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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

4.3K
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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Ligand Binding and Linkage00:49

Ligand Binding and Linkage

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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...
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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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Protein-protein Interfaces02:04

Protein-protein Interfaces

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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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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.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
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The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

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The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
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Hom-Complex-Based Machine Learning (HCML) for the Prediction of Protein-Protein Binding Affinity Changes upon

Xiang Liu1,2, Huitao Feng2,3, Jie Wu4

  • 1Chern Institute of Mathematics and LPMC, Nankai University, Tianjin, China, 300071.

Journal of Chemical Information and Modeling
|August 30, 2022
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Summary
This summary is machine-generated.

This study introduces a novel Hom-complex-based approach for protein-protein interaction (PPI) analysis. This AI-driven method accurately predicts binding affinity changes, outperforming existing models for drug and antibody design.

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Area of Science:

  • Computational Biology
  • Biophysics
  • Artificial Intelligence

Background:

  • Protein-protein interactions (PPIs) are fundamental to cellular processes, disease mechanisms, and therapeutic development.
  • Artificial intelligence (AI) models show promise for PPI analysis, but efficient molecular representation remains a challenge.

Purpose of the Study:

  • To develop a novel Hom-complex-based representation and machine learning models for predicting PPI binding affinity changes upon mutation.
  • To introduce a new method for multiscale characterization of PPIs using persistent homology and persistent Euler characteristic.

Main Methods:

  • Generation of Hom-complexes from graph representations of protein-protein complexes.
  • Utilizing persistent homology and persistent Euler characteristic as molecular descriptors.
  • Employing gradient boosting tree (GBT) machine learning models for prediction.

Main Results:

  • The proposed Hom-complex-based model demonstrates superior performance in predicting PPI binding affinity changes compared to existing methods.
  • Systematic testing on SKEMPI and AB-Bind datasets validates the model's effectiveness.
  • The approach offers a powerful new tool for PPI analysis.

Conclusions:

  • The Hom-complex-based representation provides an efficient featurization strategy for AI-based PPI models.
  • This novel method holds significant potential for advancing the understanding and manipulation of PPIs.
  • The model can aid in the analysis and design of targeted therapeutics, including antibodies for viruses like SARS-CoV-2.