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¹H NMR of Conformationally Flexible Molecules: Temporal Resolution

¹H NMR of Conformationally Flexible Molecules: Temporal Resolution

At room temperature, the chair conformer of cyclohexane undergoes rapid ring flipping between two equivalent chair conformers at a rate of approximately 105 times per second. These two chair conformers are in equilibrium. The rapid ring flipping results in the interconversion of the axial proton to an equatorial proton and an equatorial to the axial proton. Such interconversions are too rapid and cannot be detected on the NMR timescale. Hence, the NMR spectrometer cannot distinguish between the...

Conformations of Cyclohexane

Conformations of Cyclohexane

Cyclohexane does not exist in a planar form due to the high angle and torsional strain it would experience in the planar structure. Instead, it adopts non-planar chair and boat conformations.
The chair form is the most stable and derives its name from its resemblance to the “easy chair.” In the chair conformation, two carbon atoms are arranged out-of-plane — one above and one below, minimizing the torsional strain. In the chair form, the bond angle is very close to the ideal...

Protein Folding

Protein Folding

¹H NMR of Conformationally Flexible Molecules: Variable-Temperature NMR

¹H NMR of Conformationally Flexible Molecules: Variable-Temperature NMR

The axial and equatorial protons in cyclohexane can be distinguished by performing a variable-temperature NMR experiment. In this process, except for one proton, the remaining eleven protons are replaced by deuterium. The deuterium substitution avoids the possible peak splitting caused by the spin-spin coupling between the adjacent protons. The remaining proton flips between the axial and equatorial positions.

Chair Conformation of Cyclohexane

Chair Conformation of Cyclohexane

The chair conformation is the most stable form of cyclohexane due to the absence of angle and torsional strain. The absence of angle strain is a result of cyclohexane’s bond angle being very close to the ideal tetrahedral bond angle of 109.5° in its chair conformer. Similarly, the torsional strain is also absent owing to the perfectly staggered arrangement of bonds.
The hydrogen atoms linked to carbons are arranged in two different axial and equatorial orientations to achieve this...

Conserved Binding Sites

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...

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Related Experiment Video

Updated: Jul 12, 2025

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Published on: October 13, 2022

Breaking the conformational ensemble barrier: Ensemble structure modeling challenges in CASP15.

Andriy Kryshtafovych¹, Gaetano T Montelione², Daniel J Rigden³

¹Genome Center, University of California, Davis, Davis, California, USA.

|October 24, 2023

Summary

The Critical Assessment of Structure Prediction (CASP) experiment successfully modeled multiple protein and RNA conformations using deep learning. Promising results were achieved for four targets, indicating progress in computational structure prediction.

Keywords:

AlphaFold CASP RNA structure conformational ensemble protein structure

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Published on: January 10, 2018

Area of Science:

Computational structural biology
Biophysics
Bioinformatics

Background:

Traditional protein and RNA structure prediction often focuses on single static models.
Understanding molecular flexibility and multiple conformations is crucial for biological function.
The Critical Assessment of Structure Prediction (CASP) experiment benchmarks structure prediction methods.

Purpose of the Study:

To evaluate methods for computing multiple conformations of protein and RNA structures.
To assess the success of computational approaches in reproducing experimental ensembles.
To identify challenges and opportunities in modeling molecular flexibility.

Main Methods:

Inclusion of a dedicated section for conformational ensemble prediction in the 2022 CASP experiment.
Application of enhanced sampling techniques, including variations of the AlphaFold2 deep learning method for protein structures.
Utilizing experimentally derived flexibility ensembles for RNA structure modeling.

Main Results:

Full or partial success in reproducing conformational ensembles for four out of nine targets.
AlphaFold2 variations proved highly effective for protein conformational sampling, accurately reproducing a significant mutation-induced change.
Successful sampling of near-experimental conformations for two assembly modeling cases without environmental factors; accurate RNA model identified using experimental flexibility data.

Conclusions:

Computational methods show promise in predicting multiple conformations for biomolecular structures.
Deep learning approaches, particularly AlphaFold2, are effective for protein conformational sampling.
Challenges remain in handling low-resolution data and modeling RNA/protein complexes, but these are considered addressable.