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Protein Folding

Protein Folding

Conservation of Protein Domains Over Different Proteins

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...

Protein Organization

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....

Conservation of Protein Domains

Conservation of Protein Domains

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...

Protein and Protein Structure

Protein and Protein Structure

Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...

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Related Experiment Video

Updated: May 22, 2025

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

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

Published on: July 16, 2017

Conformational ensembles for protein structure prediction.

Jiaan Yang^1,2, Wen Xiang Cheng³, Peng Zhang^3,4

¹Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China. jiaanyang@yahoo.com.

Scientific Reports

|March 13, 2025

Summary

This summary is machine-generated.

A new FiveFold approach generates protein conformational ensembles, overcoming limitations of AI structure prediction. This method reveals protein intrinsic disorder and folding variations for multiple protein structures.

Keywords:

AlphaFold Intrinsically disordered protein Protein conformation Protein folding Protein intrinsic disorder Protein structure prediction

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Last Updated: May 22, 2025

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

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

Published on: July 16, 2017

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

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Area of Science:

Computational Biology
Structural Biology
Protein Folding

Background:

Predicting protein conformational ensembles is crucial for understanding protein folding and intrinsically disordered proteins.
Current AI methods like AlphaFold predict single conformations, failing to capture protein intrinsic disorder.

Purpose of the Study:

To develop a novel method for acquiring protein conformational ensembles.
To address the limitations of existing AI tools in predicting multiple protein conformations.

Main Methods:

Introduced the FiveFold approach, a single-sequence method utilizing protein folding shape codes (PFSC).
Generated protein folding variation matrices (PFVM) to analyze local folding variations.
Constructed ensembles of multiple conformational protein structures from PFSC strings.

Main Results:

The FiveFold approach successfully generated massive numbers of folding conformations.
Evaluated using benchmark proteins (P53_HUMAN, LEF1_HUMAN, Q8GT36_SPIOL), demonstrating effective prediction of multiple conformations.
Validated the algorithm's biological meaningfulness in predicting protein conformational diversity.

Conclusions:

The FiveFold approach provides an effective algorithm for predicting protein multiple conformation structures.
This method advances the study of protein folding and intrinsically disordered proteins by capturing conformational ensembles.