diff --git a/README.md b/README.md
index 73eae828..37cb075a 100644
--- a/README.md
+++ b/README.md
@@ -35,6 +35,9 @@ Datasets must be submitted as pull requests.
     conda env create -f qca-dataset-submission/devtools/prod-envs/qcarchive-user-submit.yaml
     conda activate qcarchive-user-submit
     ```
+   You may also need to install OpenEye:\
+   `conda install -c openeye openeye-toolkits`
+
 
 
 4. Choose a starting notebook and README based on the type of dataset you wish to submit:
@@ -202,6 +205,10 @@ The status only refers to the `default` specification which is required for all
 
 [![Running](https://img.shields.io/badge/Status-Running-orange)](https://img.shields.io/badge/Status-Running-orange)  the dataset is currently running and may have some incomplete jobs.
 
+# Forcefield Release Datasets
+| Forcefield  | Repo  | Optimization | Torsion Drive | Elements | Zenodo |
+|-------------|----------|-------------------|--------------------|----------|--------|
+| Release OpenFF 2.0.0 Sage | [openff-sage](https://github.com/openforcefield/openff-sage)  | [2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0) | [Coming Soon]() | H, C, N, O, S, P, F, Cl, Br, I  | [Coming Soon]() |
 
 
 # Basic Datasets
diff --git a/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/README.md b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/README.md
new file mode 100644
index 00000000..989b45e0
--- /dev/null
+++ b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/README.md
@@ -0,0 +1,69 @@
+# OpenFF Sage 2.0.0 Training Optimization v1.0
+
+### Description
+
+A quantum chemical (QC) dataset curated to train [OpenFF 2.0.0 Sage](https://github.com/openforcefield/openff-sage) forcefield, with reparametrized Lennard-Jones (LJ) and valence parameters, the latter relevant to this dataset. This QC dataset with the OpenFF default level of theory, B3LYP-D3BJ/DZVP, is used to benchmark Sage geometries and energetics. These optimized conformer geometries where used in conjunction with the QC dataset used to train one dimensional torsional profiles. This Generation 2 dataset increases chemical diversity when compared to Generation 1, which are of value to our industry partners. Large molecules (>20 heavy atoms) were also included, including more flexible molecules and a greater degree of conformational variation which provide intramolecular interactions.
+
+This is the complete optimization dataset used for training OpenFF 2.0.0 Sage, consisting of the following datasets:
+
+ - [OpenFF Gen 2 Opt Set 1 Roche](https://github.com/openforcefield/qca-dataset-submission/tree/0e6e6da930118e2a2d6402b93c3e3e93830600cc/submissions/2020-03-20-OpenFF-Gen-2-Optimization-Set-1-Roche)
+ - [OpenFF Gen 2 Opt Set 2 Coverage](https://github.com/openforcefield/qca-dataset-submission/tree/0e6e6da930118e2a2d6402b93c3e3e93830600cc/submissions/2020-03-20-OpenFF-Gen-2-Optimization-Set-2-Coverage)
+ - [OpenFF Gen 2 Opt Set 3 Pfizer Discrepancy](https://github.com/openforcefield/qca-dataset-submission/tree/0e6e6da930118e2a2d6402b93c3e3e93830600cc/submissions/2020-03-20-OpenFF-Gen-2-Optimization-Set-3-Pfizer-Discrepancy)
+ - [OpenFF Gen 2 Opt Set 4 eMolecules  - Discrepancy](https://github.com/openforcefield/qca-dataset-submission/tree/0e6e6da930118e2a2d6402b93c3e3e93830600cc/submissions/2020-03-20-OpenFF-Gen-2-Optimization-Set-4-eMolecules-Discrepancy)
+ - [OpenFF Gen 2 Opt Set 5 Bayer](https://github.com/openforcefield/qca-dataset-submission/tree/0e6e6da930118e2a2d6402b93c3e3e93830600cc/submissions/2020-03-20-OpenFF-Gen-2-Optimization-Set-5-Bayer)
+
+The following filters were applied to those datasets:
+
+ - `RecordStatusFilter(status=RecordStatusEnum.complete)`
+ - `ConnectivityFilter(tolerance=1.2)`
+ - `UndefinedStereoFilter()`
+ - `ElementFilter(allowed_elements=["H", "C", "N", "O", "S", "P", "F", "Cl", "Br", "I"])`
+ - `ConformerRMSDFilter(max_conformers=10)`
+
+ Further information can be found in the curation scripts for the linked repositories.
+
+### General Information
+
+- Date: 2024-12-12
+- Class: OpenFF Optimization Dataset
+- Purpose: Complete set of training data for OpenFF 2.0.0 Sage
+- Dataset Type: optimization
+- Name: OpenFF Sage 2.0.0 Training Optimization Dataset v1.0
+- Number of unique molecules:   1025
+- Number of filtered molecules: 0 
+- Number of conformers:         3663
+- Number of conformers (min mean max): 1.00, 3.53, 10.00
+- Mean molecular weight: 261.38
+- Max molecular weight: 544.64
+- Set of charges: -2.0, -1.0, 0.0, 1.0
+- Dataset Submitter: Jennifer A. Clark
+- Dataset Curator: Simon Boothroyd
+- Dataset Generator: Hyesu Jang
+
+### QCSubmit generation pipeline
+
+- `generate-combined-dataset.py`: A python script which shows how the dataset was prepared from the input files.
+- `output.txt`: A text file containing the printed output of `generate-combined-dataset.py`.
+
+### QCSubmit Manifest
+
+- `generate-combined-dataset.py`
+- `dataset.json.bz2`: The basic dataset ready for submission.
+- `dataset.pdf`: A pdf file containing molecule 2D structures.
+- `dataset.smi`: SMILES for every molecule in the submission.
+ 
+### Metadata
+
+* Elements: {F, I, N, C, P, Cl, S, Br, O, H}
+* QC Specifications: default
+  * basis: DZVP
+  * implicit_solvent: None
+  * keywords: {}
+  * maxiter: 200
+  * method: B3LYP-D3BJ
+  * program: psi4
+  * SCF Properties:
+    * dipole
+    * quadrupole
+    * wiberg_lowdin_indices
+    * mayer_indices
\ No newline at end of file
