NMR Assignment through Linear Programming

TL;DR

This paper presents LIAN, a linear programming approach that improves the accuracy of assigning resonance frequencies in NMR spectroscopy for protein structure determination.

Contribution

The paper introduces a novel linear programming formulation for NMR resonance assignment, achieving state-of-the-art results on simulated and real datasets.

Findings

State-of-the-art accuracy in resonance assignment

Effective linear programming formulation

Validated on both simulated and experimental data

Abstract

Nuclear Magnetic Resonance (NMR) Spectroscopy is the second most used technique (after X-ray crystallography) for structural determination of proteins. A computational challenge in this technique involves solving a discrete optimization problem that assigns the resonance frequency to each atom in the protein. This paper introduces LIAN (LInear programming Assignment for NMR), a novel linear programming formulation of the problem which yields state-of-the-art results in simulated and experimental datasets.