Attendees:
Eastwood
Wang
Wagner
Mobley
Cavender
Gokey
Gilson
Finlay Clark: Protein-ligand binding free energies
PhD project: absolute binding free energies
a3fe:
Github link macro link https://github.com/michellab/a3fe automatically selects restraints which maximally restrict configurational space
tends to find stable residues and relevant protein-ligand interaction points
has some magic to pick which lambda windows to sample more and which to sample less
aside: Gelman-Rubin (Stat. Sci. 1992) helped to identify sampling issues in some lambda windows
also some work on “robust truncation point selection”
Github link macro link https://github.com/fjclark/red
MG: What are the error bars in slide 31?
FC: Errors of errors, from bootstrapping
J Clark: What about bimodal distribution?
FC: Probably picking a local minima in very messy data. Hard to work around data that’s so noisy that the autocovariance function is itself noisy
J Clark: Do you ever detect a second equilibration time?
FC: Can never really detect that
MG:
We don’t do any subsampling ebfore we estimate free energy. could sue that for bootstrapping, but we don’t do that now.
MG – Slide 31, second case. PDE2a blue curse shows initial bias dropping off quickly. Why doesn’t autocorrelation tell you that bias decayed off in 3ns? Why would it push you beyond that?
FC – We had an informative example where we ran this with no bias, and found that it discarded a lot of the sample. … A lot of this is because, if there’s a local minimum at the end of your data, then that will heavily affect the metrics of convergence/truncation time.
JW – Plans for future communications? Newcastle meeting will connect OpenFF and FClark. What’s a good way to keep in touch with OpenFE?
DC – Good Q. Will start getting involved in alchemiscale as well as a bridge to OpenFE
Hannah Turney: Formulations
Collaboration with J&J
Excipients are compounds that are not the active drug but are important for delivery etc
Polymer structure & properties affect drug delivery behavior
Built
for automating polymer building with a bunch of knobsGithub link macro link https://github.com/matta-research-group/SwiftPol Did a case study in PLGA
Software bottlenecks in “molecule” (polymer) handling makes OpenFF intractable to use
JW: Software bottleneck is something OpenFF team should handle. Your workaround is probably something we shouldn’t need to do
DC: Interested in Espaloma result
MT – I see NAGL agrees better with AM1BCC than espaloma. But is there an experimental definition of “correct” that we can compare to?
HT – Right, this is just an early exploration.
MG: These charges look surprising to me, I’d expect carbonyl charges to be <1
JW: Long-term, what sort of systems are you building? Put a ligand in a box with polymers …. what do you want to work toward?
HT - Will look at diffusivity, solubility, properties of the drug molecule. And look at “points of hydrolysis” points on polymers in which polymers break down. Build a broken-down polymer and see how much differently the API behaves
JW: Do we think our force fields will handle these crazy chemistries well (i.e. low pH of stomach acid).
MG: The idea seems to be to model the effect of the break down, not the process.
HT: Yes
MG (+ others): Would expect the force fields to do a good job. Haven’t looked at it specifically.
CC: How are you building these systems? Packmol?
HT – Polyply, requires GROMACS inputs, but interchange gets me those. Coudl be used for other purposes but would introduce a gromacs dependency.
Github link macro link https://github.com/marrink-lab/polyply_1.0
MT – Polyply could be a good thing to investigate for packing in general, mabe could get folded into an example if it works well
J Clark: How you control the tacticity? Can you control tacticity wrt to different copolymer components
HT: This is an input into swiftpol
MRS: context for polymer discussion (since I’ll be teaching)
MuPT - funded collaboration for general tools for setting up polymer simulations
This covering all soft materials (including handling both CG and AA), but definitely includes polymer/protein interactions. Relevant touchpoints with OpenFF.
Box of proteins + polymers
Crosslinked proteins/polymers (PEGylation, attaching fatty acids)
Glycoproteins
Bringing in PDBs from however they are generated and parameterizing
Turley/Matta formulations project also shows utility of polymers in drug design
We want to support non-OpenFF force fields as well, via Foyer
A lot of these MuPT needs overlap with tool requirements for OpenFF. Proteins/nucleic acids/glycoproteins are a subset of polymers . . . What are those overlaps/opportunities for shared tooling? DISCUSS!