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Predicting binding energetics from structure: looking beyond DeltaG degrees.

K P Murphy1

  • 1Department of Biochemistry, University of Iowa, Iowa City, IA 52242, USA. K-murphy@uiowa.edu

Medicinal Research Reviews
|July 10, 1999
PubMed
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Predicting drug binding affinity (DeltaG degrees) using structural data is improved by calculating enthalpic (DeltaH degrees) and entropic (DeltaS degrees) contributions. This method enhances understanding of structure-affinity relationships and accounts for pH effects on binding energetics.

Area of Science:

  • Computational chemistry
  • Structural biology
  • Drug discovery

Background:

  • Predicting ligand binding affinity (DeltaG degrees) from molecular structure is crucial for pharmaceutical design.
  • Current methods often rely on empirical terms (hydrophobic effect, hydrogen bonding, entropy), but their limitations in refinement and understanding compensating energetic contributions are significant.
  • The temperature dependence of binding energetics, influenced by heat capacity changes (DeltaCp), further complicates accurate predictions.

Purpose of the Study:

  • To develop and validate a structure-based approach for predicting binding enthalpy (DeltaH degrees), entropy (DeltaS degrees), and heat capacity change (DeltaCp).
  • To enable calculation of the free energy of binding (DeltaG degrees) as a function of temperature.
  • To assess the reliability of computational predictions by accounting for protonation effects on binding energetics.

Related Experiment Videos

Main Methods:

  • Utilizing structural data to predict enthalpic (DeltaH degrees), entropic (DeltaS degrees), and heat capacity change (DeltaCp) contributions to binding.
  • Calculating the free energy of binding (DeltaG degrees) from predicted energetic terms across a temperature range.
  • Comparing computational predictions with experimentally determined binding affinities for various systems.
  • Employing isothermal titration calorimetry to determine proton binding energetics and understand pKa modifications by protein structure.

Main Results:

  • The structure-based prediction of DeltaH degrees, DeltaS degrees, and DeltaCp showed high accuracy across multiple systems, including protein-ligand and protein-protein interactions.
  • Calculated DeltaG degrees values correlated well with experimental data, validating the predictive power of the approach.
  • Strong pH dependencies observed in several systems highlighted the critical role of protonation states in binding energetics.
  • Methods for measuring proton binding energetics provided insights into how protein structure influences the pKa of ionizable groups.

Conclusions:

  • Structure-based prediction of enthalpic and entropic contributions offers a more robust method for determining binding free energy (DeltaG degrees) compared to empirical approaches.
  • Accurate prediction of binding energetics requires explicit consideration of protonation states and their impact on binding.
  • This integrated approach significantly enhances the ability to predict binding affinities from structural information, advancing drug design and molecular understanding.