Semiautomatic sequence-specific assignment of proteins based on the tertiary structure--the program st2nmr.

Area of Science:

• Structural biology
• Biophysical chemistry
• Computational biology

Background:

• Sequence-specific resonance assignment is a critical bottleneck in high-resolution Nuclear Magnetic Resonance (NMR) studies of proteins.
• Protein three-dimensional (3D) structures are often available from experimental (e.g., X-ray crystallography) or computational (e.g., homology modeling) methods.

Purpose of the Study:

• To introduce the st2nmr program for evaluating and optimizing trial sequence-specific assignments of protein spin systems.
• To leverage existing 3D protein structures and Nuclear Overhauser Effect (NOE) data for improved assignment accuracy and efficiency.

Main Methods:

• Utilized a distance-dependent target function to score trial assignments based on predicted NOESY crosspeaks.
• Employed Monte Carlo optimization to refine sequence-specific assignments.
• Tested the st2nmr program on real NMR data from alpha-helical (cytochrome c) and beta-sheet (lipocalin) proteins.

Main Results:

• The st2nmr program successfully reproduced correct sequence-specific assignments for proteins using 2D and/or 15N/13C NOE data.
• The program demonstrated effectiveness with both homology models and X-ray structures.
• st2nmr can also assign resonances for protein-bound ligands, such as heme.

Conclusions:

• st2nmr significantly accelerates the initial steps of NMR-based protein structure analysis.
• The program serves as a valuable complementary tool for automated and semi-automated protein resonance assignment workflows.
• Integration of structural information with NOE data enhances the reliability of NMR assignments.