Skip to end of metadata
Go to start of metadata
You are viewing an old version of this page. View the current version.
Compare with Current
View Page History
Version 1
Current »
Participants
Goals
Review OpenFF compute resources with Chapin
Review QCA datasets with Chapin
Discuss feasibility of future peptide datasets
Discussion topics
Item | Notes |
|---|
Compute resources | What are OpenFF’s available compute resources? Are there shared allocations on e.g. XSEDE or is everything run on local/institutional resources? For shared resources, what is the process for approving for QM calculations?
|
Status of peptide datasets | Peptide unconstrained Optimization dataset. Looks like 6689/6709 complete from this PR. Peptide TorsionDrive dataset. Looks like 823/845 complete from this PR. PEPCONF dataset. Looks like 2892/7560 complete from this PR. Is there documentation on how the conformations were chosen for Dave Cerutti’s datasets? Are we planning to troubleshoot errored calculations or are these datasets complete enough as is?
|
Expense of QC datasets
| What is the expected cost (in wall time or core-hours) of each conformation in an Optimization dataset and a 1-D TorsionDrive dataset? How does cost scale with number of atoms or electrons? How do you decide the number of conformations per molecule? What is the cost of a 2-D TorsionDrive? Is a 2-D TorsionDrive with spacing N-by-N equivalent to N 1-D TorsionDrives with spacing N? What is the expected cost of including an implicit solvent model, e.g. PCM?
|
Feasibility of peptide datasets | 20 canonical amino acids + 7 alternate protonation/tautomers 1-D TorsionDrives of backbone torsions and χ1 for all dipeptides 1-D TorsionDrives of backbone torsions and χ1 for subset of Ace-X-Y-Z-Nme tetrapeptides 2-D TorsionDrives of backbone torsions for subset of dipeptides
|
Action items
Decisions
0 Comments