Modeling of Biomolecular Systems Interactions, Dynamics, and Allostery: Bridging Experiments and Computations - September 10-14, 2014, Istanbul, Turkey

Modeling of Biomolecular Systems Interactions, Dynamics, and Allostery Poster Session I

3-POS Board 3 Web-Based Structure Prediction as Supplementary Tools to Protein Secondary Structure Analysis with FT-IR Spectroscopy Yekbun Adiguzel . Istanbul Kemerburgaz University, Istanbul, Turkey. Protein studies with Fourier Transform Infrared (FT-IR) spectroscopy include protein secondary structure determination and investigation of protein dynamics through structural changes. The common approach involves curve fitting of the protein-sourced regions of the FT-IR spectrum. The success of this approach relies on several criteria, among which, proper selection of the initial parameters is of utmost importance. Information derived from high resolution structures are tended to be used for this purpose, in order to perform protein studies with FT-IR. However, web-based resources and techniques that serve for protein secondary structure prediction of the proteins with known amino acid sequences can well compensate the necessary information, when high resolution structures are not available or hard to obtain. Therefore, those resources are evaluated as potential supplementary tools for protein studies with FT-IR, through this work. Secondary structure of basic fibroblast growth factor was inspected in this study, as proof of the concept. This protein is of biological and physiological relevance. It binds to heparin, performs wide range of mitogenic and angiogenic activities, and involves in processes like development of the limbs and neural system. Protein secondary structure information of this protein from DSSP (the database for secondary structure assignment in Protein Data Bank) reveals 6.90% helix structure, 41.1% sheets, 19.4% turns, and 32.6% random coils. Seven distinct models that enable protein secondary structure prediction through web-based protein structure prediction servers were tested. Among those, secondary structure prediction by self-optimized prediction method (SOPM) yielded the best results. Accordingly, SOPM results of the basic fibroblast growth factor protein sequence resulted in 6.20% helices, 41.1% sheets, 17.8% turns, and 34.9% random coils. RMSD is 1.23, which is good enough for setting parameters during curve-fitting of FT-IR data for protein studies.

57