diff --git a/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/conda_env.yml b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/conda_env.yml
new file mode 100644
index 00000000..362e5f1a
--- /dev/null
+++ b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/conda_env.yml
@@ -0,0 +1,161 @@
+name: qcarchive-user-submit
+channels:
+- conda-forge
+- openeye
+dependencies:
+- annotated-types=0.7.0=pyhd8ed1ab_1
+- apsw=3.47.0.0=py311hde754ab_0
+- argcomplete=3.5.2=pyhd8ed1ab_0
+- attrs=24.2.0=pyh71513ae_1
+- basis_set_exchange=0.10=pyhd8ed1ab_1
+- brotli=1.1.0=hd74edd7_2
+- brotli-bin=1.1.0=hd74edd7_2
+- brotli-python=1.1.0=py311h3f08180_2
+- bson=0.5.9=py_0
+- bzip2=1.0.8=h99b78c6_7
+- ca-certificates=2024.8.30=hf0a4a13_0
+- cached-property=1.5.2=hd8ed1ab_1
+- cached_property=1.5.2=pyha770c72_1
+- cachetools=5.5.0=pyhd8ed1ab_1
+- cairo=1.18.2=h6a3b0d2_1
+- certifi=2024.8.30=pyhd8ed1ab_0
+- cffi=1.17.1=py311h3a79f62_0
+- chardet=5.2.0=py311h267d04e_2
+- charset-normalizer=3.4.0=pyhd8ed1ab_1
+- colorama=0.4.6=pyhd8ed1ab_1
+- contourpy=1.3.1=py311h210dab8_0
+- cycler=0.12.1=pyhd8ed1ab_1
+- dill=0.3.9=pyhd8ed1ab_1
+- exceptiongroup=1.2.2=pyhd8ed1ab_1
+- font-ttf-dejavu-sans-mono=2.37=hab24e00_0
+- font-ttf-inconsolata=3.000=h77eed37_0
+- font-ttf-source-code-pro=2.038=h77eed37_0
+- font-ttf-ubuntu=0.83=h77eed37_3
+- fontconfig=2.15.0=h1383a14_1
+- fonts-conda-ecosystem=1=0
+- fonts-conda-forge=1=0
+- fonttools=4.55.3=py311h4921393_0
+- freetype=2.12.1=hadb7bae_2
+- freetype-py=2.3.0=pyhd8ed1ab_0
+- greenlet=3.1.1=py311h3f08180_0
+- h2=4.1.0=pyhd8ed1ab_1
+- hpack=4.0.0=pyhd8ed1ab_1
+- hyperframe=6.0.1=pyhd8ed1ab_1
+- icu=75.1=hfee45f7_0
+- idna=3.10=pyhd8ed1ab_1
+- importlib-metadata=8.5.0=pyha770c72_1
+- importlib_resources=6.4.5=pyhd8ed1ab_1
+- iniconfig=2.0.0=pyhd8ed1ab_1
+- jsonschema=4.23.0=pyhd8ed1ab_1
+- jsonschema-specifications=2024.10.1=pyhd8ed1ab_1
+- kiwisolver=1.4.7=py311h2c37856_0
+- krb5=1.21.3=h237132a_0
+- lcms2=2.16=ha0e7c42_0
+- lerc=4.0.0=h9a09cb3_0
+- libblas=3.9.0=25_osxarm64_openblas
+- libboost=1.84.0=hc9fb7c5_7
+- libboost-python=1.84.0=py311h8fc16d6_7
+- libbrotlicommon=1.1.0=hd74edd7_2
+- libbrotlidec=1.1.0=hd74edd7_2
+- libbrotlienc=1.1.0=hd74edd7_2
+- libcblas=3.9.0=25_osxarm64_openblas
+- libcxx=19.1.5=ha82da77_0
+- libdeflate=1.22=hd74edd7_0
+- libedit=3.1.20191231=hc8eb9b7_2
+- libexpat=2.6.4=h286801f_0
+- libffi=3.4.2=h3422bc3_5
+- libgfortran=5.0.0=13_2_0_hd922786_3
+- libgfortran5=13.2.0=hf226fd6_3
+- libglib=2.82.2=h07bd6cf_0
+- libiconv=1.17=h0d3ecfb_2
+- libintl=0.22.5=h8414b35_3
+- libjpeg-turbo=3.0.0=hb547adb_1
+- liblapack=3.9.0=25_osxarm64_openblas
+- liblzma=5.6.3=h39f12f2_1
+- libopenblas=0.3.28=openmp_hf332438_1
+- libpng=1.6.44=hc14010f_0
+- libpq=16.6=hb008251_1
+- librdkit=2024.03.5=h54a62e4_3
+- libsqlite=3.47.0=hbaaea75_1
+- libtiff=4.7.0=ha962b0a_2
+- libwebp-base=1.4.0=h93a5062_0
+- libxcb=1.17.0=hdb1d25a_0
+- libzlib=1.3.1=h8359307_2
+- llvm-openmp=19.1.5=hdb05f8b_0
+- matplotlib-base=3.9.3=py311h031da69_0
+- msgpack-python=1.1.0=py311h2c37856_0
+- multiprocess=0.70.17=py311h917b07b_1
+- munkres=1.1.4=pyh9f0ad1d_0
+- ncurses=6.5=h7bae524_1
+- networkx=3.4.2=pyh267e887_2
+- numpy=1.26.4=py311h7125741_0
+- openeye-toolkits=2024.2.0=py311_0
+- openff-amber-ff-ports=0.0.4=pyhca7485f_0
+- openff-forcefields=2024.09.0=pyhff2d567_0
+- openff-qcsubmit=0.54.0=pyhd8ed1ab_0
+- openff-toolkit-base=0.16.7=pyhd8ed1ab_0
+- openff-units=0.2.2=pyhca7485f_0
+- openff-utilities=0.1.13=pyhd8ed1ab_0
+- openjpeg=2.5.3=h8a3d83b_0
+- openssl=3.4.0=h39f12f2_0
+- packaging=24.2=pyhd8ed1ab_2
+- pandas=2.2.2=py311h4b4568b_1
+- pcre2=10.44=h297a79d_2
+- pillow=11.0.0=py311h3894ae9_0
+- pint=0.23=pyhd8ed1ab_1
+- pip=24.3.1=pyh8b19718_0
+- pixman=0.44.2=h2f9eb0b_0
+- pkgutil-resolve-name=1.3.10=pyhd8ed1ab_2
+- pluggy=1.5.0=pyhd8ed1ab_1
+- pthread-stubs=0.4=hd74edd7_1002
+- pycairo=1.27.0=py311h84a5a08_0
+- pycalverter=1.6.1=pyhd8ed1ab_1
+- pycparser=2.22=pyh29332c3_1
+- pydantic=2.10.3=pyh3cfb1c2_0
+- pydantic-core=2.27.1=py311h3ff9189_0
+- pyjwt=2.10.1=pyhd8ed1ab_0
+- pyparsing=3.2.0=pyhd8ed1ab_2
+- pysocks=1.7.1=pyha55dd90_7
+- pytest=8.3.4=pyhd8ed1ab_1
+- python=3.11.11=hc22306f_1_cpython
+- python-constraint=1.4.0=py_0
+- python-dateutil=2.9.0.post0=pyhff2d567_1
+- python-tzdata=2024.2=pyhd8ed1ab_1
+- python_abi=3.11=5_cp311
+- pytz=2024.2=pyhd8ed1ab_1
+- pyyaml=6.0.2=py311h460d6c5_1
+- qcelemental=0.28.0=pyhd8ed1ab_1
+- qcportal=0.56=pyhd8ed1ab_1
+- qhull=2020.2=h420ef59_5
+- rdkit=2024.03.5=py311h8a4e316_3
+- readline=8.2=h92ec313_1
+- referencing=0.35.1=pyhd8ed1ab_1
+- regex=2024.11.6=py311h917b07b_0
+- reportlab=4.2.5=py311h460d6c5_0
+- requests=2.32.3=pyhd8ed1ab_1
+- rlpycairo=0.2.0=pyhd8ed1ab_0
+- rpds-py=0.22.3=py311h3ff9189_0
+- setuptools=75.6.0=pyhff2d567_1
+- six=1.17.0=pyhd8ed1ab_0
+- smirnoff99frosst=1.1.0=pyh44b312d_0
+- sqlalchemy=2.0.36=py311hae2e1ce_0
+- sqlite=3.47.0=hcd14bea_1
+- tabulate=0.9.0=pyhd8ed1ab_2
+- tk=8.6.13=h5083fa2_1
+- tomli=2.2.1=pyhd8ed1ab_1
+- tqdm=4.67.1=pyhd8ed1ab_0
+- typing-extensions=4.12.2=hd8ed1ab_1
+- typing_extensions=4.12.2=pyha770c72_1
+- tzdata=2024b=hc8b5060_0
+- unicodedata2=15.1.0=py311hae2e1ce_1
+- unidecode=1.3.8=pyh29332c3_1
+- urllib3=2.2.3=pyhd8ed1ab_1
+- wheel=0.45.1=pyhd8ed1ab_1
+- xmltodict=0.14.2=pyhd8ed1ab_1
+- xorg-libxau=1.0.11=hd74edd7_1
+- xorg-libxdmcp=1.1.5=hd74edd7_0
+- yaml=0.2.5=h3422bc3_2
+- zipp=3.21.0=pyhd8ed1ab_1
+- zstandard=0.23.0=py311ha60cc69_1
+- zstd=1.5.6=hb46c0d2_0
+
diff --git a/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/dataset.json.bz2 b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/dataset.json.bz2
