A binding potential of mean force (BPMF) is a free energy of noncovalent association in which one binding partner is flexible and the other is rigid . I have developed a method to calculate BPMFs for protein-ligand systems. The method is based on replica exchange sampling from multiple thermodynamic states at different temperatures and protein-ligand interaction strengths. Protein-ligand interactions are represented by interpolating precomputed electrostatic and van der Waals grids. Using a simple estimator for thermodynamic length, thermodynamic states are initialized at approximately equal intervals. The method is demonstrated on the Astex diverse set, a database of 85 protein-ligand complexes relevant to pharmacy or agriculture. Fifteen independent simulations of each complex were started using poses from crystallography, docking, or the lowest-energy pose observed in the other simulations. Benchmark simulations completed within three days on a single processor. Overall, protocols initialized using the thermodynamic length estimator were system-specific, robust, and led to approximately even replica exchange acceptance probabilities between neighboring states. In most systems, the standard deviation of the BPMF converges to within 5 kT . Even with low variance, however, the mean BPMF was sometimes dependent on starting conditions, implying inadequate sampling. Within the thermodynamic cycle, free energies estimated based on multiple intermediate states were more precise, and those estimated by single-step perturbation were less precise. The results demonstrate that the method is promising, but that ligand pose sampling and phase space overlap can sometimes prevent precise BPMF estimation. The software used to perform these calculations, Alchemical Grid Dock (AlGDock), is available under the open-source MIT license at URL
Alchemical Grid Dock (AlGDock) is open-source software designed to compute the binding potential of mean force (BPMF) - the binding free energy between a flexible ligand and a rigid receptor - for a URLanic ligand and a biological macromolecule. Multiple BPMFs can be used to rigorously compute binding affinities between flexible partners. AlGDock uses replica exchange between thermodynamic states at different temperatures and receptor-ligand interaction strengths. Receptor-ligand interaction energies are represented by interpolating precomputed grids. Thermodynamic states are adaptively initialized and adjusted on-the-fly to maintain replica exchange rates. In demonstrative calculations, when the bound ligand is treated as fully solvated, AlGDock estimates BPMFs with a precision within 4 kT in 65\% and within 8 kT for 91\% of systems. It correctly identifies the native binding pose in 83\% of simulations. Performance is sometimes limited by subtle differences in the important configuration space of sampled and targeted thermodynamic states.
R
A
Alchemical Grid Dock (AlGDock) is open-source software designed to compute the
R
is a free energy of noncovalent association in which one binding partner is flexible and the other is rigid . I have developed a method to calculate BPMFs for protein-ligand systems. The method is based on replica exchange sampling from multiple
- the binding free energy between a flexible ligand and a rigid receptor - for a URLanic ligand and a biological macromolecule. Multiple BPMFs can be used to rigorously compute binding affinities between flexible partners. AlGDock uses replica exchange between
R
protein-ligand
receptor-ligand
R
Protein-ligand interactions
Receptor-ligand interaction energies
R
electrostatic and van der Waals grids. Using a simple estimator for thermodynamic length, thermodynamic states are initialized at approximately equal intervals. The method is demonstrated on the Astex diverse set, a database of 85 protein-ligand complexes relevant to pharmacy or agriculture. Fifteen independent simulations of each complex were started using poses from crystallography, docking, or the lowest-energy pose observed in the other simulations. Benchmark simulations completed within three days on a single processor. Overall, protocols initialized using the thermodynamic length estimator were system-specific, robust, and led to approximately even replica exchange acceptance probabilities between neighboring states. In most systems, the standard deviation of the BPMF converges to within 5 kT . Even with low variance, however, the mean BPMF was sometimes dependent on starting conditions, implying inadequate sampling. Within the thermodynamic cycle, free energies estimated based on multiple intermediate states were more precise, and those estimated by single-step perturbation were less precise. The results demonstrate that the method is promising, but that ligand pose sampling and phase space overlap can sometimes prevent precise BPMF estimation. The software used to perform these calculations, Alchemical Grid Dock (AlGDock), is available under the open-source MIT license at URL
grids. Thermodynamic states are adaptively initialized and adjusted on-the-fly to maintain replica exchange rates. In demonstrative calculations, when the bound ligand is treated as fully solvated, AlGDock estimates BPMFs with a precision within 4 kT in 65\% and within 8 kT for 91\% of systems. It correctly identifies the native binding pose in 83\% of simulations. Performance is sometimes limited by subtle differences in the important configuration space of sampled and targeted thermodynamic states.