ARTIST & ASAP Automate, Speed Processes for Residue Type Assignment of Nuclear Magnetic Resonance Signals

Abstract

Two University of Central Florida technologies automate and speed the process of identifying protein structures in crowded spectra. With UCF’s ARTIST and ASAP computer programs, what used to take years now takes days. By assigning NMR and ssNMR signals, scientists can derive protein structures, understand their functions and their connection to certain diseases. In an example application, the faster processes enable pharmaceutical companies to more quickly discover and design drugs to combat disease.

• ARTIST (auto-residue type assignment strategy) automates the residue type assignment of nuclear magnetic resonance (NMR) signals in biomolecules. To identify matched residue type assignments in congested spectra, the UCF technology exploits identical chemical shifts of the same nuclear site across spectra based on reference residue type assignments from better-resolved spectra. The program algorithm can accurately assign the residue type of multidimensional NMR in spectra. Coded in Python, the ARTIST algorithm is tested by NCACX and NCOCX experiments of spectra for multiple proteins. The script can easily be modified to assist residue type assignments of other multidimensional NMR spectra to alleviate the challenge from spectral congestion.
  
  
• ASAP (automatic sequential assignment program) automates the residue type assignment of solid-state nuclear magnetic resonance (ssNMR) signals in congested spectra. Sequential assignment, the foundation for structural NMR studies, is particularly challenging in ssNMR, due to broad resonance lines with increasing protein sizes. UCF’s ASAP algorithm exploits the resonance correlation between different spectra of the same sample to make accurate sequential assignments of congested spectra, given the assignments of resolved spectra. The technology can identify three distinct types of mistaken assignments (local minima) and provides a method to remove or identify them. It is also more accurate and efficient than Monte Carlo simulated annealing (MCSA) algorithm. ASAP first applies the UCF auto-residue type assignment strategy (ARTIST) to group individual resonances in unassigned congested spectra into matched residue type assignments. After accounting for all possible combinations, ASAP then matches residue type assignment pairs sequentially allocated by the Monte Carlo simulated annealing (MCSA) algorithm.

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