new file mode 100644
index 00000000..5672e648
--- /dev/null
+++ b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/dataset.json.bz2
@@ -0,0 +1,3 @@
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+oid sha256:165105359234746b9c5bcae522f70405b4bfa4586fdb9afd372f0f90f6913145
+size 1972763
diff --git a/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/dataset.pdf b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/dataset.pdf
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diff --git a/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/dataset.smi b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/dataset.smi
new file mode 100644
index 00000000..5a67bfa9
--- /dev/null
+++ b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/dataset.smi
@@ -0,0 +1,1039 @@
+CN1C(=O)C=CC=C1c2ccccc2OC
+C1CN(CC[NH2+]1)CC2=CC=CNC2=O
+CC(C)S(=O)(=O)C1=CC=CS1
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+[C@@](C(F)(F)Br)(F)(Cl)Br
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+Cc1ccccc1[C@H]2CCCN2C(=O)C
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+Cc1cnc2ccccc2c1N3CCCCC3
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+CC(=O)C1=CNc2c1c(ncc2Br)Br
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+COc1c(cccc1N)C(=O)OC
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+COC(=O)c1c(ccc2c1C=NN2)Br
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+CC(=O)N1C=C(c2c1cccc2)[C@H]3CCN3
+CC1=C(C(=NN1CC2=C(ON=C2C)C)C)[N+](=O)[O-]
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+c1c(cnc(n1)C2(CC2)C#N)Br
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+COc1ccc(c(c1)OC)/C(=N/O)/N
+CC1=CSC(=N1)Sc2ccc(cc2)F
+c1ccc(c(c1)[C@H]2COC(=O)N2)[N+](=O)[O-]
+CC1(CC1)c2cc(ccn2)Cl
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+c1cnc(c(n1)C=O)Br
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+c1cc(cc(c1)Br)C/C(=N\O)/N
+CCNCC1=CC(=C(S1)C)Br
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+CN1N=C(C(=N1)Br)C(=O)OC
+c1cc2c(cc1Br)C(=CN2)[C@@H]3CCN3
+C[N@]1C[C@@H]2CC[C@H](C1)[N@@](C2)CC3=CC=C(O3)c4ccccc4C#N
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+CC1=CC(=C(N1C)C)C(=O)CN2C(=O)c3ccccc3S2(=O)=O
+c1ccc(c(c1)C/C(=N\O)/N)Cl
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+CC1=C(SC=C1)[C@H](C)N
+Cc1cc(ccc1Br)C(=O)Nc2ccccc2
+Cc1ccccc1C2=NOC(=N2)/C(=C/c3ccc(cc3)C#N)/C#N
+c1ccnc(c1)C(=O)Cc2ccnc(c2)Br
+c1ccc2c(c1)cccc2/N=C\C3=C(c4ccccc4S3)O
+c1ccc2c(c1)c(ccc2O)[C@H]3CCN3
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+Cc1cc(cnc1Nc2ccccc2)/C=N/O
+C[C@H]1CN(CC[C@]1(C)O)C(=O)CN2C(=O)c3ccccc3N2
+c1c(c(ncn1)Cl)CO
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+CC1=NN(C(=C1/C=N/N2CCOCC2)Cl)c3ccccc3Cl
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+c1cc2cccnc2c(c1)C(=O)N/N=C\3/CCN4C3=CC=C4
+c1ccc2c(c1)C(=NS2(=O)=O)N/N=C/c3cc4c(cc3Cl)OCO4
+c1cc(cc(c1)Br)/C(=N/O)/N
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+CC(=O)C1=CNc2c1c(cnc2)C(=O)O
+C1CC2(CCOCC2)NC1
+C1=C(C(=C(S1)CN)Br)Br
+Cc1c(nc(nn1)N/N=C/c2cccc3c2cccc3)O
+c1cc(c(c(c1)Cl)O)[C@@H]2CCN2
+Cc1cccc2c1NC=C2/C(=N/O)/N
+c1ccc(cc1)/C=C\S(=O)(=O)c2ccc(c(c2)Cl)Cl
+c1cc(cc(c1)F)C/C(=N\O)/N
+C/C(=N/O)/c1ccc(c(c1)Cl)Cl
+c1c(cc(c(c1[C@H]2CCN2)Cl)Cl)Cl
+c1cc2c(cc1F)c(cc(n2)CN3CC(C3)N4CCOCC4)O
+C1CNCCC1N2CC(C2)(F)F
+c1cc(c(c(c1F)[C@@H]2CCN2)F)F
+c1cc2c(cc(nc2c(c1)F)CN3CC(C3)c4cccnc4)O
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+c1cc(cc(c1)I)[C@@H]2CCN2
+C1CC1CC(=O)N2CCC3(CC2)COC3
+C1C(CN1)N2CC(C2)F
+CN(C)C(=O)CN1CC2(C1)CCCO2
+CC1=C(OC(=C1)[C@H]2COCCN2)C
+C1=CSC(=C1)/C=N/NC2=NN=C(N2N)S
+c1cc(c(cc1Cl)[N+](=O)[O-])NN
+C1CC1[C@@H](C2=CC=CN2)N
+CC1=C(C=C(S1)CNC(C)C)Br
+c1ccc(cc1)CC(=O)N2CC[C@@H]3CNS(=O)(=O)[C@@H]3CC2
+Cc1c(cc(cc1F)CN)OC
+CCNC(=O)c1cc(cnc1)Br
+C1CN(S(=O)(=O)C1)C(=O)C2=C(SC(=C2)Cl)Cl
+Cc1ccccc1C2=NOC(=N2)/C(=C\c3ccccc3)/C#N
+CN1C=CC=C1[C@H](CF)N
+COc1ccc2ccccc2c1/C=N/c3ccc(cc3)Cl
+c1cc(c(cc1C(=O)O)[N+](=O)[O-])C#N
+CC1=C(C=C(N1C)C#N)/C=N\NC2=Nc3ccccc3S2
+c1ccc2c(c1)N(CCO2)C(=O)c3ccc(cc3)C#N
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+c1cc2c(cc1Nc3ccc(cn3)C#N)CCC2
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+CC1=NN(C(=C1C#N)N)Cc2ccc(c(c2)Br)F
+C#Cc1cccc(c1)NC(=O)c2ccnc(c2)Cl
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+Cc1ccc(nn1)C2=NOC(=N2)C3=C4C(=CS3)OCCO4
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+CC1=NN(C(=C1/C=N\c2cccc(c2)C#N)Cl)c3ccc(cc3)F
+Cc1ccc2c(c1)N(CCO2)C(=O)c3ccc(cc3)C#N
+CCOc1cc(ccc1C#N)Br
+c1cc(c(cc1C#N)C(=O)O)Cl
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+c1cc(nc(c1)Br)C2(CC2)C#N
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+c1cc(ccc1/C=N\Nc2c(c(c(c(n2)Cl)C#N)Cl)Cl)Br
+Cc1cc(c2ccccc2n1)CN3C(=C(C(=N3)C)C#N)N
+COC(=O)c1cc(c(nc1CBr)Cl)Cl
+COC(=O)c1cc(cc2c1OCO2)Br
+CC(C)(C)OC(=O)N1C=Cc2c1c(ccc2)Br
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+CC(C)(C)OC(=O)N1CCNCC12CCCC2
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+c1cc(nc(c1[N+](=O)[O-])C(=O)O)Cl
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+c1ccc(c(c1)/C=N\NC2=Nc3ccccc3O2)Br
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+CC1=NOc2c1c(ncn2)[N@](C)CC3=C(ON=C3C)C
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+c1ccc(c(c1)/C=N/NC2=NON=C2N)Br
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+CC(C)COc1ccc(cc1Cl)S
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+c1cc(c(cc1Br)S)C(=O)O
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+CC1=NSC(=C1[N+](=O)[O-])N
