Add LIPID MAPS fragment optimization dataset (#394)

* OpenFF Lipid Optimization Training Supplement v1.0

* update main readme

* update elements

README.md

@@ -276,6 +276,8 @@ These are currently used to find a minimum energy conformation of a molecule.
 |`OpenFF Iodine Fragment Opt v1.0` | [2024-09-10-OpenFF-Iodine-Fragment-Opt-v1.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-09-10-OpenFF-Iodine-Fragment-Opt-v1.0) | B3LYP-D3BJ/DZVP optimized conformers for a variety of I-containing fragment molecules | C, O, I, S, F, Br, Cl, N, H ||
 | `OpenFF Sulfur Optimization Training Coverage Supplement v1.0` | [2024-09-11-OpenFF-Sulfur-Optimization-Training-Coverage-Supplement-v1.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-09-11-OpenFF-Sulfur-Optimization-Training-Coverage-Supplement-v1.0) | Additional optimization training data for Sage sulfur and phosphorus parameters | C, S, F, O, H, Cl, Br, P, N | |
 | `OpenFF Sulfur Optimization Benchmarking Coverage Supplement v1.0` | [2024-09-18-OpenFF-Sulfur-Optimization-Benchmarking-Coverage-Supplement-v1.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-09-18-OpenFF-Sulfur-Optimization-Benchmarking-Coverage-Supplement-v1.0) | Additional optimization benchmarking data for Sage sulfur and phosphorus parameters | S, P, Cl, C, N, O, H, Br, F | |
+| `OpenFF Lipid Optimization Training Supplement v1.0` | [2024-10-08-OpenFF-Lipid-Optimization-Training-Supplement-v1.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-10-08-OpenFF-Lipid-Optimization-Training-Supplement-v1.0) | Additional optimization training data for Sage from representative LIPID MAPS fragments | I, Br, O, H, P, C, N, Cl, F, S | |
+
 
 # TorsionDrive Datasets
 These are currently used perform a complete rotation of one or more selected bonds, where optimizations are performed over a discrete set of angles.

submissions/2024-10-08-OpenFF-Lipid-Optimization-Training-Supplement-v1.0/README.md

@@ -0,0 +1,67 @@
+# OpenFF Lipid Optimization Training Supplement v1.0
+
+## Description
+
+An optimization data set created to improve the training coverage of lipid-like
+molecules in Sage. The molecules in this data set were selected from the [LIPID
+MAPS](https://www.lipidmaps.org/) database via
+[cura](https://github.com/ntBre/curato/tree/6039bea5c64f8cd6b374fd12b5fa3b355898d98b)
+after being fragmented by the [XFF
+fragmentation](https://github.com/XtalPi-XFF/2023_XFF_paper/tree/b84ef6079d24ebd2e86f78a495e3257b375255fa/fragmentation)
+algorithm, clustered on the 2048-bit, radius-3 Morgan fingerprint from RDKit by
+the `LeaderPicker.LazyBitVectorPick` algorithm, also from RDKit, with a distance
+threshold of 0.6559. Placeholder dummy atoms in the fragments were generally
+filled with H atoms, and `S(=O)(=O)*` groups were replaced with `S(=O)([O-])`.
+The candidate fragments were further restricted to those with between 3 and 70
+heavy atoms and containing only the elements Cl, P, Br, I, H, C, O, N, F, and S.
+Candidates with InChIKeys matching existing Sage training or benchmarking data
+were also filtered out.
+
+## General Information
+
+* Date: 2024-10-08
+* Class: OpenFF Optimization Dataset
+* Purpose: Improve training coverage in Sage
+* Name: OpenFF Lipid Optimization Training Supplement v1.0
+* Number of unique molecules: 3971
+* Number of filtered molecules: 32
+* Number of conformers: 29770
+* Number of conformers per molecule (min, mean, max): 1, 7.50, 10
+* Mean molecular weight: 291.73
+* Max molecular weight: 1016.29
+* Charges: -4.0, -1.0, 0.0, 1.0
+* Dataset submitter: Brent Westbrook
+* Dataset generator: Brent Westbrook
+
+## QCSubmit Generation Pipeline
+
+* `generate-dataset.py`: This script shows how the dataset was prepared from the input file `input.smi`.
+* `main.py`: This script shows how the dataset was prepared from the initial cura database.
+* `inchis.dat`: The list of InChIKeys present in existing Sage training and
+  benchmarking data, used by `main.py`.
+
+## QCSubmit Manifest
+
+* `generate-dataset.py`: Script describing dataset generation and submission
+* `input-environment.yaml`: Environment file used to create the Python environment for the script
+* `full-environment.yaml`: Fully-resolved environment used to execute the script
+* `opt.toml`: Experimental [qcaide](https://github.com/ntBre/qcaide) input file for defining
+variables used throughout the QCA submission process
+* `dataset.json.bz2`: Compressed dataset ready for submission
+* `dataset.pdf`: Visualization of dataset molecules
+* `output.smi`: SMILES strings for dataset molecules
+
+## Metadata
+* Elements: {I, Br, O, H, P, C, N, Cl, F, S}
+* Spec: default
+	* basis: DZVP
+	* implicit_solvent: None
+	* keywords: {}
+	* maxiter: 200
+	* method: B3LYP-D3BJ
+	* program: psi4
+	* SCF properties:
+		* dipole
+		* quadrupole
+		* wiberg_lowdin_indices
+		* mayer_indices

submissions/2024-10-08-OpenFF-Lipid-Optimization-Training-Supplement-v1.0/full-environment.yaml

@@ -0,0 +1,306 @@
+name: qcarchive-user-submit
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+  - conda-forge
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+  - xorg-libxdmcp=1.1.3=h7f98852_0
+  - xorg-libxext=1.3.4=h0b41bf4_2
+  - xorg-libxrender=0.9.11=hd590300_0
+  - xorg-libxt=1.3.0=hd590300_1
+  - xorg-renderproto=0.11.1=h7f98852_1002
+  - xorg-xextproto=7.3.0=h0b41bf4_1003
+  - xorg-xproto=7.0.31=h7f98852_1007
+  - xz=5.2.6=h166bdaf_0
+  - yaml=0.2.5=h7f98852_2
+  - zeromq=4.3.5=h59595ed_0
+  - zipp=3.17.0=pyhd8ed1ab_0
+  - zlib=1.2.13=hd590300_5
+  - zlib-ng=2.0.7=h0b41bf4_0
+  - zstandard=0.22.0=py311haa97af0_0
+  - zstd=1.5.5=hfc55251_0
+  - pip:
+      - amberutils==21.0
+      - edgembar==0.2
+      - mmpbsa-py==16.0
+      - packmol-memgen==2023.2.24
+      - pdb4amber==22.0
+      - pymsmt==22.0
+      - pytraj==2.0.6
+      - sander==22.0
+prefix: /home/brent/mambaforge/envs/qcarchive-user-submit