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Protein Folding

Protein Folding

Protein Folding

Protein Folding

Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
Protein Structure Is Critical to Its Biological Function
Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...

Protein Folding

Protein Folding

Molecular Models

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.

Protein Complexes with Interchangeable Parts

Protein Complexes with Interchangeable Parts

Protein Complexes with Interchangeable Parts

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order...

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Updated: Apr 19, 2026

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

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

Published on: July 16, 2017

A monte carlo method for generating side chain structural ensembles.

Asmit Bhowmick¹, Teresa Head-Gordon²

¹Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.

Structure (London, England : 1993)

|December 9, 2014

Summary

This summary is machine-generated.

A new Monte Carlo method accurately models protein structures by analyzing side chain entropy and backbone flexibility. This approach effectively distinguishes native protein states from misfolded structures across many proteins.

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

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Published on: July 16, 2017

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR

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A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

Computational Biology
Structural Biology
Biophysics

Background:

Understanding protein conformational ensembles is crucial for deciphering protein function and misfolding.
Accurate modeling of side chain dynamics and their influence on protein structure remains a challenge.

Purpose of the Study:

To introduce a novel computational method, Monte Carlo side chain entropy (MC-SCE), for describing protein conformational ensembles.
To validate the MC-SCE method's ability to predict side chain rotamer populations and discriminate between native and misfolded protein states.

Main Methods:

Developed the MC-SCE method incorporating a physical energy function with long-range electrostatics and hydrophobic potentials.
Integrated backbone variations and a backbone-dependent side chain rotamer library into the MC-SCE approach.
Applied the method to analyze X-ray crystallographic and NMR data for various proteins, including CypA, H-Ras, Eglin-C, and DHFR complexes.

Main Results:

Successfully determined side chain rotamer populations from experimental data (X-ray crystallography and NMR J-coupling constants).
Demonstrated reliable prediction of these populations for multiple protein systems.
Achieved high accuracy in discriminating between native and misfolded protein ensembles for 55 different proteins.

Conclusions:

The MC-SCE method provides a robust framework for modeling protein conformational ensembles.
This method significantly improves the accuracy of side chain packing predictions, aiding in the study of protein folding and misfolding.
The MC-SCE approach offers a powerful tool for structural biology and drug discovery efforts.