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+Cc1cc(c(cc1OC)C(=O)O)N
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+CN1c2ccccc2N=C1N/N=C\3/CCCOc4c3ccc(c4)Br
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+CCSc1cccc(c1)C(F)(F)F
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+CC(=O)Sc1ccc(c(c1)F)Cl
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+Cc1ccc(c(c1)/C=N/NC2=NS(=O)(=O)c3c2cccc3)C
+c1ccc(cc1)SC2=NC(=NN2)[N+](=O)[O-]
+C/C=C\C(=N/NC1=Nc2ccccc2S1)\N
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+c1cc2c(cc1F)C(=CN2)/C(=N\O)/N
+COc1ccc(cc1/C(=N/O)/N)Br
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+CS(=O)(=O)[N@]1CCC[C@]12CCCN(C2)C(=O)CC#N
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+CN1C(=NN=N1)CN
+C#Cc1cccc(c1)NC(=O)c2cc(c(nc2)Cl)Cl
+CC(=O)Nc1cc(cc(c1[N+](=O)[O-])Br)Br
+c1cc(c(cc1Cl)[N+](=O)[O-])OC(F)(F)F
+c1cc(nc(c1C(F)(F)F)C=O)Cl
+c1cc(cc(c1)OC(F)(F)F)NN
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+CN1CCC[C@@]2(C1=O)CC[N@](C2)c3cccc(n3)C(F)(F)F
+c1cc(c(cc1F)C(F)(F)F)[C@@H]2CCN2
+c1cc(c(cc1[C@H]2CCN2)F)F
+c1cc(ccc1C2(CC2)C(=O)N3C[C@@H]4CCC[C@H](C3)NC4=O)F
+CC(C)Oc1cc(ccc1F)C=O
+CCOc1cc(ccc1F)SC
+COC(=O)c1cc(ccc1F)CBr
+CC(=O)N1CCCCC12CCNCC2
+Cc1cc(c(nc1C)[N@]2CC[C@]3(C2)CCCN(C3=O)CC4CC4)C#N
+c1c(c(cc(c1F)F)F)C(=O)C2CC2
+c1c(cnc(n1)C2(CC2)CO)Br
+c1ccc(c(c1)C2(CC2)C(=O)N3CCCCC3)Cl
+c1cc(c(c(c1)Br)F)C(=O)C2CC2
+c1cc(ncc1F)C2(CC2)C(=O)O
+c1cc(cc(c1)F)CC(=O)N2CCC3(CC3)CC2
+Cc1ccc(cc1)/N=C/2\C=C(SS2)c3ccc(cc3)OC
+c1cc(c(cc1OC(Cl)(Cl)Cl)Br)F
+c1cc(c(cc1F)[N+](=O)[O-])OC(F)(F)Cl
+c1cc(c(cc1Br)I)[N+](=O)[O-]
+c1cc(c(c(c1)I)O)C(=O)O
+CC1=NN(C=C1I)CC(=O)C
+Cc1cc(nc(n1)N/N=C/C2=C(N=C3N2C=C(C=C3)I)C)C
+Cc1c(cc(c(c1Cl)I)Cl)[N+](=O)[O-]
+C1=C(OC(=C1)[N+](=O)[O-])[C@@H](CO)N
+c1c(c(c(c(c1Br)F)F)N)[N+](=O)[O-]
+c1c(c(cc(c1I)F)Br)[N+](=O)[O-]
+C[C@@H]1CN(CC[C@@]1(C)O)C(=O)CN2N=CC=N2
+c1cc(c(cc1OC(F)(F)F)CO)Cl
+c1c(c(nc(n1)Cl)Cl)CO
+CCCOc1cc(cc(c1F)F)S
+CCCOc1ccc(cc1S)C
+Cc1ccc(cc1)N2C(=C(C(=N2)C)/C=N/N3C(=NN=C3S)C)Cl
+c1cc(c(c(c1)Cl)Cl)/C=N/NC2=NN=CN2N
+CC1=CC(=O)N2C(=C(C(=O)N2)/N=N\c3ccccc3)N1
+c1cc(nc(c1)Cl)C2(CC2)C(=O)O
+c1cc(c(cc1N=C=O)[N+](=O)[O-])F
+Cc1c(nc(nn1)N/N=C/C2=CNc3c2cccc3)O
+c1ccnc(c1)OS(=O)(=O)c2ccc(cc2)F
+CC1=NSC(=C1[N+](=O)[O-])Br
+CC1=NN(C(=C1N)Cl)CC=C
+C1C(=S)N=CC(=N1)F
+C=C(C(=O)O)OP(=O)(O)O
+c1cc(cc(c1)F)CC(=O)N2CCSSCC2
+c1ccc(cc1)/N=C\NC#N
+C#Cc1cccc(c1)NC(=O)N2CCc3ccccc3C2
+Cc1cccc(c1)C(=O)Nc2cccc(c2)C#C
+CCOc1cc(ccc1C#N)S(=O)(=O)Cl
+CN1CC(=O)N=C1NP(=O)(Cl)Cl
+CCCCCc1c(c(c(nc1C(C)C)C(C)C)CO)c2ccc(c(c2)CC)F
+CCCCC[S@@](=O)C1=NN=C(S1)N(C)C(=O)N(C)C
+C1C[C@@H](NC1)CCCS(=O)(=O)CCCC(F)(F)F
+C1C[C@@H]([NH2+]C1)CCCS(=O)(=O)CCCC(F)(F)F
+C1C[C@H](C2=C(C1)OC=C2)NC3=NCCO3
+C1C[C@H](C2=C(C1)OC=C2)NC3=[NH+]CCO3
+C1C[C@H](C2=C(C1)OC=C2)/[NH+]=C\3/NCCO3
+C[C@@H](CCc1ccc(c(c1)OC)OC)O
+CCS(=O)(=O)c1ccc(c(c1OCC2CCCC2)Cl)C(=O)C3C(=O)CCCC3=O
+c1ccc(cc1)C2=C(c3ccc(cc3CCC2)O)c4ccc(cc4)OCCCCC[S@@](=O)Cc5ccccn5
+C[C@H](C(C)(C)C)[N@]1CC[C@](O1)(C)c2cccc(c2)[C@]3(CC[N@](O3)[C@H](C)C(C)(C)C)C
+c1ccc2c(c1)[C@@H](CCS2)C[C@@](CO)(C(F)(F)F)O
+CC[C@@H]1C(=Nc2cc3c(cc2O1)CCCC3)N
+CC[C@@H]1C(=[NH+]c2cc3c(cc2O1)CCCC3)N
+c1ccc(cc1)c2ccc(cc2)C3(CCCC3)CNC=O
+CC[C@@H]1CS[C@@H](C1=O)C(=O)OCC
+CC[C@@H]1CSC(=C1O)C(=O)OCC
+CC(C)(C)OC(=O)[C@@]1(COC[C@@H]1F)N(C(=O)OC(C)(C)C)S(=O)(=O)O
+CC(C)(C)OC(=O)[C@@]1(COC[C@@H]1F)N(C(=O)OC(C)(C)C)S(=O)(=O)[O-]
+c1ccc(cc1)CN(Cc2ccccc2)c3ccc(cc3)C4(CCC4)CCO
+CC1(CC1)c2c(cc(cn2)Cl)CNC3CC3
+CC1(CC1)c2c(cc(cn2)Cl)C[NH2+]C3CC3
+CC(C)C(=O)c1cc(cc(c1OC)Cl)O
+C[C@@H](Cc1ccc(cc1)OCCO)N
+C[C@@H](Cc1ccc(cc1)OCCO)[NH3+]
+Cc1cc(cc(c1CC(=O)O)C)C2CC2
+Cc1cc(cc(c1CC(=O)[O-])C)C2CC2
+Cc1cc(nc2c1COC(=O)N2)c3c(cccc3OCC4CC4)O
+C[S@@](=O)C1=NN=C(S1)C(=O)NC2CC2
+c1ccc2c(c1)CCC[C@@H]2NC3=NCCS3
+c1ccc2c(c1)CCC[C@@H]2NC3=[NH+]CCS3
+c1ccc2c(c1)CCC[C@@H]2/[NH+]=C\3/NCCS3
+CC/C(=C(\c1ccccc1)/c2ccc(cc2)OCCCCCS(=O)(=O)Cc3ccccn3)/c4ccccc4
+CC(=C(C)COc1ccccc1C(=C)N2C=CN=C2)C
+CSCC[C@@H]1C(=Nc2ccccc2O1)N
+CSCC[C@@H]1C(=[NH+]c2ccccc2O1)N
+CSCC[C@@H]1C(=[NH2+])Nc2ccccc2O1
+c1ccc(cc1)CCCC(=O)NCCc2ccccc2
+CCOC(=O)C1(CCN(CC1)OC)O
+CCCOc1ccc(cc1OC)CCN
+CCCOc1ccc(cc1OC)CC[NH3+]
+CCc1cc(cc(c1CC(=O)O)C)C#CC2CC2
+CCc1cc(cc(c1CC(=O)[O-])C)C#CC2CC2
+c1ccc(cc1)[C@@H]2CCc3cccc(c3S2)CO
+CC[C@@H](c1ccc(c(c1)OC2CCCC2)OC)O
+CC[C@@H]1CS[C@@H](C1=O)C(=O)OC
+CC[C@@H]1CSC(=C1O)C(=O)OC
+Cc1cc(c(nc1)C2(CC2)C)CNC3CC3
+Cc1cc(c(nc1)C2(CC2)C)C[NH2+]C3CC3
+COc1ccc2c(c1)CCC[C@@H](C2=O)c3cccc(c3)S(=O)(=O)C
+CC(C)(C)OC(=O)[C@@]12COC[C@@H]1OS(=O)(=O)N2C(=O)OC(C)(C)C
+C[N@@](Cc1ccc(cc1)[C@@H]2CCCC[C@@H]2C(=O)O)c3ccccc3
+C[N@@](Cc1ccc(cc1)[C@@H]2CCCC[C@@H]2C(=O)[O-])c3ccccc3
+C[C@@H](CCN(Cc1ccccc1)Cc2ccccc2)OC(=O)N3C(COC3(C)C)(C)C
+C[C@@H](CC[NH+](Cc1ccccc1)Cc2ccccc2)OC(=O)N3C(COC3(C)C)(C)C
+C1C[C@@H](NC1)CCS(=O)(=O)CCC(F)(F)F
+C1C[C@@H]([NH2+]C1)CCS(=O)(=O)CCC(F)(F)F
+c1ccc2c(c1)CC(C2)NC3=NCCO3
+c1ccc2c(c1)CC(C2)NC3=[NH+]CCO3
+c1ccc2c(c1)CC(C2)/[NH+]=C\3/NCCO3
+C[C@H](C(C)C)[N@@]1CC[C@@H](O1)c2ccc(cc2)[C@@H]3CC[N@@](O3)[C@@H](C)C(C)C
+CC1(CC1)c2c(cccn2)CNC3CC3
+CC1(CC1)c2c(cccn2)C[NH2+]C3CC3
+Cc1cc2c(c(c1)OCCC(C)C)Oc3ccc(c(c3C(=O)OC2)OC)[C@@H](CC(C)(C)c4ccccc4)O
+c1ccc2c(c1)[C@@H](CO2)NC3=NCCO3
+c1ccc2c(c1)[C@@H](CO2)NC3=[NH+]CCO3
+c1ccc2c(c1)[C@@H](CO2)/[NH+]=C\3/NCCO3
+COc1ccc(cc1OC2CCCC2)[C@@H](C#N)O
+CS(=O)(=O)c1ccc(c(c1COC2CCCCC2)Cl)C(=O)C3C(=O)CCCC3=O
+COc1ccc2c(c1)CCCC(=C2CCCCCO)c3ccc(cc3)S(=O)(=O)C
+CC1(CC1)COC(=O)[C@@H](c2ccccc2)C(=O)O
+CC1(CC1)COC(=O)[C@@H](c2ccccc2)C(=O)[O-]
+C[C@H](C(C)(C)C)[N@]1CC[C@](O1)(C)c2ccc(cc2)[C@]3(CC[N@](O3)[C@H](C)C(C)(C)C)C
+C[C@@H]1C(=Nc2cc3c(cc2O1)CCCC3)N
+C[C@@H]1C(=[NH+]c2cc3c(cc2O1)CCCC3)N
