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Related Concept Videos

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 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...
Conservation of Protein Domains02:26

Conservation of Protein Domains

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...
Mechanical Protein Function01:58

Mechanical Protein Function

Proteins perform many mechanical functions in a cell. These proteins can be classified into two general categories- proteins that generate mechanical forces and proteins that are subjected to mechanical forces. Proteins providing mechanical support to the structure of the cell, such as keratin, are subjected to mechanical force, whereas proteins involved in cell movement and transport of molecules across cell membranes, such as an ion pump, are examples of generating mechanical force. 
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...

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Related Experiment Video

Updated: Jun 6, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

A unified multimodal model for generalizable zero-shot and supervised protein function prediction.

Frimpong Boadu1,2, Yanli Wang1,2, Jianlin Cheng1,2

  • 1Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri 65211, United States.

Bioinformatics (Oxford, England)
|June 5, 2026
PubMed
Summary

FunBind, a novel AI model, integrates five data types for accurate protein function prediction. It excels at predicting novel functions, outperforming existing methods by leveraging multimodal data and zero-shot learning capabilities.

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Last Updated: Jun 6, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Artificial Intelligence in Biology

Background:

  • Protein function prediction is crucial but challenging, often limited by traditional methods using single or few data types.
  • Existing approaches struggle with predicting novel function terms due to reliance on preselected Gene Ontology (GO) terms.
  • Integrating diverse biological data modalities is key to capturing complex functional relationships.

Purpose of the Study:

  • To develop a multimodal AI model, FunBind, for enhanced protein function prediction.
  • To enable the prediction of previously unseen protein functions.
  • To improve accuracy by jointly learning from diverse biological data.

Main Methods:

  • FunBind utilizes five modalities: protein sequences, textual descriptions, domain annotations, structures, and GO terms.
  • Employs self-supervised pretraining with contrastive learning to create a unified latent space for sequence and other modalities.
  • Incorporates supervised fine-tuning for comprehensive and accurate function classification.

Main Results:

  • FunBind demonstrates effective zero-shot generalization to novel function terms.
  • The model achieves superior performance compared to single-modality models and current state-of-the-art methods.
  • Joint multimodal fine-tuning significantly enhances prediction accuracy.

Conclusions:

  • FunBind offers a powerful approach for accurate protein function prediction by integrating multimodal data.
  • The model's zero-shot capabilities address the challenge of predicting novel protein functions.
  • FunBind represents a significant advancement in computational biology for understanding protein roles.