Document Type
Article
Original Publication Date
2014
Journal/Book/Conference Title
Proteins: Structure, Function, and Bioinformatics
Volume
82
Last Page
2253–2262
DOI of Original Publication
10.1002/prot.24592
Date of Submission
March 2015
Abstract
A simple, static contact mapping algorithm has been developed as a first step at identifying potential peptide biomimetics from protein interaction partner structure files. This rapid and simple mapping algorithm, “OpenContact” provides screened or parsed protein interaction files based on specified criteria for interatomic separation distances and interatomic potential interactions. The algorithm, which uses all-atom Amber03 force field models, was blindly tested on several unrelated cases from the literature where potential peptide mimetics have been experimentally developed to varying degrees of success. In all cases, the screening algorithm efficiently predicted proposed or potential peptide biomimetics, or close variations thereof, and provided complete atom-atom interaction data necessary for further detailed analysis and drug development. In addition, we used the static parsing/mapping method to develop a peptide mimetic to the cancer protein target, epidermal growth factor receptor. In this case, secondary, loop structure for the peptide was indicated from the intra-protein mapping, and the peptide was subsequently synthesized and shown to exhibit successful binding to the target protein. The case studies, which all involved experimental peptide drug advancement, illustrate many of the challenges associated with the development of peptide biomimetics, in general.
Rights
© 2014 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. Originally published at http://dx.doi.org/10.1002/prot.24592
Is Part Of
VCU Computer Science Publications
Comments
Alex Krall,1 Jonathan Brunn,2 Spandana Kankanala,2 and Michael H. Peters2,3,4*
1 Department of Computer Science, Virginia Commonwealth University, Richmond, Virginia 23284
2 Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, Virginia 23284
3 Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia 23284
4 Massey Cancer Center, Virginia Commonwealth University, Richmond, Virginia 23298
*corresponding author