+CC(C)CCOc1ccccc1N2C=CN=C2
+CCOC(=O)[C@@H]1C(=O)[C@@H](CS1)C
+CCOC(=O)C1=C([C@@H](CS1)C)O
+C[C@@](CN)(c1ccc(c(c1)OC2CCCC2)OC)O
+C[C@@](C[NH3+])(c1ccc(c(c1)OC2CCCC2)OC)O
+CCOc1cc(ccc1[C@@H]2CCC(=O)N2)C(C)(C)C
+C[C@@]1(O[C@@H](CS1)CN2CCCCC2)C(C)(C)COc3ccc(cc3)Cl
+C[C@@]1(O[C@@H](CS1)C[NH+]2CCCCC2)C(C)(C)COc3ccc(cc3)Cl
+c1ccc(cc1)C2=C(c3ccc(cc3CCC2)O)c4ccc(cc4)OCCCC[S@@](=O)Cc5ccccn5
+Cc1cc(c2c(c1)N=C([C@@H](O2)C)N)C
+Cc1cc(c2c(c1)[NH+]=C([C@@H](O2)C)N)C
+C[S@@](=O)CCOc1ccccc1N2C=CN=C2
+CCCc1cc(ccc1OCCCOc2ccc3c(c2)CC[C@@H]3CC(=O)O)C4=NC(=C(O4)C(=O)C)C
+CCCc1cc(ccc1OCCCOc2ccc3c(c2)CC[C@@H]3CC(=O)[O-])C4=NC(=C(O4)C(=O)C)C
+c1ccc2c(c1)CC[C@@H]2NC3=NCCO3
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+CCc1cc(cc(c1CC(=O)[O-])CC)C#CC
+c1ccc2c(c1)[C@@H](CCS2)C[C@@H](C(F)(F)F)O
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+COC(=O)C[C@@H](CS(=O)(=O)c1ccc(cc1)[O-])c2ccccc2
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+c1ccc(cc1)CN(Cc2ccccc2)c3ccc(cc3)C4(CCC4)CC(=O)[O-]
+C[C@@H](C1=CCCc2c1ccc(c2)OC)C(=O)O
+C[C@@H](C1=CCCc2c1ccc(c2)OC)C(=O)[O-]
+CC(C)c1ccc(cc1C(=O)O)O
+CC(C)c1ccc(cc1C(=O)[O-])O
+c1ccc2c(c1)CCC[C@@H]2NC(=O)CN3C(=O)N(C(=N3)c4ccc(cc4)Cl)C5CC5
+COC(=O)N[C@@]12CN(C[C@@H]1C=CC=C2)C(=O)OC
+C[C@@H](c1ccccc1F)NC2=NCCO2
+C[C@@H](c1ccccc1F)NC2=[NH+]CCO2
+C[C@@H](c1ccccc1F)/[NH+]=C\2/NCCO2
+CCS(=O)(=O)c1ccc(c(c1OCC2CCCC2)Cl)C(=O)O
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+Cc1ccc(cc1CC(=O)O)C2CC2
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+c1ccc2c(c1)C(=CCS2)C[C@@](CO)(C(F)(F)F)O
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+c1ccc(c(c1)O)S(=O)(=O)c2ccccc2O
+c1ccc(c(c1)[O-])S(=O)(=O)c2ccccc2[O-]
+C[C@@H](c1ccc2cc(ccc2c1)OC)C(=O)O
+C[C@@H](c1ccc2cc(ccc2c1)OC)C(=O)[O-]
+C[C@@H]1Cc2cc(c(cc2C1=O)F)OC
+Cc1ccc2c(c1)C(=O)N(N=N2)C[C@@H]3CC[C@@H]([C@@H]3C(=O)O)C(=O)c4ccc(cc4)OCC5CCCCC5
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+CS(=O)(=O)Cc1ccccc1S(=O)(=O)N
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+CCOc1ccc(cc1OC)C[C@@H](C)N
+CCOc1ccc(cc1OC)C[C@@H](C)[NH3+]
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+c1cc(ccc1c2ccc3c(c2)CC[C@@H](O3)C[NH2+]C[C@@H](COc4ccc(cc4)F)O)C(=O)[O-]
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+CCC[C@@H]1C(=Nc2ccccc2O1)N
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+Cc1cc(cc(c1Cc2ccc(c(c2)S(=O)(=O)c3ccc(cc3)F)O)C)OC(C)(C)C(=O)O
+Cc1cc(cc(c1Cc2ccc(c(c2)S(=O)(=O)c3ccc(cc3)F)[O-])C)OC(C)(C)C(=O)[O-]
+CC(C)c1cccc(c1OC)C(C)(C)O
+CC[C@@H]([C@@H]1CCc2c1ccc(c2)OCCC3=C(OC(=N3)c4cccc(c4)OC)C)C(=O)O
+CC[C@@H]([C@@H]1CCc2c1ccc(c2)OCCC3=C(OC(=N3)c4cccc(c4)OC)C)C(=O)[O-]
+CC/C(=C(\c1ccc(cc1)O)/c2ccc(cc2)OCCCCCS(=O)(=O)Cc3ccccn3)/c4ccccc4
+c1cc(ccc1CCO)S(=O)(=O)c2ccc(cc2)CCO
+CC(=O)OCCC1(CCC1)c2ccc(cc2)N(Cc3ccccc3)Cc4ccccc4
+CCOC(=O)C1=C2c3cc(c(cc3CCN2C(=C1C4=CNc5c4cccc5OC)C)OC)OC
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+c1cc(ccc1c2ccc(cc2)F)C3(CCCCC3)CNC=O
+C[C@@H](C(=O)O)Oc1cccc2c1cccc2O
+C[C@@H](C(=O)[O-])Oc1cccc2c1cccc2O
+c1ccc2cc(ccc2c1)C[C@@]34CCC[C@@H]3COC4=O
+CCCCC[S@@](=O)C1=NN=C(S1)C(=O)NCC(C)C
+c1cc(c(c(c1)Cl)NC2=NCCO2)Cl
+c1cc(c(c(c1)Cl)NC2=[NH+]CCO2)Cl
+c1cc(c(c(c1)Cl)/[NH+]=C\2/NCCO2)Cl
+C1C[C@@H](NC1)CCCS(=O)(=O)CCCCC(F)(F)F
+C1C[C@@H]([NH2+]C1)CCCS(=O)(=O)CCCCC(F)(F)F
+c1ccc(cc1)C[S@@](=O)CCCCCOc2ccc(cc2)C3=C(CCCc4c3ccc(c4)O)c5ccccc5
+c1ccc(cc1)c2ccc(cc2)C3(CCCCC3)CNC=O
+CCC(=O)c1ccc(c(c1)OC2CCCC2)OC
+CC1(CC1)c2c(cc(cn2)Br)CNC3CC3
+CC1(CC1)c2c(cc(cn2)Br)C[NH2+]C3CC3
+c1ccc2c(c1)CCC[C@@H]2Nc3ncc(cn3)Cl
+Cc1cc(cc2c1OC3(CCCCC3)C[C@@H]2NCc4ccccc4)Cl
+Cc1cc(cc2c1OC3(CCCCC3)C[C@@H]2[NH2+]Cc4ccccc4)Cl
+c1c2c(cc(c1C=C3CCCCC3)Cl)[C@@H](CC2)C(=O)O
+c1c2c(cc(c1C=C3CCCCC3)Cl)[C@@H](CC2)C(=O)[O-]
+C[C@@H]1C[C@@H](CN(C1)C[C@@H]2[C@@H]([C@@H](CO2)c3ccc(cc3)Cl)C)C
+C[C@@H]1C[C@@H](C[NH+](C1)C[C@@H]2[C@@H]([C@@H](CO2)c3ccc(cc3)Cl)C)C
+C[C@@H]1C(=O)N(c2ccc(nc2[N@@]1C3CCCCCC3)Nc4ccc(cc4)S(=O)(=O)N(C)C)C
+C[C@@H](c1ccccc1Cl)NC2=NCCO2
+C[C@@H](c1ccccc1Cl)NC2=[NH+]CCO2
+C[C@@H](c1ccccc1Cl)/[NH+]=C\2/NCCO2
+C[C@@H]1C(=Nc2cc(ccc2O1)C#N)N
+C[C@@H]1C(=[NH+]c2cc(ccc2O1)C#N)N
+CC1(CC(=O)Nc2c1cc(cc2)F)C
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+CCCC[S@@](=O)C1=NN=C(S1)C(=O)N
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+CC(C)[S@@](=O)C1=NN=C(S1)C(=O)NCC2CCCCC2
+c1ccc2c(c1)NC(=O)CC[S@@]2=O
+C[C@@H]1Cc2ccccc2[C@@H]1NC(=O)COC
+CCCCS(=O)(=O)Nc1cccc(c1)OCc2ccc3ccccc3n2
+CCCCC[S@@](=O)C1=NN=C(S1)C(=O)NCCC
+c1cc(ccc1[S@@](=O)[C@@H]2CCCCNC2=O)Cl
+CCN(CC)CCOc1ccc(cc1)CNc2ccc(c3c2cccc3)Cl
+CC[NH+](CC)CCOc1ccc(cc1)CNc2ccc(c3c2cccc3)Cl
+Cc1ncc2c(n1)cccc2N[C@@H]3c4cc(ccc4C(C[C@@]3(C(F)(F)F)O)(C)C)Cl
+c1cc2c(nc1)NC(=N2)COCCO
+c1cc2c(nc1)N=C(N2)COCCO
+CCC[C@@H](c1ccc(nc1)C#N)N2C=CN=C2
+C[C@@H](CO)Nc1c(cnc(n1)Nc2cccc(c2)S(=O)(=O)NCCCc3ccccc3)Br
+CCCc1c(ccc2c1ON=C2C(F)(F)F)OCCCOc3ccc4c(c3)CC[C@@H]4[C@@H](C)C(=O)OC
+Cc1cc(cnc1CO)OCC[N@@](C)OC
+c1ccc(cc1)C(=O)NS(=O)(=O)c2ccc(cc2)c3ccc4c(c3)CC[C@@H](O4)CNC[C@@H](c5cccnc5)O
+c1ccc(cc1)C(=O)NS(=O)(=O)c2ccc(cc2)c3ccc4c(c3)CC[C@@H](O4)C[NH2+]C[C@@H](c5cccnc5)O
+c1ccc2c(c1)ccc(n2)COc3ccc(cc3)[C@@](C4CCCC4)(C(=O)O)O
+c1ccc2c(c1)ccc(n2)COc3ccc(cc3)[C@@](C4CCCC4)(C(=O)[O-])O
+CN1[C@@H]([C@@H](CC1=O)c2ccccc2)[C@@H](C#Cc3ccccc3)O
+c1ccc(cc1)OCCCCOc2ccc(cc2)C#CCO
+COc1ccc(cc1)[C@@]23[C@@H](C[C@@H]([C@@]2(c4c(cc(cc4OC)OC)O3)O)O)c5ccccc5
+CCc1cccc(c1)N(CC)C(=O)CO
+CCCC[C@@H](c1cccc(c1)COc2cccc3c2nccc3C)O
+c1cc2c(nc1)C(=CN2)C[C@@H](CO)N
+c1cc2c(nc1)C(=CN2)C[C@@H](CO)[NH3+]
+c1cc(c(cc1S(=O)(=O)N)S(=O)(=O)N)O
+c1cc(c(cc1S(=O)(=O)N)S(=O)(=O)N)[O-]
+c1cncc2c1NC=C2C[C@@H](CO)N
+c1cncc2c1NC=C2C[C@@H](CO)[NH3+]
