Abstract

ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. With a [13C,15N]-labeled protein sample loaded into the NMR spectrometer, ADAPT-NMR delivers complete backbone resonance assignments and secondary structure in an optimal fashion without human intervention. ADAPT-NMR achieves this by implementing a strategy in which the goal of optimal assignment in each step determines the subsequent step by analyzing the current sum of available data. ADAPT-NMR is the first iterative and fully automated approach designed specifically for the optimal assignment of proteins with fast data collection as a byproduct of this goal. ADAPT-NMR evaluates the current spectral information, and uses a goal-directed objective function to select the optimal next data collection step(s) and then directs the NMR spectrometer to collect the selected data set. ADAPT-NMR extracts peak positions from the newly collected data and uses this information in updating the analysis resonance assignments and secondary structure. The goal-directed objective function then defines the next data collection step. The procedure continues until the collected data support comprehensive peak identification, resonance assignments at the desired level of completeness, and protein secondary structure. We present test cases in which ADAPT-NMR achieved results in two days or less that would have taken two months or more by manual approaches.

Highlights

  • A goal-directed experimental strategy can be defined as one that optimizes each new experimental step by analyzing the current sum of available results with the aim of achieving a particular goal

  • We describe here a proof of concept implementation of this strategy to the collection and analysis of protein nuclear magnetic resonance (NMR) data with the goal of achieving complete resonance assignments of the type required for automated structure determination

  • The initial stage in solution-state NMR spectroscopy of proteins concerns the production of labeled molecules and the identification of suitable solution conditions for data collection

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Summary

Introduction

A goal-directed experimental strategy can be defined as one that optimizes each new experimental step by analyzing the current sum of available results with the aim of achieving a particular goal. We describe here a proof of concept implementation of this strategy to the collection and analysis of protein NMR data with the goal of achieving complete resonance assignments of the type required for automated structure determination. With crystallography, the subsequent data collection and analysis steps leading to structure determination are fairly standardized and automated, this is not yet the case with protein NMR spectroscopy.

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