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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 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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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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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.
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A Protocol for Computer-Based Protein Structure and Function Prediction

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Mathematical and Machine Learning Approaches for Classification of Protein Secondary Structure Elements from Cα

Ali Sekmen¹, Kamal Al Nasr¹, Bahadir Bilgin^1,2

¹Department of Computer Science, Tennessee State University, Nashville, TN 37209, USA.

|June 28, 2023

Summary

New methods using only Cα atoms can identify protein secondary structure elements (SSEs) even with missing atomic data. These approaches offer alternatives to traditional tools when structural details are incomplete.

Keywords:

machine learning mathematical modeling protein secondary structure protein structure modeling protein trace secondary structure identification

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Area of Science:

Structural Biology
Bioinformatics
Computational Chemistry

Background:

Secondary Structure Elements (SSEs) are vital for protein tertiary structure determination.
Traditional SSE identification tools like DSSP and STRIDE rely on complete atomic information.
Missing atomic data poses a significant challenge for accurate SSE prediction.

Purpose of the Study:

To develop and evaluate novel methods for classifying SSEs using only Cα atom information.
To address limitations of existing tools when spatial atomic details are absent.
To compare the performance of new Cα-based approaches against each other and state-of-the-art methods.

Main Methods:

Development of three distinct approaches: a mathematical model, a deep learning model, and an ensemble of five machine learning models.
Utilizing Cα atom coordinates from protein chains as input.
Comparative analysis against the PCASSO algorithm and among the developed methods.

Main Results:

The proposed methods demonstrate the feasibility of SSE prediction using Cα atoms alone.
Performance evaluation indicates the effectiveness of these novel approaches in handling incomplete structural data.
Comparative results highlight the strengths and weaknesses of each developed method.

Conclusions:

Cα atom-based methods provide a viable alternative for SSE identification when atomic data is incomplete.
These new approaches enhance the robustness of secondary structure prediction in structural biology.
The study offers valuable tools for experimental tertiary structure determination workflows.