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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

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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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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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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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Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
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Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
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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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Updated: Jun 24, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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Robust Prediction of Relative Binding Energies for Protein-Protein Complex Mutations Using Free Energy Perturbation

Jared M Sampson1, Daniel A Cannon2, Jianxin Duan2

  • 1Schrödinger, Inc., Life Sciences Software, New York, NY, USA.

Journal of Molecular Biology
|June 6, 2024
PubMed
Summary

Computational free energy calculations enhance protein design by improving accuracy and reducing costs. This study validates free energy perturbation (FEP+) for predicting binding affinity changes from mutations, offering a more reliable computational tool.

Keywords:
binding affinity predictionfree energy methodsin silico mutational screeningprotein binding interface optimizationprotein-protein interactions

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Area of Science:

  • Computational chemistry
  • Protein engineering
  • Biophysics

Background:

  • Computational methods are crucial for advancing protein design.
  • Accurate prediction of binding affinity changes is essential for protein engineering.
  • Free energy perturbation (FEP+) offers a promising approach for such predictions.

Purpose of the Study:

  • To benchmark free energy perturbation (FEP+) for calculating relative binding affinity changes due to single point mutations.
  • To improve the accuracy and reliability of FEP+ calculations in protein design.
  • To develop automated methods for handling outliers and improving FEP+ predictions.

Main Methods:

  • Utilized free energy perturbation (FEP+) calculations on diverse protein-protein binding systems.
  • Developed a robust method for treating alternate protonation states of titratable amino acids.
  • Analyzed outlier cases and implemented an automated script for outlier identification and correction.

Main Results:

  • FEP+ calculations showed improved correlation and reduced error with experimental binding free energies.
  • The method for protonation states enhanced prediction accuracy.
  • An automated script successfully identified and corrected a subset of charge-related outliers.

Conclusions:

  • The validated FEP+ approach, with improved protonation state treatment and outlier correction, is a reliable tool for protein design.
  • This computational strategy can significantly impact industrial protein design projects.
  • Further studies are suggested to refine protocols and expand applicability.