AtomGen
Collection
Suite of datasets and pre-trained models for molecular structures focusing on transformer-based implementations. • 10 items • Updated
Search is not available for this dataset
input_ids sequencelengths 53 8.77k | coords sequencelengths 53 8.77k | labels sequencelengths 4 4 |
|---|---|---|
[
7,
6,
6,
8,
6,
6,
1,
7,
6,
6,
1,
1,
7,
1,
1,
7,
7,
6,
6,
8,
1,
6,
1,
8,
7,
6,
6,
8,
6,
6,
6,
7,
6,
6,
8,
1,
6,
1,
8,
7,
6,
6,
8,
1,
6,
6,
6,
8,
8,
7,
6,
6,
8,
1,
7,
6,
6,
8,
1,
6,
1,
8,
7,
6... | [
[
21.368,
138.819,
-45.535
],
[
20.524,
137.966003,
-46.300999
],
[
20.006001,
136.897003,
-45.376999
],
[
20.790001,
136.229996,
-44.709
],
[
21.291,
137.378006,
-47.487
],
[
21.233999,
136.065002,
-49.625
],
[
20.0... | [
10.449000000000002,
0.4806,
0.33799999999999997,
0.5578
] |
[
7,
6,
6,
8,
1,
1,
1,
6,
16,
6,
6,
7,
6,
6,
8,
1,
6,
1,
8,
6,
7,
6,
6,
8,
1,
6,
1,
8,
7,
6,
6,
8,
1,
6,
1,
8,
7,
6,
6,
8,
1,
6,
6,
6,
8,
8,
7,
6,
6,
8,
6,
6,
6,
7,
6,
6,
8,
1,
6,
7,
6,
6,
8,
... | [
[
36.029999,
6.808,
48.756001
],
[
35.153999,
7.633,
49.619999
],
[
35.175999,
7.103,
51.013
],
[
36.073002,
6.349,
51.387001
],
[
36.118,
7.008,
47.882999
],
[
35.862999,
5.93,
48.653999
],
[
36.907001,
6.735,
... | [
5.604,
0.544,
0.3363,
0.6372
] |
[
7,
6,
6,
8,
1,
1,
1,
6,
16,
6,
6,
7,
6,
6,
8,
1,
6,
1,
8,
6,
7,
6,
6,
8,
1,
6,
1,
8,
7,
6,
6,
8,
1,
6,
1,
8,
7,
6,
6,
8,
1,
6,
6,
6,
8,
8,
7,
6,
6,
8,
6,
6,
6,
7,
6,
6,
8,
1,
6,
7,
6,
6,
8,
... | [
[
0.601,
-0.265,
1.1
],
[
1.492,
-0.001,
-0.027
],
[
2.093,
1.402,
0.022
],
[
2.26,
2.108,
-0.996
],
[
0.191,
-1.063,
1.172
],
[
-0.127,
0.248,
1.227
],
[
0.916,
-0.224,
1.942
],
[
0.75,
-0.189,
... | [
13.950999999999999,
0.2254,
0.1356,
0.28
] |
[
7,
6,
6,
8,
1,
1,
1,
6,
16,
6,
6,
7,
6,
6,
8,
1,
6,
1,
8,
6,
7,
6,
6,
8,
1,
6,
1,
8,
7,
6,
6,
8,
1,
6,
1,
8,
7,
6,
6,
8,
1,
6,
6,
6,
8,
8,
7,
6,
6,
8,
6,
6,
6,
7,
6,
6,
8,
1,
6,
7,
6,
6,
8,
... | [
[
0.654,
-0.855,
-0.753
],
[
1.465,
0.021,
0.028
],
[
1.869,
1.34,
-0.649
],
[
2.574,
1.386,
-1.657
],
[
0.385,
-1.643,
-0.412
],
[
0.96,
-1.171,
-1.538
],
[
-0.15,
-0.58,
-1.048
],
[
2.751,
-0.68... | [
16.677,
0.1972,
0.1215,
0.2173
] |
[
7,
6,
6,
8,
6,
1,
8,
7,
6,
6,
8,
1,
6,
6,
6,
8,
8,
7,
6,
6,
8,
1,
7,
6,
6,
8,
1,
6,
1,
8,
7,
6,
6,
8,
1,
6,
7,
6,
6,
8,
1,
6,
6,
8,
8,
7,
6,
6,
8,
1,
6,
6,
8,
1,
1,
7,
7,
6,
6,
8,
1,
6,
7,
6... | [
[
-11.482,
-4.26,
42.171001
],
[
-12.178,
-5.36,
42.799
],
[
-12.704,
-4.894,
44.139999
],
[
-11.999,
-4.118,
44.759998
],
[
-11.248,
-6.566,
42.951
],
[
-12.566,
-7.86,
43.208
],
[
-11.894,
-7.625,
43.634998... | [
3.2569999999999997,
0.7465,
0.5528,
0.8081
] |
[7,6,6,8,6,1,8,6,7,6,6,8,1,6,1,8,7,6,6,8,1,6,1,8,7,6,6,8,1,6,6,6,8,8,7,6,6,8,6,6,6,7,6,6,8,1,6,7,6,6(...TRUNCATED) | [[21.593,58.507999,56.400002],[20.122999,58.375999,56.43],[19.702999,57.470001,55.252998],[20.209,57(...TRUNCATED) | [
2.334,
0.7201,
0.5264,
0.7998
] |
[7,6,6,8,1,1,1,6,16,6,6,7,6,6,8,1,6,1,8,6,7,6,6,8,1,6,1,8,7,6,6,8,1,6,1,8,7,6,6,8,1,6,6,6,8,8,7,6,6,(...TRUNCATED) | [[57.448002,66.815002,-14.777],[56.563,65.667,-14.523],[55.078999,66.079002,-14.451],[54.207001,65.2(...TRUNCATED) | [
