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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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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.
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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.
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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.
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Recent advances in predicting and modeling protein-protein interactions.

Jesse Durham1, Jing Zhang1, Ian R Humphreys2

  • 1Eugene McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, USA; Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Trends in Biochemical Sciences
|April 15, 2023
PubMed
Summary

Computational methods leveraging evolutionary data and AI accurately predict protein-protein interactions (PPIs) and model complex structures. This advance aids understanding of biological processes and diseases caused by disrupted PPIs.

Keywords:
coevolutionhomologyinteractomemachine learningmultiple sequence alignment (MSA)protein–protein dockingprotein–protein interaction (PPI)

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Area of Science:

  • Computational biology
  • Structural biology
  • Genomics

Background:

  • Protein-protein interactions (PPIs) are fundamental to biological processes.
  • Disruption of PPIs is implicated in various diseases.
  • Experimental methods for studying PPIs are often limited in scope and scale.

Purpose of the Study:

  • To advance computational methods for predicting PPIs and modeling protein complex structures.
  • To leverage evolutionary information and machine learning for enhanced prediction accuracy.
  • To explore the potential of AI in providing proteome-wide 3D models of PPIs.

Main Methods:

  • Utilizing evolutionary information from homologous sequences.
  • Applying sophisticated statistical and machine learning (ML) algorithms to detect covariation signals.
  • Employing artificial intelligence (AI)-based modeling for protein structure prediction.

Main Results:

  • Computational methods now approach experimental accuracy for predicting permanent PPIs.
  • These methods show promise for elucidating transient PPIs.
  • Covariation signals effectively predict physiological interactions.

Conclusions:

  • Rich evolutionary information is key to successful PPI prediction.
  • AI-driven protein structure modeling offers a scalable approach to understanding PPIs.
  • These advancements hold significant potential for biological and medical research.