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Related Concept Videos

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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Nonstandard Reaction Conditions
The interconnection between standard cell potentials and various thermodynamic parameters such as the standard free energy change ΔG° and equilibrium constant K has been previously explored. For example, a redox reaction involving zinc(II) and tin(II) ions at 1 M concentration with Eºcell = +0.291 V and ΔG° = −56.2 kJ is spontaneous.
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A reduction-oxidation reaction is commonly called a redox reaction. In a redox reaction, electrons are transferred from one species to another rather than being shared between or among atoms. The reducing agent or reductant is the species that loses electrons and gets oxidized in the process. The species that gains electrons and gets reduced in the process is the oxidizing agent or oxidant. Redox reactions are represented as two separate equations called half-reactions, where one equation...
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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 free energy change for a reaction that occurs under the standard conditions of 1 bar pressure and at 298 K is called the standard free energy change. Since free energy is a state function, its value depends only on the conditions of the initial and final states of the system. A convenient and common approach to the calculation of free energy changes for physical and chemical reactions is by use of widely available compilations of standard state thermodynamic data. One method involves the...
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The spontaneity of a process depends upon the temperature of the system. Phase transitions, for example, will proceed spontaneously in one direction or the other depending upon the temperature of the substance in question. Likewise, some chemical reactions can also exhibit temperature-dependent spontaneities. To illustrate this concept, the equation relating free energy change to the enthalpy and entropy changes for the process is considered:
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Related Experiment Video

Updated: Jun 4, 2025

15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the µs-ms Timescale
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RED-E-Function-Based Equilibrium Parameter Finder: Finding the Best Restraint Parameters in Absolute Binding Free

Wanyi Huang1, Runduo Liu1, Yufen Yao1

  • 1State Key Laboratory of Anti-Infective Drug Discovery and Development, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou 510006, China.

The Journal of Physical Chemistry Letters
|December 24, 2024
PubMed
Summary

This study introduces a new method, REPF, to optimize restraints in binding free energy calculations. REPF significantly reduces computational costs while maintaining accuracy in predicting ligand-protein binding affinities.

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Area of Science:

  • Computational chemistry
  • Molecular modeling
  • Drug discovery

Background:

  • Free energy perturbation (FEP)-based absolute binding free energy (ABFE) calculations are vital for predicting ligand-protein binding affinities.
  • Optimizing restraint addition in FEP-ABFE is challenging due to non-orthogonal couplings, requiring many simulations (λ windows).

Purpose of the Study:

  • To introduce a novel method, the RED-E-function-based equilibrium parameter finder (REPF), for optimizing restraint equilibrium values.
  • To improve phase-space overlap and convergence during restraint addition in FEP-ABFE calculations.

Main Methods:

  • REPF utilizes harmonic restraints to optimize equilibrium values.
  • The method was applied to 44 protein-ligand complexes across 5 targets.
  • REPF-optimized restraints were compared against existing literature restraint schemes.

Main Results:

  • REPF achieved accuracy comparable to the 12λ approach using only 2λ simulations.
  • This represents a significant reduction in computational cost.
  • Extensive testing confirmed improved convergence and reduced energy fluctuations with REPF-optimized restraints.

Conclusions:

  • REPF offers a more efficient approach to restraint optimization in FEP-ABFE calculations.
  • The method enhances accuracy and reduces computational demands in drug discovery.
  • REPF is a valuable tool for accelerating the prediction of binding affinities.