Discipline: Biological Sciences
Subcategory: Cell and Molecular Biology
Christopher Jones - Tennessee State University
Co-Author(s): Kamal Al Nasr, Dept. of Computer Science, Tennessee State Universit; Feras Yousef, Department of Mathematics, University of Jordan; Ruba Jebril, Dept. of Computer Science, Tennessee State University
Proteins are undeniably one of the most crucial and most complicated of all biological molecules. We can relatively cheaply sequence the genes that code for them and thus generate a primary structure. However, determining the final, native conformation of the tertiary (or quaternary) structure remains a challenging task. Traditionally X-ray crystallography or nuclear magnetic resonance imaging have been used to map physical structure of the native conformation. Cryo-EM is a newer method that allows us to image the native conformation without having to produce pure crystals of the protein and also allows imaging of much larger or membrane bound proteins.
Unfortunately, cryo-EM does not have the resolution capabilities of the traditional methods and provides a volume cloud rather than strongly localized atomic coordinates. As a result, cryo-EM is often used to help guide de novo modeling of the native conformation rather than as the single determinative factor of the structure.
Currently it is possible to predict the location of secondary structures from the primary structure with an accuracy in the range of 75% to 80%. It is also possible to determine the location of secondary structures by analyzing a cryo-EM volume at a lower level of confidence.
DP-TOSS is an algorithm developed by Al Nasr et. al. which attempts to match the secondary structure located by analysis of a cryo-EM volume with those located by examining the primary structure of the protein. This allows the confirmation of the detection via analysis of the cryo-EM volume and, potentially, could lead to more accurate de novo modeling of protein structures. The analysis is performed by converting the problem in to a constraint graph problem and using dynamic programming techniques to reduce the search time and space.
Our current research is a revision of the scoring function for DP-TOSS to include a new geometry based analysis which improves accuracy over the original function by a substantial margin.
This geometry based analysis is, in essence, the quantification of the parameters of the loop which connects any two secondary structure. Three vectors are defined which describe the first secondary structure, the relationship between it and the second secondary structure and the second secondary structure. These vectors are then used to help calculate the appropriate weigh for any given edge in the constraint graph.
By using this improved scoring function we are able to better score which is the most likely secondary structure topology for a given protein. This will allow better determination of which candidate protein structures are suitable for additional examination (via potential energy based calculation) in future de novo modeling algorithms.
 Al Nasr, K., Ranjan, D., Zubair, M. and He, J. Ranking Valid Topologies of the Secondary Structure elements Using a constraint Graph. Journal of Bioinformatics and Computational Biology, 9, 3 2011), 415-430.
 Al Nasr, K., Ranjan, D., Zubair, M., Chen, L. and He, J. Solving the Secondary Structure Matching Problem in Cryo-EM De Novo Modeling Using a Constrained K-Shortest Path Graph Algorithm. Computational Biology and Bioinformatics, IEEE/ACM Transactions on, 11, 2 2014), 419-430.
 Jones, D. T. Protein secondary structure prediction based on position-specific scoring matrices. Journal of Molecular Biology, 292, 2 (Sep 1999), 195-202.
 Pollastri, G. and McLysaght, A. Porter: a new, accurate server for protein secondary structure prediction. Bioinformatics, 21, 8 (Apr 15 2005), 1719-1720.Not Submitted
Funder Acknowledgement(s): I thank The National Science Foundation for funding this research through the Research Initiation Award (RIA)(HRD: 1600919)
Faculty Advisor: Kamal Al Nasr, firstname.lastname@example.org
Role: Analysis, documentation