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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

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 analyses the...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...
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-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...
Allosteric Proteins-ATCase01:19

Allosteric Proteins-ATCase

Binding sites linkages can regulate a protein's function.  For example, enzyme activity is often regulated through a feedback mechanism where the end product of the biochemical process serves as an inhibitor.
Aspartate transcarbamoylase (ATCase) is a cytosolic enzyme that catalyzes the condensation of L-aspartate and carbamoyl phosphate to  N-carbamoyl-L-aspartate. This reaction is the first step in pyrimidine biosynthesis. UTP and CTP, the end products of the pyrimidine synthesis pathway,...
Ligand Binding Sites02:40

Ligand Binding Sites

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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Related Experiment Video

Updated: Jun 7, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Heuristic multi-site optimization for protein sequence design using Masked Protein Language Models.

Lijuan Wang1, Yuze Wang2, Chen Qiu1

  • 1School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China.

Plos Computational Biology
|June 5, 2026
PubMed
Summary
This summary is machine-generated.

ProtHMSO, a new framework, uses protein language models to design functional proteins more efficiently. It guides mutation searches, improving drug discovery and protein engineering outcomes.

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

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Last Updated: Jun 7, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

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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

Area of Science:

  • Biotechnology
  • Computational Biology
  • Protein Engineering

Background:

  • Designing proteins with specific functions is crucial for drug discovery and therapeutics.
  • Exploring vast protein sequence possibilities is challenging with current methods.
  • Existing approaches risk local optima and structural instability.

Purpose of the Study:

  • Introduce ProtHMSO, a novel heuristic multi-site optimization framework.
  • Leverage masked protein language models (ProtLMs) for context-aware protein sequence exploration.
  • Enhance the efficiency of genetic algorithms (GAs) and Monte Carlo tree search (MCTS).

Main Methods:

  • ProtHMSO employs ProtLM-derived substitution probabilities to guide heuristic searches.
  • It mimics natural evolution to find synergistic mutations.
  • The framework constrains search spaces using evolutionary and biophysical priors.

Main Results:

  • Generated protein sequences show superior functional performance.
  • Sequences align better with natural sequence distributions compared to other methods.
  • ProtHMSO improved convergence efficiency when integrated with GAs and MCTS.

Conclusions:

  • ProtHMSO accelerates functional protein discovery.
  • It offers a robust framework for efficient, context-aware protein sequence space exploration.
  • The method shows strong potential for therapeutic development applications.