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Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Conservation of Protein Domains Over Different Proteins

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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.
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Protein and Protein Structure

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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.
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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

Enhancing HMM-based protein profile-profile alignment with structural features and evolutionary coupling information.

Xin Deng, Jianlin Cheng¹

¹Computer Science Department, Informatics Institute, C, Bond Life Science Center, University of Missouri-Columbia, Columbia, MO 65211, USA. chengji@missouri.edu.

BMC Bioinformatics

|July 27, 2014

Summary

Improving protein sequence profile-profile alignment accuracy is crucial for biological analysis. Integrating predicted structural data like solvent accessibility and torsion angles enhances remote homology detection and alignment precision.

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An Integrated Approach for Microprotein Identification and Sequence Analysis

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Area of Science:

Bioinformatics
Computational Biology
Structural Bioinformatics

Background:

Protein sequence profile-profile alignment is vital for identifying distant protein relationships and creating precise pairwise alignments.
This method is fundamental for tasks such as protein database searching, structure and function prediction, and phylogenetic analysis.

Purpose of the Study:

To enhance the accuracy of protein sequence profile-profile alignment.
To investigate the utility of integrating predicted structural features into alignment algorithms.

Main Methods:

The study employed a pairwise Hidden Markov Model (HMM) based profile alignment method.
Predicted solvent accessibility, torsion angles, and evolutionary residue coupling information were integrated into the alignment process.

Main Results:

The integration of predicted relative solvent accessibility and torsion angle information significantly improved the accuracy of profile-profile alignments.
Evolutionary residue coupling information showed a variable, though sometimes helpful, contribution to alignment improvement.

Conclusions:

Incorporating predicted structural data, specifically solvent accessibility and torsion angles, offers a valuable strategy for enhancing pairwise profile-profile alignment methods.