Exploring potent ligand for proteins: insights from knowledge-based scoring functions and molecular interaction energies

Structural Chemistry(2017)

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摘要
Two different scoring functions, Hirshfeld fingerprint-based scoring ( HFBS ) and molecular operating environment ( MOE ), and the kernel energy method (KEM) along with counterpoise (CP)-corrected approach were used to estimate the binding energies of protein–ligand complexes and tested against a series of inhibitors of human aldose reductase enzyme. The new scoring function, HFBS , is based on Hirshfeld fingerprints, which are 2D histogram plots of the distances from the molecular Hirshfeld surface to the nearest atomic nuclei inside versus outside the surface and are highly sensitive to the immediate environment of the molecule. The Hirshfeld surface plotted over the ligand molecule helped to visualize the contacts with the active site residues and solvents, which were then taken into account for interaction energy calculations. Application of KEM-assisted CP-corrected approach facilitated an efficient way of calculating interaction energies in protein complex systems. Interaction energies calculated using MP2/6-31G( d ) level of theory allowed us to rank the ligands by potency. We find that both the KEM-assisted CP-corrected interaction energies and the scoring functions used here predict comparable rankings for the strength of binding of the series of ligands as docked to the active site of the protein, which are also in good agreement with the experimental binding affinities in this case.
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关键词
Kernel energy method,Hirshfeld surface,Stockholder partitioning,Knowledge-based scoring function,Protein–ligand interaction,Counterpoise corrections
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