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Determination of Protein-ligand Interactions Using Differential Scanning Fluorimetry
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Accurate and Efficient Calculation of Protein-Ligand Interaction Energies Using an Electrostatically Embedded

Yingfeng Zhang1, Wei Xia2,3, Kaifang Huang4

  • 1Faculty of Synthetic Biology, Shenzhen University of Advanced Technology, Shenzhen 518055, China.

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|January 27, 2026
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Summary
This summary is machine-generated.

Accurate protein-ligand binding energy calculation is vital for drug design. This study refines the Electrostatically Embedded Generalized Molecular Fractionation with Conjugate Caps (EE-GMFCC) method for efficient and accurate quantum mechanical (QM) energy computations.

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Area of Science:

  • Computational chemistry
  • Molecular modeling
  • Drug discovery

Background:

  • Accurate protein-ligand binding free energy calculation is crucial for rational drug design.
  • Traditional quantum-mechanical (QM) methods are computationally prohibitive for large systems.
  • Fragmentation methods offer a computationally tractable alternative but require accurate environmental modeling.

Purpose of the Study:

  • To present and refine the Electrostatically Embedded Generalized Molecular Fractionation with Conjugate Caps (EE-GMFCC) approach, specifically EE-GMFCC[P-L], for protein-ligand interaction energy calculations.
  • To establish a high-accuracy benchmark data set for developing and validating computational drug design methods.

Main Methods:

  • Application and refinement of the EE-GMFCC[P-L] method for QM energy calculations.
  • Systematic investigation of methodological parameters: ligand charge, capping scheme, and basis set.
  • Calculation of interaction energies for a benchmark set of 21 protein-ligand systems.

Main Results:

  • The EE-GMFCC[P-L] method efficiently computes total QM energy by combining fragment energies in a protein point-charge field and non-neighboring fragment interactions.
  • Methodological parameter investigations informed optimal settings for the EE-GMFCC approach.
  • A high-accuracy data set of protein-ligand interaction energies was generated.

Conclusions:

  • The refined EE-GMFCC[P-L] method provides an efficient and accurate means to compute protein-ligand interaction energies.
  • The generated benchmark data set serves as a valuable resource for advancing computational drug design methodologies.
  • This work facilitates the development of more approximate yet reliable computational tools for drug discovery.