+Cc1cc(cc(c1O)C)S(=O)(=O)c2cc(c(c(c2)C)O)C
+Cc1cc(cc(c1[O-])C)S(=O)(=O)c2cc(c(c(c2)C)[O-])C
+COc1c(cc(cc1Cl)O)C(=O)C2CCCCC2
+COc1ccc2ccc(cc2c1)OCCCOc3ccc-4c(c3)N(c5c4cccc5)CC(=O)O
+COc1ccc2ccc(cc2c1)OCCCOc3ccc-4c(c3)N(c5c4cccc5)CC(=O)[O-]
+CCCC[C@@H]1C(C(=O)c2ccccc2O1)(CCS(=O)(=O)C)CCS(=O)(=O)C
+Cc1ccc2c(c1)[C@@H]([C@@H](C2)C)Nc3ncc(cn3)C(=O)C
+CCCC[S@@](=O)[C@@H]1CCCCNC1=O
+c1cc(cc2c1cc(cc2)O)C(=O)O
+c1cc(cc2c1cc(cc2)O)C(=O)[O-]
+CC(C)N1C(=O)c2ccccc2NS1(=O)=O
+c1cc(ccc1S(=O)(=O)[C@@H]2CCCCNC2=O)Cl
+CC1(c2c(nc(nc2NC1=O)C3=NN(c4c3cccn4)Cc5ccccc5F)C(=O)NCC[S@@](=O)C)C
+CCC[C@@H]1C(C(=O)c2ccccc2O1)(CCS(=O)(=O)C)CCS(=O)(=O)C
+CC(=O)c1ccc(cc1)[C@@H](C2CCCCC2)O
+C[C@@H]1C(=O)N(c2ccc(nc2[N@@]1C3CCN(CC3)C)Nc4cccc(c4)S(=O)(=O)N5CCOCC5)C
+C[C@@H]1C(=O)N(c2ccc(nc2[N@@]1C3CC[NH+](CC3)C)Nc4cccc(c4)S(=O)(=O)N5CCOCC5)C
+Cc1ccc(cc1)S(=O)(=O)[C@@H]2CCCNC(=O)C2
+CCC(=O)N[C@@H]1CCc2c1ccc(c2)C(=O)C
+CC(=O)NC[C@@]1(CC(=O)c2ccccc2O1)C
+CCCCC[S@@](=O)C1=NN=C(S1)C(=O)NCCCC
+c1cc2c(cc1O)S(=O)(=O)CO2
+CCN(CC)CCC[C@@]1(C(C(=O)c2ccccc2O1)(CCS(=O)(=O)C)CCS(=O)(=O)C)C
+CC[NH+](CC)CCC[C@@]1(C(C(=O)c2ccccc2O1)(CCS(=O)(=O)C)CCS(=O)(=O)C)C
+CC1(CC1)C(=O)[C@@H](CS(=O)(=O)c2ccccc2)N3C=NC=N3
+C[C@@H]1Cc2cc(c(cc2C(=NN1C(=O)NC)c3ccc(cc3)c4cccc(c4)NS(=O)(=O)C)OC)OC
+CCCCC[S@@](=O)C1=NN=C(S1)C(=O)NCC
+CCS(=O)(=O)C1(CC1)[C@@](CN2C=NC=N2)(c3ccc(cc3)Cl)O
+COC(=O)CCN1c2ccc(cc2C3=C1CC[C@@H](C3)NS(=O)(=O)c4ccc(cc4)Cl)F
+Cc1ccc2c(c1)COC(=O)c3c(ccc(c3OC)[C@@H](C(C)C)O)S2(=O)=O
+CC(C)(C)OC(=O)[C@@]12CCOC[C@@H]1OS(=O)(=O)N2C(=O)OC(C)(C)C
+C1=C2N(C=N1)S(=O)(=O)C3=CN=CN3S2(=O)=O
+Cc1cc2c(c(c1)OC)S(=O)(=O)c3ccc(c(c3C(=O)OC2)OC)[C@@H](CC(C)C)O
+CC(C)(C)[C@@H]([C@@H](CS(=O)(=O)c1ccccc1)N2C=NC=N2)O
+c1cc(ccc1CCN2C(=O)N3[C@H](CCCC3=N2)C(=O)N4CC(C4)(F)F)F
+c1ccc2c(c1)C(=O)N3c4ccccc4C(=O)NCC3=N2
+c1ccc2c(c1)N=C([C@@H](O2)CCO)N
+c1ccc2c(c1)[NH+]=C([C@@H](O2)CCO)N
+c1ccc2c(c1)NC(=[NH2+])[C@@H](O2)CCO
+CCC1=COC(=N1)c2ccc(cc2)OCCCOc3ccc4c(c3)C=CN4[C@@H](C)C(=O)O
+CCC1=COC(=N1)c2ccc(cc2)OCCCOc3ccc4c(c3)C=CN4[C@@H](C)C(=O)[O-]
+Cc1cc(ccn1)c2ccc(cc2C3=NNN=N3)NC(=O)C4(CC4)c5cccc(c5)Cl
+Cc1cc(ccn1)c2ccc(cc2C3=N[N-]N=N3)NC(=O)C4(CC4)c5cccc(c5)Cl
+Cc1cc(ccn1)c2ccc(cc2C3=NN=N[N-]3)NC(=O)C4(CC4)c5cccc(c5)Cl
+CN(C)S(=O)(=O)N1C=C(N=C1C#N)S(=O)(=O)[N@@]2CCc3c2cccc3
+CN(C)S(=O)(=O)N1C=C([NH+]=C1C#N)S(=O)(=O)[N@@]2CCc3c2cccc3
+Cc1nc2cc(c(cc2c(n1)N[C@@H](C)c3cccc(c3)C4=CNN=C4)O)OC
+CCc1cc(cc(c1C2C(=O)[C@@H]3CC(C[C@@H]3C2=O)OC)CC)C
+CCCOC(=O)[C@@H]1C(=O)[C@@H](CS1)C
+CCCOC(=O)C1=C([C@@H](CS1)C)O
+CC(=CC[C@@H](c1ccc(cc1)OCc2ccc3ccccc3n2)C(=O)OC)C
+CC(=C[C@@H]([C@@H](C(C)(C)C)O)N1C=NC=N1)C
+CC1=CC(Cc2c1nc(c(c2c3ccc(cc3)F)CO)C(C)C)(C)C
+C[C@@H]1[C@@H]2CC(=C)C[C@@]2(C(=O)O1)Cc3ccc4ccccc4c3
+CC1(C[C@@]([C@@H](c2c1c(c(cc2)F)O)NC(=O)c3ccc4c(c3)C=CO4)(C(F)(F)F)O)C
+CC1(C=C(c2ccccc2O1)CN3CCN(CC3)c4ccccc4)C
+CC1(C=C(c2ccccc2O1)C[NH+]3CCN(CC3)c4ccccc4)C
+CC(=CCOc1cc(ccc1OC)[C@@H]2CC(=O)NC2)C
+COc1ccc(cc1)C2(CC2)CN3C(=O)N4[C@H](CCCC4=N3)C(=O)N5CC(C5)F
+CCOc1ccc(cc1)C2=C(N(c3c2cc(cc3)CCOCC4CC4)Cc5ccc(cc5)F)C(=O)O
+CCOc1ccc(cc1)C2=C(N(c3c2cc(cc3)CCOCC4CC4)Cc5ccc(cc5)F)C(=O)[O-]
+C[C@@]1(CNC(=O)O1)c2ccc(c(c2)OCC3CC3)OC
+c1cc(cnc1)CNC(=O)c2ccc3c(c2)N(CC(=O)N3C4CC4)C(=O)CNC5CCCCC5
+c1cc(cnc1)CNC(=O)c2ccc3c(c2)N(CC(=O)N3C4CC4)C(=O)C[NH2+]C5CCCCC5
+c1cc(ccc1[C@@](CN2C=NC=N2)(C3(CC3)F)O)Cl
+c1ccc2c(c1)C(=C(N2Cc3ccc(cc3)F)C(=O)O)c4cccc(c4)OCC5CC5
+c1ccc2c(c1)C(=C(N2Cc3ccc(cc3)F)C(=O)[O-])c4cccc(c4)OCC5CC5
+c1cc2c(cc1CC(=O)C3CC3)OC(=C2)C(=O)N[C@@H]4CN5CCC4CC5
+c1cc2c(cc1CC(=O)C3CC3)OC(=C2)C(=O)N[C@@H]4C[NH+]5CCC4CC5
+CCOC(=O)C1(CC1)[C@@](CN2C=NC=N2)(COc3ccc(cc3)F)O
+COc1cccc(c1)CN2c3ccccc3C(=C2C(=O)O)c4ccc(cc4)OCC5CC5
+COc1cccc(c1)CN2c3ccccc3C(=C2C(=O)[O-])c4ccc(cc4)OCC5CC5
+CC1(C[C@@H](c2ccccc2O1)CNC3CC3)C
+CC1(C[C@@H](c2ccccc2O1)C[NH2+]C3CC3)C
+COc1cc2ccccc2cc1OCCCCOc3ccc-4c(c3)N(c5c4cccc5)CCC(=O)O
+COc1cc2ccccc2cc1OCCCCOc3ccc-4c(c3)N(c5c4cccc5)CCC(=O)[O-]
+c1cc2c(cc1Cl)OC3(CCCC3)C[C@@H]2O
+c1ccc2c(c1)[C@@H](CO2)NC3=NCCS3
+c1ccc2c(c1)[C@@H](CO2)NC3=[NH+]CCS3
+C[C@@]12CC[C@@](C[C@@H]1CC[C@@H]2OC(C)(C)C)(c3ccc(cc3)OC)O
+CCC1=C(SC2=C1C(=O)N(C(=O)N2CCOC)C3(CC3)C)CN4CCNC4=O
+COC1(CC1)[C@@](Cc2ccc(cc2)F)(CN3C=NC=N3)O
+c1ccc(cc1)C2=C(N=C3N2C=CC(=N3)OCCN4CCCC4=O)c5ccc(cc5)C6(CCC6)N
+c1ccc(cc1)C2=C(N=C3N2C=CC(=N3)OCCN4CCCC4=O)c5ccc(cc5)C6(CCC6)[NH3+]
+c1c(ncc(n1)Cl)C(=O)NC2CN(C2)CC(F)(F)F
+C[C@@H]1C(=O)N(c2ccc(nc2[N@@]1C3CCCC3)Nc4ccc(cc4OC)C(=O)N5CC6(C5)CCS6(=O)=O)C
+c1c(ncc(n1)Cl)C(=O)NC2CN(C2)CC(F)F
+CC(C)c1cc2c(c(c1[C@@H](c3ccc(cc3)C(F)(F)F)F)C4CCCC4)[C@@H](CC5(O2)CCC5)O
+C[C@@H]1C(=O)N(c2ccc(nc2[N@@]1C3CCOCC3)Nc4ccc(cc4)N5CC6(C5)COC6)C
+c1c(nc(cn1)Cl)C(=O)NC2CN(C2)CCF
+c1c(nc(cn1)Cl)C(=O)NC2C[NH+](C2)CCF
+CC(C)c1cc2c(c(c1[C@@H](c3ccc(cc3)C(F)(F)F)O)C4=CCCC4)C(=O)CC5(O2)CCC5
+C[N@@](CCCN1CCCC1)c2c3c(ccn2)OC=C3
+C[N@@](CCC[NH+]1CCCC1)c2c3c(ccn2)OC=C3
+CC1(C[C@@]([C@@H](c2c1c(c(cc2)F)O)NC(=O)C3=Cc4ccccc4O3)(C(F)(F)F)O)C
+Cc1ccc(cc1N(C)C)C2=NC(=C(O2)C)CCOc3ccc4c(c3)CC[C@@H]4CC(=O)O
+Cc1ccc(cc1N(C)C)C2=NC(=C(O2)C)CCOc3ccc4c(c3)CC[C@@H]4CC(=O)[O-]
+C[C@@H]1C[C@@]([C@@H](c2c1c(c(cc2)Cl)O)Nc3cccc4c3C=COC4=O)(C(F)(F)F)O
+CCN(CC)c1cccc(c1)C2=NC(=C(O2)C)CCOc3ccc4c(c3)CC[C@@H]4CC(=O)O
+CCN(CC)c1cccc(c1)C2=NC(=C(O2)C)CCOc3ccc4c(c3)CC[C@@H]4CC(=O)[O-]
+CC(C)(C)NS(=O)(=O)c1cc(ccc1C(=O)O)C2CC2
+CC(C)(C)NS(=O)(=O)c1cc(ccc1C(=O)[O-])C2CC2
+C[C@@H](CCN1C=CN=C1)c2ccc(cc2)O
+c1cc(ccc1Nc2ncc(c(n2)NC3CCC(CC3)N4CCC(CC4)O)Br)S(=O)(=O)N
+c1cc(ccc1Nc2ncc(c(n2)NC3CCC(CC3)[NH+]4CCC(CC4)O)Br)S(=O)(=O)N
+C[C@@H]1C(=O)N(c2ccc(nc2[N@@]1C3CCOCC3)Nc4cccc(c4)S(=O)(=O)N5CCOCC5)C
+CC(=O)c1ccc(cc1)[C@@H](C2CCCCC2)N3C=CN=C3
+CCC[C@@]1(C(C(=O)c2ccccc2O1)(CCS(=O)(=O)C)CCS(=O)(=O)C)C
