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Related Concept Videos

Protein Networks02:26

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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein-protein Interfaces02:04

Protein-protein Interfaces

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 polypeptide...
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
Conservation of Protein Domains Over Different Proteins02:26

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 form...
Protein Families02:47

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key locations, protein...
Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

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Protein Target Prediction and Validation of Small Molecule Compound
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Protein Target Prediction and Validation of Small Molecule Compound

Published on: February 23, 2024

Predicting Protein Function in the AI and Big Data Era.

Riccardo Percudani1, Carlo De Rito1

  • 1Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy.

Biochemistry
|May 17, 2025
PubMed
Summary

Deep learning and AI are revolutionizing protein function prediction. These advanced methods enrich protein databases with 3D structures, improving our understanding of molecular life.

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A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

  • Proteomics and Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Traditional methods for determining protein function from genomic sequences are largely outdated.
  • Recent advancements in big data analytics have spurred progress in functional genomics.
  • The integration of artificial intelligence (AI) and deep learning (DL) is transforming biological research.

Purpose of the Study:

  • To highlight the impact of AI and DL on predicting protein functions.
  • To emphasize the enrichment of protein databases with structural and functional information.
  • To discuss the potential of these methods in advancing molecular-level understanding of life.

Main Methods:

  • Utilizing deep learning algorithms for analyzing genomic and proteomic data.
  • Employing AI-based approaches to predict protein structures and functions.
  • Integrating large-scale biological datasets to train predictive models.

Main Results:

  • AI and DL methods are enhancing protein databases with crucial three-dimensional structural information.
  • These advanced techniques offer the potential to accurately predict biochemical properties and biomolecular interactions.
  • A significant increase in functionally annotated proteins is anticipated.

Conclusions:

  • AI and deep learning represent a paradigm shift in understanding protein function.
  • The enhanced functional insights will deepen our comprehension of biological processes at the molecular level.
  • This progress promises to accelerate discoveries in molecular biology and related fields.