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example demonstrating a free energy estimation starting from OFF and OpenMM

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mmpbsa_from_openmm

example demonstrating a free energy estimate starting from OpenFoceField-parameterized ligands and using an OpenMM-derived trajectory.

file prep:

see files in openmm_simulation dir.

  • process the PDB file with openmm-setup (1XEP - catechol bound to T4 lysozyme)
  • in align_ligand.ipynb, generate an RDKit mol object that is aligned with the crystal structure ligand
  • in parameterize_ligand.ipynb, use OpenForceField to parameterize this mol object
  • in combine_systems.ipynb, add the parameterized ligand to the system and save a copy as *.parm7

You now have a .parm7 file called complex_plus_water.parm7. There will also be complex_system.xml, which is an openmm System object that can be fed into a Simulation to make a trajectory. Thus we have the building blocks for an MMPBSA run using CaFE in VMD/NAMD2.

generate a trajectory

  • in the topmost directory, see generate_trajectory.ipynb to generate a 5ns trajectory using OpenMM

analyse

  • run VMD script (vmd -dispdev text < analyse.tcl > out.log), having installed APBS, NAMD2 and CaFE plugin (~40mins)

results

result

The free energy estimate was -6.1105 kcal/mol with SD 2.5155. By my calculations that's an IC50 of around 50 micromolar. The errorbars are unequal because I am assuming the error is normally distributed around the mean affinity value, which gets distorted when exponentiated to get IC50. This is at least an order of magnitude off, if you consider catechol has low millimolar or high micromolar binding affinity (see Mobley, Chodera, Dill 10.1063/1.2221683).

Crystal structures of catechol bound to T4 lysozyme show two possible binding modes, so correctly sampling these might improve the calculation (https://doi.org/10.1021/jm0491187). Also, I assumed 250 statistically independent samples and only sampled for a small time (5ns). It may be safer to do some block averaging here, or increase the time between samples (i.e. the DCD stride), since 20ps between samples doesn't sound like enough to decorrelate. Ultimately, though, MMPBSA is an approximate method so we don't expect to be super close to the absolute values. Instead, it is more applicable to relative affinity calculations (not shown here).

Assuming a true 1uM binding affinity, current estimate is about 1.8kcal/mol too high.

tidbits

  • CaFE can be installed by cloning the CaFE repo at https://github.com/HuiLiuCode/CaFE_Plugin, then changing the name of the src dir within to cafe1.0. To let VMD know where this directory is, add this line to your ~/.vmdrc file (change the actual filepath to your own computer): set auto_path [linsert $auto_path 0 {/home/lewis/Documents/cafe/cafe1.0}]
  • Test if CaFE runs by opening vmd and typing package require cafe 1.0
  • You will need to install APBS and add it to the PATH so it can be called from within CaFE
  • APBS is offered as a binary and, to run it, you will need to add the lib dir within the APBS directory to the LD_LIBRARY_PATH as well
  • Likewise you need to install namd2 and add it to the PATH
  • CaFE script uses the defaults from the manual. Up to you whether that applies in every case.
  • APBS takes a long time to run even with 8CPUs. 250 frames took 40 minutes.

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example demonstrating a free energy estimation starting from OFF and OpenMM

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