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Related Concept Videos

Protein Organization01:13

Protein Organization

Overview
Protein and Protein Structure02:15

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 can...
Protein Organization01:13

Protein Organization

Overview
Protein Folding01:22

Protein Folding

Overview
Protein Organization01:24

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 Organization01:24

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.

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A Protocol for Computer-Based Protein Structure and Function Prediction
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Porter 6: Protein Secondary Structure Prediction by Leveraging Pre-Trained Language Models (PLMs).

Wafa Alanazi1,2, Di Meng1, Gianluca Pollastri1

  • 1School of Computer Science, University College Dublin (UCD), D04 V1W8 Dublin, Ireland.

International Journal of Molecular Sciences
|January 11, 2025
PubMed
Summary
This summary is machine-generated.

Accurate protein secondary structure prediction is vital for drug development. A new model, Porter 6, uses advanced language models to achieve over 86% accuracy, improving upon previous methods.

Keywords:
bioinformaticscomputational biologydeep learningnatural language processingprotein structure predictionstructural bioinformatics

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Structural biology

Background:

  • Protein secondary structure prediction (PSSP) is essential for understanding protein function, impacting drug development and biotechnology.
  • Deep learning, particularly natural language processing (NLP) algorithms, has shown great promise in enhancing PSSP accuracy.
  • Pre-trained language models (PLMs) offer a powerful approach to capture complex patterns in protein sequences.

Purpose of the Study:

  • To develop a highly accurate and computationally efficient protein secondary structure prediction system.
  • To evaluate the effectiveness of various deep learning models and sequence embeddings for PSSP.
  • To leverage advanced PLMs for improved PSSP performance.

Main Methods:

  • Ensemble of Convolutional Bidirectional Recurrent Neural Network (CBRNN)-based predictors.
  • Utilized protein language model (PLM) ESM-2 for input feature generation.
  • Comprehensive evaluation using distinct sequence embeddings like one-hot encoding and PLM-based approaches.

Main Results:

  • The proposed model, Porter 6, achieved 86.60% accuracy in three-state (Q3) and 76.43% in eight-state (Q8) classifications on a 2022 test set.
  • Maintained robust performance on a 2024 test set with 84.56% Q3 and 74.18% Q8 accuracy.
  • Demonstrated a significant 3% improvement over its predecessor, outperforming or matching state-of-the-art methods.

Conclusions:

  • Porter 6 represents a significant advancement in protein secondary structure prediction accuracy.
  • The integration of advanced PLMs like ESM-2 is highly effective for PSSP.
  • The developed system offers a powerful tool for protein structure and function research.