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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....

Protein Organization

Protein Organization

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...

Protein and Protein Structures

Protein and Protein Structures

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 Folding

Protein Folding

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Updated: Dec 16, 2025

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

Deep learning methods in protein structure prediction.

Mirko Torrisi¹, Gianluca Pollastri¹, Quan Le²

¹School of Computer Science, University College Dublin, Ireland.

Computational and Structural Biotechnology Journal

|July 3, 2020

Summary

This summary is machine-generated.

Deep learning methods have advanced protein structure prediction, evolving from early statistical approaches. This review details the progression of these computational techniques and their impact on structural bioinformatics.

Keywords:

Deep learning Machine learning Protein structure prediction

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Area of Science:

Structural Bioinformatics
Computational Biology
Machine Learning

Background:

Protein structure prediction is a fundamental challenge in structural bioinformatics.
Methods have evolved from statistical approaches to machine learning and deep learning.
Databases and evolutionary information have grown, impacting prediction accuracy.

Purpose of the Study:

To review the evolution of protein structure prediction methods.
To introduce deep learning concepts and their application in this field.
To discuss the role of databases and co-evolutionary data.

Main Methods:

Review of historical and modern computational methods for protein structure prediction.
Explanation of deep learning architectures (CNNs, RNNs, feed-forward networks).
Analysis of database growth and its influence on predictive algorithms.

Main Results:

Deep learning significantly enhances the prediction of 1D and 2D protein structure annotations.
Advancements in databases and co-evolutionary analysis have improved prediction accuracy.
Deep learning is now integral to protein structure prediction pipelines.

Conclusions:

Deep learning represents a major advancement in protein structure prediction.
Future opportunities lie in refining deep learning models and integrating diverse data.
Continued research is needed to address remaining challenges in predicting complex protein structures.