+CCc1c(cnc(n1)N[C@@H]2c3cc(ccc3C[C@@H]2C)C)C(=O)CC
+c1cc(c(cc1C(F)F)CC(=O)O)C(F)F
+c1cc(c(cc1C(F)F)CC(=O)[O-])C(F)F
+CC1=C2c3c(ccc(c3CC[C@@H]2C(=O)O)F)N1
+CC1=C2c3c(ccc(c3CC[C@@H]2C(=O)[O-])F)N1
+CC1=C(SC2=C1C(=O)N(C(=O)N2CCCF)CC(C)(C)OC)CNCCN
+CC1=C(SC2=C1C(=O)N(C(=O)N2CCCF)CC(C)(C)OC)C[NH2+]CCN
+COc1cccc(c1)N2CC[C@@H](C2=O)N
+COc1cccc(c1)N2CC[C@@H](C2=O)[NH3+]
+CC(C)c1c(c(c(c(n1)C(C)C)CO)c2ccc(cc2)F)CNC3CCCCC3
+CC(C)c1c(c(c(c(n1)C(C)C)CO)c2ccc(cc2)F)C[NH2+]C3CCCCC3
+Cc1cc2c(c(c1)C#CC3CCCC3)Oc4ccc(c(c4C(=O)OC2)OC)[C@@H](CC(C)C)O
+c1cc(ccc1C#N)[C@@H](C2CCCC2)N3C=CN=C3
+CCCC(=O)N1CCN(CC1)CCCCN2C(=S)N(C(=O)C2(C)C)c3ccc(c(c3)C(F)(F)F)C#N
+CCCC(=O)N1CC[NH+](CC1)CCCCN2C(=S)N(C(=O)C2(C)C)c3ccc(c(c3)C(F)(F)F)C#N
+C[C@@H]1Cc2cc(c(cc2C(=NN1C(=O)NC)c3ccc(cc3)c4ccc(cc4)C#N)OC)OC
+CC(C)(C#N)[C@@](CCc1ccc(cc1)F)(CN2C=NC=N2)O
+CC(=O)OCC1=C[C@@H]2c3cccc4c3C(=C(N4)CO)C[C@@H]2N(C1)C#N
+CCCC(=O)N1CCN(CC1)CCCN2C(=S)N(C(=O)C2(C)C)c3ccc(c(c3)C(F)(F)F)C#N
+CCCC(=O)N1CC[NH+](CC1)CCCN2C(=S)N(C(=O)C2(C)C)c3ccc(c(c3)C(F)(F)F)C#N
+Cc1cc(c2c(c1C#N)COC(=O)c3c(ccc(c3OC)[C@@H](CC(C)C)O)O2)OCCC(C)C
+c1ccc(cc1)CC[C@@](CN2C=NC=N2)(C3(CC3)C#N)O
+CCC[N@@]1C[C@@H](C[C@@H]2[C@@H]1CC3=C(Nc4c3c2ccc4)COC)CC#N
+CCC[N@@H+]1C[C@@H](C[C@@H]2[C@@H]1CC3=C(Nc4c3c2ccc4)COC)CC#N
+CC(C)C[C@@H](c1ccc2c(c1OC)C(=O)OCc3cc(cc(c3O2)O)C#N)O
+CC1(C(=O)N(C(=S)N1CCCCN2CCN(CC2)C(=O)COC)c3ccc(c(c3)C(F)(F)F)C#N)C
+CC1(C(=O)N(C(=S)N1CCCC[NH+]2CCN(CC2)C(=O)COC)c3ccc(c(c3)C(F)(F)F)C#N)C
+C[C@@H]1Cc2cc(c(cc2C(=NN1C(=O)NC)c3ccc(cc3)c4ccccc4C#N)OC)OC
+c1cc(ccc1NS(=O)(=O)c2ccc3c(c2)CC[C@@H](O3)C(=O)O)N4C(=O)N(N=N4)CCCC5CCCC5
+c1cc(ccc1NS(=O)(=O)c2ccc3c(c2)CC[C@@H](O3)C(=O)[O-])N4C(=O)N(N=N4)CCCC5CCCC5
+c1cc(cc(c1)Cl)C2(CC2)C(=O)Nc3ccc(c(c3)C4=NNN=N4)c5cc(cnc5)F
+c1cc(cc(c1)Cl)C2(CC2)C(=O)Nc3ccc(c(c3)C4=N[N-]N=N4)c5cc(cnc5)F
+c1cc(cc(c1)Cl)C2(CC2)C(=O)Nc3ccc(c(c3)C4=NN=N[N-]4)c5cc(cnc5)F
+CC1=C(SC2=C1C(=O)N(C(=O)N2CCOC)CC(C)(C)F)CN3CCNC3=O
+Cc1ccc2c(c1)COC(=O)c3c(ccc(c3OC)[C@@H](CC(=C)C)O)S2
+CC[C@@H](COc1ccc(cc1)C(=O)OCC(C)C)OC(=O)C2=C(C(=NS2)Cl)Cl
+CCSC1(CC1)[C@@](CN2C=CN=C2)(c3ccc(cc3)Cl)O
+C[C@@]1(O[C@@H](CS1)C[N@]2CCCC(C2)(C)C)C(C)(C)COc3ccc(cc3)Cl
+C[C@@]1(O[C@@H](CS1)C[N@H+]2CCCC(C2)(C)C)C(C)(C)COc3ccc(cc3)Cl
+c1cc(ncc1Cl)CN2C(=O)N3[C@H](CCCC3=N2)C(=O)N4CCSC4
+CCC[N@@]1C[C@@H](C[C@@H]2[C@@H]1CC3=C(Nc4c3c2ccc4)COC)CSC
+CCC[N@@H+]1C[C@@H](C[C@@H]2[C@@H]1CC3=C(Nc4c3c2ccc4)COC)CSC
+CC1(c2c(nc(nn2)C3=NN(c4c3cc(cn4)F)CC5CC(C5)(F)F)NC1=O)C
+C[C@@H]1C(=O)N(c2ccc(nc2[N@@]1C3CC[NH+](CC3)C)Nc4cccc(c4)S(=O)(=O)N5CC(C5)(F)F)C
+CC1(C[N@@](c2c1cc(cc2)c3ccc(cc3)C(F)(F)F)S(=O)(=O)c4ccc5c(c4)[C@@H](CCC5)CC(=O)O)C
+CC1(C[N@@](c2c1cc(cc2)c3ccc(cc3)C(F)(F)F)S(=O)(=O)c4ccc5c(c4)[C@@H](CCC5)CC(=O)[O-])C
+c1c(ncc(n1)Cl)C(=O)NC2CCN(CC2)CC(F)F
+CC(C)c1c(c(c2c(n1)CC3(CCC3)C[C@@H]2O)C4CCCC4)[C@@H](c5ccc(cc5)C(F)(F)F)F
+C[C@H]1C[C@H]1N2C(=O)C3=C(N(C2=O)CC4COC4)SC(=C3C)CN5CCNC5=O
+CC[C@@H](C)COc1cc(cc2c1Oc3ccc(c(c3C(=O)OC2)OC)[C@@H](CC(C)C)O)C
+c1ccc(cc1)[C@@H](C(=O)O)C(=O)OCC2CCCCC2
+c1ccc(cc1)[C@@H](C(=O)[O-])C(=O)OCC2CCCCC2
+CCOC(=O)[C@@H]1Cc2cccc(c2C1=O)O
+CCOC(=O)C1=C(c2c(cccc2O)C1)O
+CCCCN(CCCC)c1ncc(cn1)Br
+CSC1(CC1)[C@@](CN2C=NC=N2)(c3ccc(cc3F)F)O
+CC(=O)NC[C@@H]1CN(C(=O)O1)c2ccc3c(c2)SCC4=NC=CN34
+CCN(CC)C(=O)N[C@@H]1C[C@@H]2c3cc(cc4c3C(=C(N4)C)C[C@@H]2[N@@](C1)C)C5SCCS5
+CCN(CC)C(=O)N[C@@H]1C[C@@H]2c3cc(cc4c3C(=C(N4)C)C[C@@H]2[N@@H+](C1)C)C5SCCS5
+c1ccc(cc1)[C@@](CN2C=NC=N2)(C#N)OC3CCCC3
+Cc1ccccc1C2=Nc3ccc(cc3C(=O)N2C[C@@H]4CCC[N@@](C4)C(C)C)C#CC5CC5
+Cc1ccccc1C2=Nc3ccc(cc3C(=O)N2C[C@@H]4CCC[N@@H+](C4)C(C)C)C#CC5CC5
+CC1(C(=O)N(C(=S)N1CCCCCO)c2ccc3c(c2)COC3=O)C
+C=C1C[C@@H]2COC(=O)[C@@]2(C1)Cc3cccc(c3)C(=O)O
+C=C1C[C@@H]2COC(=O)[C@@]2(C1)Cc3cccc(c3)C(=O)[O-]
+Cc1cc2c(c(c1)OC)Sc3ccc(c(c3C(=O)OC2)OC)[C@@H](CC(=C)C)O
+C[C@@H](CCc1ccc(cc1)Cl)NC(=O)N2C(=O)N(C(=N2)C3CC3)NC
+CS(=O)(=O)c1ccc(c(c1OCCN2C=NN=N2)Cl)C(=O)C3C(=O)CCCC3=O
+CCCCC[S@@](=O)C1=NN=C(S1)C(=O)NC2CC2
+CC(C)C1=NN=C(N(C1=O)C)N(C)C
+CCOC(=O)CSC1=Nc2ccc(cc2O1)N3C[C@@H](OC3=O)CNC(=O)C
+CCC[N@@]1C[C@@H](C[C@@H]2[C@@H]1CC3=C(Nc4c3c2cc(c4)C)SC)NC(=O)N(CC)CC
+CCC[N@@H+]1C[C@@H](C[C@@H]2[C@@H]1CC3=C(Nc4c3c2cc(c4)C)SC)NC(=O)N(CC)CC
+CC(C)Nc1c2cc(c(cc2ncn1)OCCCC[S@@](=N)(=O)C)OC
+CC1=C2C[C@@H]3[C@@H](C[C@@H](CN3C#N)C(=O)OC)c4c2c(ccc4)N1
+CC(C)(C)[C@@H]([C@@H](C[C@@H]1CC1(Cl)Cl)N2C=NC=N2)O
+Cc1cccc(c1N([C@@H](C)C=C=C)C(=O)CS(=O)(=O)C)C
diff --git a/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/generate-combined-dataset.py b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/generate-combined-dataset.py
new file mode 100644
index 00000000..529f922f
--- /dev/null
+++ b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/generate-combined-dataset.py
@@ -0,0 +1,192 @@
+import numpy as np
+import requests
+import logging
+from typing import Type
+from collections import Counter
+
+logging.getLogger("openff").setLevel(logging.ERROR)
+
+from openff.qcsubmit.results import OptimizationResultCollection
+from openff.qcsubmit.datasets import OptimizationDataset
+from openff.qcsubmit.factories import OptimizationDatasetFactory
+from openff.qcsubmit.common_structures import MoleculeAttributes
+
+from openff.toolkit.utils import OpenEyeToolkitWrapper, ToolkitRegistry
+from openff.units import unit
+
+
+def pull_record_id_cmiles(Opt):
+    """Pull CMILES strings associated with each molecule record
+
+    Parameters
+    ----------
+    Opt
+        An OptimizationResultCollection object providing a reference to, and
+        allows the retrieval of, data from a single optimization result record
+        stored in a QCFractal instance.
