A Novel RDC Analysis Pipeline for Determination of Protein Structure and Dynamics

Irausquin Stephanie J, Irmo SC

Investigators

Abstract

The study of solution state structure and dynamics of biological macromolecules has been one of the long standing challenges in structural biology. Currently, investigating the internal dynamics of proteins is limited to NMR spectroscopy, which often yields limited characterization of internal dynamics. Recent developments in NMR spectroscopy have facilitated the acquisition of a powerful and relevant source of NMR data referred to as Residual Dipolar Couplings (RDC) which can be used as informative, accurate, and economical probes of structure and internal dynamics on pico to microsecond time scales - when most important biological events take place. Despite their promise, a number of unique challenges have been introduced related to the separation of structural from motional information. Here we aim to overcome the challenges associated with RDC data analysis by using the well-studied DiHydroFolate Reductase (DHFR) protein. More specifically, we aim to: 1.) Successfully obtain experimental RDC data from the DHFR protein by NMR spectroscopy and 2.) Develop and implement a novel pipeline for RDC analysis using a number of published software tools, designed to address specific aspects of RDC analysis, to characterize the structure and dynamics of DHFR in solution state. The challenge of the above objectives is in developing a methodology which can bridge the gap between experimental and computational approaches as they relate to investigations of protein structure and dynamics. The proposed analysis pipeline provides such an approach: exemplifying a work-flow that is capable of addressing file input/output compatibility between the different RDC analysis tools; making such research algorithms available via public dissemination; and continuing developments which improve the usability of current software programs, by either incorporating new features into the existing software, or encouraging the inception of other programs for other aspects of RDC analysis. Moreover, the implication of the proposed work is the need for high-performance computing in order to address protein dynamics. Therefore, we will utilize high-performance computing facilities to engage in analysis of extensive Molecular Dynamics Simulation results. Connecting high-performance computing with the developed analysis pipeline, allows for a method that may be used by students and researchers alike and is applicable to a number of other, more challenging proteins for testing hypotheses aimed at further contributing to our understanding of protein structure-function-dynamic relationships. The impact of the proposed research lies in utilizing a multidisciplinary approach which integrates computational, biological and physical sciences and includes collaborations with instrumentation and training facilities. In addition, the PI will assist in the teaching of a Distance-Learning Applied Bioinformatics course as part of an initiative to increase the networking of research activities for both faculty and staff throughout the state; educational activities related to the course include the following teaching responsibilities: innovating the current curriculum; creating and grading exams, quizzes, and homework assignments; maintaining office hours; and mentoring students in the laboratories of the sponsor and co-sponsor.