A convenient method for determining cyclic peptide conformation from 1D 1H-NMR information

Area of Science:

• Structural Biology
• Computational Chemistry
• Nuclear Magnetic Resonance Spectroscopy

Background:

• Determining the three-dimensional structure of cyclic peptides is crucial for understanding their biological activity.
• Traditional methods for structure determination can be time-consuming and resource-intensive.

Purpose of the Study:

• To develop a rapid and convenient method for elucidating cyclic peptide backbone conformations.
• To integrate 1D proton nuclear magnetic resonance (1D 1H NMR) data with molecular modeling techniques.

Main Methods:

• Utilized phi angle torsional constraints derived from 3JHN-Hα coupling constants.
• Applied these constraints as potential energy penalty functions within the Amber* force field with a GB/SA solvation model.
• Employed Monte Carlo searches and minimizations, followed by clustering and filtering based on hydrogen-bonding constraints from amide proton chemical shift temperature dependencies.

Main Results:

• The method successfully reproduced previously determined structures for four out of five cyclic peptides that exhibit a predominant conformation.
• Assessed the relative importance of torsional, hydrogen-bonding, and solvation restraints in structure refinement.
• Demonstrated that lack of convergence for the fifth peptide indicated the presence of multiple backbone conformations.

Conclusions:

• The combined 1D NMR and molecular modeling approach offers a fast and efficient alternative for cyclic peptide structure determination.
• This method is particularly effective for cyclic peptides adopting a single dominant conformation.
• Highlights the utility of specific NMR-derived restraints and computational modeling for structural analysis.