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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

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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.
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...
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Protein-protein Interfaces02:04

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Protein Organization01:24

Protein Organization

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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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Ligand Binding Sites02:40

Ligand Binding Sites

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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
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Conservation of Protein Domains Over Different Proteins02:26

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 Folding01:22

Protein Folding

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

Yang Yang1,2,3, Mengqi Chen2, Congrui Liu2

  • 1Computing Science and Artificial Intelligence College, Suzhou City University, Suzhou 215004, China.

International Journal of Molecular Sciences
|June 26, 2025
PubMed
Summary
This summary is machine-generated.

Predicting amino acid solubility is key to understanding protein function. A new tool, SolAcc, uses deep learning to accurately predict residue accessibility from protein sequences, outperforming existing methods.

Keywords:
amino acid accessibilitymachine learningprotein structuresequence-based predictionsolubility

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Area of Science:

  • Structural biology
  • Computational biology
  • Biochemistry

Background:

  • Amino acid positioning (surface vs. core) in folded proteins dictates environmental interaction.
  • Residue accessibility is vital for protein functions like enzymatic activity, allostery, multimerization, binding, and immunogenicity.

Purpose of the Study:

  • To develop a novel sequence-based predictor for amino acid accessibility.
  • To provide insights into protein function and residue relevance through solubility prediction.

Main Methods:

  • Feature extraction from three-dimensional protein structures.
  • Testing various machine learning algorithms.
  • Utilizing the long short-term memory (LSTM) deep learning method for prediction.

Main Results:

  • The LSTM deep learning method showed the best performance among tested algorithms.
  • The developed SolAcc tool demonstrated superior performance in blind tests compared to state-of-the-art predictors.

Conclusions:

  • SolAcc is a novel, freely available tool for predicting amino acid accessibility.
  • The tool offers accurate predictions based on sequence data, aiding in understanding protein structure-function relationships.