+    
+    """
+    rec_ids_cmiles = {}
+    for _, results in Opt.entries.items():
+        tmp_rec_ids_cmiles = {result.record_id: result.cmiles for result in results}
+        # TODO: Check if updating dic would change the number of records
+        rec_ids_cmiles.update(tmp_rec_ids_cmiles)
+
+    return rec_ids_cmiles
+
+
+
+# _________ Pull Dataset into OptimizationDataset object ____________
+print("# Creating dataset")
+
+file = requests.get(
+    "https://raw.githubusercontent.com/openforcefield/openff-sage/37a36e7eeaf6cdca795847089a288bdff168c08a/data-set-curation/quantum-chemical/data-sets/1-2-0-opt-set-v3.json"
+)
+filtered_and_combined = OptimizationResultCollection.parse_raw(file.content)
+rec_and_mol = filtered_and_combined.to_records()
+rec_and_cmiles = pull_record_id_cmiles(filtered_and_combined)
+
+print("Number of results: ", filtered_and_combined.n_results, flush=True)
+print("Finished converting to records", flush=True)
+
+dataset_factory1 = OptimizationDatasetFactory()
+provenance1 = dataset_factory1.provenance(ToolkitRegistry([OpenEyeToolkitWrapper]))
+
+dataset1 = OptimizationDataset(
+    dataset_name="OpenFF Sage 2.0.0 Training Optimization Dataset v1.0",
+    dataset_tagline="B3LYP-D3BJ/DZVP conformers applicable to drug-like molecules for OpenFF 2.0.0 Sage",
+    description=(
+        "A quantum chemical (QC) dataset curated to train OpenFF 2.0.0 Sage, "
+        "with reparametrized Lennard-Jones (LJ) and valence parameters, the latter "
+        "relevant to this dataset. This QC dataset with the OpenFF default level of "
+        "theory, B3LYP-D3BJ/DZVP, is used to benchmark Sage geometries and energetics. "
+        "These optimized conformer geometries where used in conjunction with the QC "
+        "dataset used to train one dimensional torsional profiles. This Generation 2 "
+        "dataset increases chemical diversity when compared to Generation 1, which are "
+        "of value to our industry partners. Large molecules (>20 heavy atoms) were also "
+        "included, including more flexible molecules and a greater degree of conformational "
+        "variation which provide intramolecular interactions.\nThis is the complete optimization "
+        "dataset used for training OpenFF 2.0.0 Sage, consisting of the following datasets: "
+        "'OpenFF Gen 2 Opt Set 1 Roche', 'OpenFF Gen 2 Opt Set 2 Coverage', 'OpenFF Gen 2 Opt Set 3 Pfizer Discrepancy', "
+        "'OpenFF Gen 2 Opt Set 4 eMolecules  - Discrepancy', and 'OpenFF Gen 2 Opt Set 5 Bayer'.\nThe "
+        "following filters were applied: RecordStatusFilter(status=RecordStatusEnum.complete), "
+        "ConnectivityFilter(tolerance=1.2), UndefinedStereoFilter(), ConformerRMSDFilter(max_conformers=10), "
+        "and ElementFilter(allowed_elements=['H', 'C', 'N', 'O', 'S', 'P', 'F', 'Cl', 'Br', 'I'])"
+        "Further information can be found in the curation scripts for the linked repositories."
+    ),
+    provenance=provenance1,
+)
+dataset1.metadata.submitter = "Jennifer A Clark"
+dataset1.metadata.long_description_url = (
+    "https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/"
+    "2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0"
+)
+
+
+# Have to add records this way to avoid a round trip through the toolkit.
+# rec_and_mole is a linear representation of all the molecules
+# records_by_cmiles groups together conformers
+records_by_cmiles = {}
+for record, molecule in rec_and_mol:
+    cmiles = rec_and_cmiles[record.id]
+    if cmiles in records_by_cmiles:
+        records_by_cmiles[cmiles].append((record, molecule))
+    else:
+        records_by_cmiles[cmiles] = [(record, molecule)]
+
+for cmiles, records in records_by_cmiles.items():
+    base_record, base_molecule = records[0]
+    base_molecule._conformers = [m.conformers[0] for _, m in records]
+
+    # Need to input initial molecules so that QCA will recognize the inputs as the same.
+    initial_mols = [rec.initial_molecule for rec, _ in records]
+
+    dataset1.add_molecule(
+        index=cmiles,
+        molecule=None,
+        initial_molecules=initial_mols, 
+        attributes=MoleculeAttributes.from_openff_molecule(base_molecule),
+        extras=base_record.extras,
+        keywords=base_record.specification.keywords,
+    )
+
+# Check that the molecules are identical
+opt_hashes = {rec.initial_molecule.get_hash() for rec, _mol in rec_and_mol}
+
+new_hashes = {
+    qcemol.identifiers.molecule_hash
+    for moldata in dataset1.dataset.values()
+    for qcemol in moldata.initial_molecules
+}
+
+print("Dataset creation preserved Molecules? ", opt_hashes == new_hashes)
+
+
+
+# _________ Pull Statistics from Dataset ____________
+
+n_confs1 = np.array([mol.n_conformers for mol in dataset1.molecules])
+
+n_heavy_atoms1 = np.array(
+    [mol.to_rdkit().GetNumHeavyAtoms() for mol in dataset1.molecules]
+)
+
+masses1 = np.array(
+    [sum([atom.mass.m for atom in mol.atoms]) for mol in dataset1.molecules]
+)
+
+unique_charges1 = [
+    str(charge)
+    for charge in sorted(
+        set(
+            [
+                mol.total_charge.m_as(unit.elementary_charge)
+                for mol in dataset1.molecules
+            ]
+        )
+    )
+]
+
+# _________ Write Output ____________
+
+print("\n# Heavy Atom Counts")
+counts1 = Counter(n_heavy_atoms1)
+for n_heavy in sorted(counts1):
+    print(f"{str(n_heavy):>3}: {counts1[n_heavy]}")
+
+print("\n\n# Output for README\n")
+print("* Description: {}".format(dataset1.description))
+print("* Purpose: {}".format(dataset1.dataset_tagline))
+print("* Name: {}".format(dataset1.dataset_name))
+print("* Number of unique molecules: {}".format(dataset1.n_molecules))
+print("* Number of filtered molecules:", dataset1.n_filtered)
+print("* Number of conformers: {}".format(dataset1.n_records))
+print(
+    "* Number of conformers (min, mean, max): {:.2f}, {:.2f}, {:.2f}".format(
+        min(n_confs1), np.mean(n_confs1), max(n_confs1)
+    )
+)
+print(
+    "* Molecular weight (min, mean, max): {:.2f}, {:.2f}, {:.2f}".format(
+        min(masses1), np.mean(masses1), max(masses1)
+    )
+)
+print("* Charges: {}".format(", ".join(unique_charges1)))
+print("* Submitter: {}".format(dataset1.metadata.submitter))
+
+print("\n## Metadata")
+print(f"* Elements: {{{', '.join(sorted(dataset1.metadata.dict()['elements']))}}}")
+
+fields = ["basis", "implicit_solvent", "keywords", "maxiter", "method", "program"]
+for spec, obj in dataset1.qc_specifications.items():
+    od = obj.dict()
+    print("* QC Specifications:", spec)
+    for field in fields:
+        print(f"  * {field}: {od[field]}")
+    print("  * SCF Properties:")
+    for field in od["scf_properties"]:
+        print(f"    * {field}")
+
+dataset1.export_dataset("dataset.json.bz2")
+dataset1.molecules_to_file("dataset.smi", "smi")
+dataset1.visualize("dataset.pdf", columns=8)
diff --git a/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/output.txt b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/output.txt
new file mode 100644
index 00000000..8a2bd0de
--- /dev/null
+++ b/submissions/2024-12-12-OpenFF-Sage-2.0.0-Training-Optimization-Dataset-v1.0/output.txt
@@ -0,0 +1,73 @@
+# Creating dataset
+Number of results:  3663
+Finished converting to records
+Dataset creation preserved Molecules?  True
+
+# Heavy Atom Counts
+  4: 2
+  5: 3
+  6: 4
+  7: 7
+  8: 20
+  9: 19
+ 10: 46
+ 11: 56
+ 12: 81
+ 13: 81
+ 14: 94
+ 15: 94
+ 16: 59
+ 17: 59
+ 18: 47
+ 19: 38
+ 20: 36
+ 21: 45
+ 22: 30
+ 23: 23
+ 24: 21
+ 25: 29
+ 26: 6
+ 27: 11
+ 28: 16
+ 29: 10
+ 30: 8
+ 31: 16
+ 32: 16
+ 33: 11
+ 34: 11
+ 35: 5
+ 36: 15
+ 37: 7
+ 38: 8
+ 39: 5
+
+
+# Output for README
+
+* Description: A quantum chemical (QC) dataset curated to train OpenFF 2.0.0 Sage, with reparametrized Lennard-Jones (LJ) and valence parameters, the latter relevant to this dataset. This QC dataset with the OpenFF default level of theory, B3LYP-D3BJ/DZVP, is used to benchmark Sage geometries and energetics. These optimized conformer geometries where used in conjunction with the QC dataset used to train one dimensional torsional profiles. This Generation 2 dataset increases chemical diversity when compared to Generation 1, which are of value to our industry partners. Large molecules (>20 heavy atoms) were also included, including more flexible molecules and a greater degree of conformational variation which provide intramolecular interactions.
+This is the complete optimization dataset used for training OpenFF 2.0.0 Sage, consisting of the following datasets: 'OpenFF Gen 2 Opt Set 1 Roche', 'OpenFF Gen 2 Opt Set 2 Coverage', 'OpenFF Gen 2 Opt Set 3 Pfizer Discrepancy', 'OpenFF Gen 2 Opt Set 4 eMolecules  - Discrepancy', and 'OpenFF Gen 2 Opt Set 5 Bayer'.
+The following filters were applied: RecordStatusFilter(status=RecordStatusEnum.complete), ConnectivityFilter(tolerance=1.2), UndefinedStereoFilter(), ConformerRMSDFilter(max_conformers=10), and ElementFilter(allowed_elements=['H', 'C', 'N', 'O', 'S', 'P', 'F', 'Cl', 'Br', 'I'])Further information can be found in the curation scripts for the linked repositories.
+* Purpose: B3LYP-D3BJ/DZVP conformers applicable to drug-like molecules for OpenFF 2.0.0 Sage
+* Name: OpenFF Sage 2.0.0 Training Optimization Dataset v1.0
+* Number of unique molecules: 1025
+* Number of filtered molecules: 0
+* Number of conformers: 3663
+* Number of conformers (min, mean, max): 1.00, 3.53, 10.00
+* Molecular weight (min, mean, max): 76.05, 261.38, 544.64
+* Charges: -2.0, -1.0, 0.0, 1.0
+* Submitter: Jennifer A Clark
+
+## Metadata
+* Elements: {Br, C, Cl, F, H, I, N, O, P, S}
+* QC Specifications: default
+  * basis: DZVP
+  * implicit_solvent: None
+  * keywords: {}
+  * maxiter: 200
+  * method: B3LYP-D3BJ
+  * program: psi4
+  * SCF Properties:
+    * dipole
+    * quadrupole
+    * wiberg_lowdin_indices
+    * mayer_indices