Guiding automated NMR structure determination using a global optimization metric, the NMR DP score

Area of Science:

• Structural Biology
• Biophysics
• Computational Chemistry

Background:

• Nuclear Magnetic Resonance (NMR) spectroscopy is crucial for determining molecular structures.
• Automated interpretation of NOESY (Nuclear Overhauser Effect Spectroscopy) peak lists is essential for efficient structure calculation.
• Previous automated methods faced challenges with raw or refined peak lists and resonance assignment errors.

Purpose of the Study:

• To present ASDP, an advanced automated NMR NOE assignment program.
• To demonstrate ASDP's performance and improvements using blinded NMR data from the CASD-NMR project.
• To highlight ASDP's capability for robust NOE interpretation and integration with various structure determination software.

Main Methods:

• ASDP employs a bottom-up, topology-constrained network anchoring approach for NOE interpretation.
• Input includes 2D, 3D, or 4D NOESY peak lists and resonance assignments.
• Algorithmic improvements include using a discriminating power score for model selection and identifying resonance assignment errors.

Main Results:

• ASDP demonstrated high performance on all tested targets using both raw and refined NOESY peak list data in blinded trials.
• The program successfully generated unambiguous NOE constraints for iterative structure calculations.
• ASDP effectively identified and corrected errors stemming from inaccurate NMR resonance assignments.

Conclusions:

• ASDP is a robust, fully-automated program for NOE assignment and interpretation in NMR structure determination.
• Its advanced algorithms improve structural accuracy and reliability compared to previous methods.
• ASDP is versatile and compatible with multiple structure generation and refinement programs like CYANA, CNS, and Rosetta.