An Algebraic Geometry Approach to Protein Structure Determination from NMR Data

Our paper describes the first provably-efficient algorithm for determining protein structures de novo, solely from experimental data. We show how the global nature of a certain kind of NMR data provides quantifiable complexity-theoretic benefits, allowing us to classify our algorithm as running in polynomial time. While our algorithm uses NMR data as input, it is the first polynomial-time algorithm to compute high-resolution structures de novo using any experimentally-recorded data, from either NMR spectroscopy or X-Ray crystallography. Improved algorithms for protein structure determination are needed, because currently, the process is expensive and time-consuming. For example, an area of intense research in NMR methodology is automated assignment of nuclear Overhauser effect (NOE) restraints, in which structure determination sits in a tight inner-loop (cycle) of assignment/refinement. These algorithms are very time-consuming, and typically require a large cluster. Thus, algori...

• Type: Conference
• Year: 2005
• Where: CSB
• Authors: Lincong Wang, Ramgopal R. Mettu, Bruce Randall Donald
• Keywords: Algorithms, Bioinformatics, CSB 2005, Protein Structure, Protein Structure Determination