality of the energy landscape and elimination of the bonded energy terms. The latest version of SCOPE includes an exclusive hydrogen bond energy term, and is also capable of producing a hydrogen bond profile that is substantially more informative than a single hydrogen bond energy value. SCOPE also includes a hydrophobicity score and profile. Furthermore the energy profile produced by SCOPE is incorporated into an artificial neural network based approach to predict the backbone root mean square deviation of a given protein structure to that of the native structure based on its potential energy alone. This method has been shown to help with refinement of protein structures from around 7.0 Å to approximately 2.0 Å</p>

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Campus Access Dissertation

Discipline thesis:degree_discipline

Computer Science and Engineering

Year

2012

Author dc:creator

• Fawcett, Timothy Matthew

Contributors dc:contributor

• Homayoun Valafar

• Computer Sciences
• Electrical and Computer Engineering
• Engineering
• Physical Sciences and Mathematics
• Artificial Intelligence
• Bioinformatics
• Computational Biology
• Machine Learning
• Pattern Recognition
• Protein Structure Determination

Statement dc:rights

• © 2012, Timothy Matthew Fawcett

Repository record dc:identifier

https://scholarcommons.sc.edu/etd/779

OAI identifier oai:identifier

oai:scholarcommons.sc.edu:etd-1780