Density functional theory calculations on entire proteins for free energies of binding: application to a model polar binding site

Proteins. 2014 Dec;82(12):3335-46. doi: 10.1002/prot.24686. Epub 2014 Oct 21.

Abstract

In drug optimization calculations, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method can be used to compute free energies of binding of ligands to proteins. The method involves the evaluation of the energy of configurations in an implicit solvent model. One source of errors is the force field used, which can potentially lead to large errors due to the restrictions in accuracy imposed by its empirical nature. To assess the effect of the force field on the calculation of binding energies, in this article we use large-scale density functional theory (DFT) calculations as an alternative method to evaluate the energies of the configurations in a "QM-PBSA" approach. Our DFT calculations are performed with a near-complete basis set and a minimal parameter implicit solvent model, within the self-consistent calculation, using the ONETEP program on protein-ligand complexes containing more than 2600 atoms. We apply this approach to the T4-lysozyme double mutant L99A/M102Q protein, which is a well-studied model of a polar binding site, using a set of eight small aromatic ligands. We observe that there is very good correlation between the MM and QM binding energies in vacuum but less so in the solvent. The relative binding free energies from DFT are more accurate than the ones from the MM calculations, and give markedly better agreement with experiment for six of the eight ligands. Furthermore, in contrast to MM-PBSA, QM-PBSA is able to correctly predict a nonbinder.

Keywords: DFT; ONETEP; QM-PBSA; T4-lysozyme L99A/M102Q; free energies of binding; large-scale DFT; protein-ligand interactions.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Amino Acid Substitution
  • Bacteriophage T4 / enzymology
  • Binding Sites
  • Databases, Protein
  • Energy Transfer
  • Kinetics
  • Ligands
  • Mathematical Concepts
  • Models, Molecular*
  • Molecular Dynamics Simulation
  • Mutation
  • N-Acetylmuramoyl-L-alanine Amidase / chemistry*
  • N-Acetylmuramoyl-L-alanine Amidase / genetics
  • N-Acetylmuramoyl-L-alanine Amidase / metabolism
  • Protein Conformation
  • Solvents / chemistry
  • Surface Properties
  • Viral Proteins / chemistry*
  • Viral Proteins / genetics
  • Viral Proteins / metabolism

Substances

  • Ligands
  • Solvents
  • Viral Proteins
  • N-Acetylmuramoyl-L-alanine Amidase