Postdoctoral: Physical Geometric Algorithms and Systems for Structural Biology Using Mass Spectrometry

Dartmouth College, Hanover NH

Investigators

Abstract

EIA- 0102710 Donald, Bruce Dartmouth College CISE Postdoctoral Associates in Experimental Computer Science: Physical Geometric Algorithms and Systems for High-Throughput NMR While automation is revolutionizing many aspects of biology, the determination of three-dimensional protein structure remains an expensive task. Traditional automated and semiautomated approaches to protein structure determination through nuclear magnetic resonance (NMR) spectroscopy require dozens of experiments and months of spectrometer time, making them unsuitable for high-throughput automation. The research proposed is to develop algorithms and systems for determining protein structure from only a few key NMR spectra. The system will use algorithms similar to and adapted from physical geometric algorithms, pattern recognition and machine vision, signal processing, and robotics, in order to analyze spectra, assign spectral peaks to atom interactions, compute secondary structure, and estimate the global fold. Previously developed software, JIGSAW, represents NMR data with graphs encoding potential interactions between amino acid residues. JIGSAW applies graph algorithms to find subgraphs encoding the secondary protein structure. The postdoctoral research associate will build on the insights of JIGSAW by assisting to 1) integrate automated analysis of geometry and correlations in three-dimensional input spectra, 2) prove correctness, completeness, and complexity results within a random graph formalism, 3) extend JIGSAW to larger proteins, and 4) utilize long-range interactions in order to estimate three-dimensional protein structure.