4.289,
0.6901,
0.4982,
0.7683
] |
[7,6,6,8,6,1,8,7,6,6,8,1,6,1,8,7,6,6,8,1,6,6,6,8,8,7,6,6,8,6,6,6,7,6,6,8,1,6,7,6,6,8,1,6,6,7,6,6,1,7(...TRUNCATED) | [[107.360001,80.632004,254.507004],[105.973,80.866997,254.927002],[105.07,79.643997,254.699005],[103(...TRUNCATED) | [
4.453,
0.6813,
0.4912,
0.7618
] |
[7,6,6,8,6,6,6,7,6,6,8,1,6,6,6,6,1,1,1,7,7,6,6,8,1,6,6,1,7,6,6,1,1,7,1,1,7,7,6,6,8,1,6,1,8,7,6,6,8,6(...TRUNCATED) | [[53.286999,18.6,22.219999],[52.105999,18.115999,21.486],[51.719002,19.145,20.441999],[51.516998,20.(...TRUNCATED) | [
3.185,
0.6725,
0.4665,
0.7666
] |
[7,6,6,8,1,1,1,6,16,6,6,7,6,6,8,1,6,1,8,6,7,6,6,8,1,6,1,8,7,6,6,8,1,6,1,8,7,6,6,8,1,6,6,6,8,8,7,6,6,(...TRUNCATED) | [[-0.149,-0.053,1.116],[1.319,0.11,0.684],[1.93,-1.287,0.411],[2.921,-1.429,-0.305],[-0.644,0.673,1.(...TRUNCATED) | [
17.349,
0.1444,
0.0757,
0.1905
] |
End of preview. Expand
in Data Studio
PSR: Protein Structure Ranking
Overview
This task relates to predicting the three-dimensional structure of a protein molecule, given its sequence. A total of around 700 protein targets are included, which consist of protein targets from Critical Assessment of Structure Prediction (CASP) 5-13.
We phrase this problem as decoy ranking. For each protein target, we include its decoys sets compiled from the CASP decoy sets released for the Model Quality Assessment (MQA). We relax those structures with the SCWRL4 software (Krivov and Dunbrack, 2019) to improve side-chain conformations. For each decoy, we calculate the RMSD, TM-score, GDT_TS, and GDT_HA scores to the experimentally determined structure using the TM-score software (Zhang and Skolnick, 2007).
Datasets
- splits:
- split-by-year: This dataset contains data in the CASP dataset, but is split temporally. More specifically, we randomly split the targets in CASP5-10 and randomly sample 50 decoys for each target to generate the training and validation sets (508 targets for training, 56 targets for validation), and use the CASP11 Stage 2 as test set (85 targets total, with 150 decoys for each target, excluding the native structures).
Citation Information
@article{townshend2020atom3d,
title={Atom3d: Tasks on molecules in three dimensions},
author={Townshend, Raphael JL and V{\"o}gele, Martin and Suriana, Patricia and Derry, Alexander and Powers, Alexander and Laloudakis, Yianni and Balachandar, Sidhika and Jing, Bowen and Anderson, Brandon and Eismann, Stephan and others},
journal={arXiv preprint arXiv:2012.04035},
year={2020}
}
@article{kryshtafovych2019critical,
title={Critical assessment of methods of protein structure prediction (CASP)—Round XIII},
author={Kryshtafovych, Andriy and Schwede, Torsten and Topf, Maya and Fidelis, Krzysztof and Moult, John},
journal={Proteins: Structure, Function, and Bioinformatics},
volume={87},
number={12},
pages={1011--1020},
year={2019},
publisher={Wiley Online Library}
}
- Downloads last month
- 40
Size of downloaded dataset files:
1.5 GB
Size of the auto-converted Parquet files:
1.5 GB
Number of rows:
44,214