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Related Experiment Video

Updated: Mar 2, 2026

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

Exploring biomolecular energy landscapes.

Jerelle A Joseph¹, Konstantin Röder¹, Debayan Chakraborty²

¹Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK. dw34@cam.ac.uk.

Chemical Communications (Cambridge, England)

|May 11, 2017

Summary

This summary is machine-generated.

This study advances molecular modeling by accelerating protein and nucleic acid structure prediction and analysis using computational energy landscapes. New methods enhance the understanding of molecular thermodynamics and kinetics, revealing potential biomolecular switch mechanisms.

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Area of Science:

Computational chemistry
Molecular biophysics
Structural biology

Background:

The potential energy landscape (PEL) is crucial for predicting, understanding, and designing molecular properties.
Advances in computational frameworks are needed to analyze complex molecular systems like proteins and nucleic acids.

Purpose of the Study:

To highlight recent advances in PEL perspective for molecular structure prediction and thermodynamic/kinetic analysis.
To demonstrate accelerated geometry optimization procedures for enhanced computational efficiency.

Main Methods:

Utilizing local rigidification of selected degrees of freedom to accelerate geometry optimization.
Implementing calculations on graphics processing units (GPUs) for significant speed-up.
Analyzing heat capacity and rearrangement rates using progressive local rigidification.

Main Results:

Demonstrated accelerated optimization procedures for a variety of proteins.
Systematic analysis of heat capacity and rearrangement rates for trpzip1.
Illustrated effects of mutation on coiled-coil protein energy landscapes and DNA duplex helix morphology transitions.

Conclusions:

The enhanced computational methods significantly facilitate structure prediction and analysis of protein and nucleic acid thermodynamics and kinetics.
Mutations and helix morphology transitions in proteins and DNA reveal intrinsically multifunnel landscapes.
These multifunnel landscapes indicate potential for biomolecular switch functionalities.