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Optimization of Protein-Ligand Electrostatic Interactions Using an Alchemical Free-Energy Method.

Alexander D WadeDavid J Huggins
Published in: Journal of chemical theory and computation (2019)
We present an explicit solvent alchemical free-energy method for optimizing the partial charges of a ligand to maximize the binding affinity with a receptor. This methodology can be applied to known ligand-protein complexes to determine an optimized set of ligand partial atomic changes. Three protein-ligand complexes have been optimized in this work: FXa, P38, and the androgen receptor. The sets of optimized charges can be used to identify design principles for chemical changes to the ligands which improve the binding affinity for all three systems. In this work, beneficial chemical mutations are generated from these principles and the resulting molecules tested using free-energy perturbation calculations. We show that three quarters of our chemical changes are predicted to improve the binding affinity, with an average improvement for the beneficial mutations of approximately 1 kcal/mol. In the cases where experimental data are available, the agreement between prediction and experiment is also good. The results demonstrate that charge optimization in explicit solvent is a useful tool for predicting beneficial chemical changes such as pyridinations, fluorinations, and oxygen to sulfur mutations.
Keyphrases
  • binding protein
  • protein protein
  • amino acid
  • dna binding
  • molecular dynamics simulations
  • solar cells
  • mass spectrometry
  • capillary electrophoresis
  • deep learning
  • transcription factor