AtomGen
Collection
Suite of datasets and pre-trained models for molecular structures focusing on transformer-based implementations.
•
10 items
•
Updated
input_ids
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[6,8,8,8,6,8,8,6,8,6,6,6,6,8,6,7,6,6,6,8,6,8,7,8,6,7,6,6,6,6,6,7,6,6,8,8,6,8,8,8,8,6,8,8,6,8,6,6,8,7(...TRUNCATED) | [[6.151000022888184,32.03499984741211,11.21399974822998],[8.92199993133545,27.312999725341797,7.6719(...TRUNCATED) | 0 | [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0(...TRUNCATED) |
[7,8,8,8,8,8,8,6,8,6,6,8,8,8,7,6,6,6,6,8,6,7,8,6,6,6,8,8,8,8,8,6,8,6,7,6,8,8,8,6,7,6,7,6,6,6,8,7,6,8(...TRUNCATED) | [[19.73200035095215,31.288999557495117,3.61899995803833],[18.854000091552734,32.36800003051758,1.299(...TRUNCATED) | 1 | [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0(...TRUNCATED) |
[7,8,8,8,8,8,6,8,6,6,8,8,6,6,8,6,7,8,6,6,8,6,7,6,6,6,8,7,6,6,8,6,6,6,8,7,6,7,7,8,6,6,6,7,6,6,8,8,6,6(...TRUNCATED) | [[19.73200035095215,31.288999557495117,3.61899995803833],[18.854000091552734,32.36800003051758,1.299(...TRUNCATED) | 0 | [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0(...TRUNCATED) |
[6,8,6,6,8,8,8,6,6,6,8,6,8,7,6,6,6,6,7,6,8,6,8,6,6,7,6,7,8,6,6,8,6,6,6,8,7,8,6,8,8,6,8,6,6,7,7,7,6,6(...TRUNCATED) | [[19.770000457763672,0.6010000109672546,3.7639999389648438],[17.91900062561035,1.8109999895095825,0.(...TRUNCATED) | 1 | [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0(...TRUNCATED) |
[6,8,6,6,6,6,6,7,6,8,6,8,6,6,7,6,7,8,6,6,8,6,6,6,8,7,8,6,8,8,6,8,6,6,7,7,7,6,6,6,6,6,8,7,6,6,6,6,7,8(...TRUNCATED) | [[19.770000457763672,0.6010000109672546,3.7639999389648438],[17.91900062561035,1.8109999895095825,0.(...TRUNCATED) | 1 | [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0(...TRUNCATED) |
[6,8,6,6,8,8,8,6,6,6,8,6,8,7,6,6,6,6,7,6,8,6,8,6,6,7,6,7,8,6,6,8,6,6,6,8,7,8,6,8,8,6,8,6,6,7,7,7,6,6(...TRUNCATED) | [[19.770000457763672,0.6010000109672546,3.7639999389648438],[17.91900062561035,1.8109999895095825,0.(...TRUNCATED) | 1 | [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0(...TRUNCATED) |
[6,8,6,6,8,8,8,6,6,6,8,6,8,7,6,6,6,6,7,6,8,6,8,6,6,7,6,7,8,6,6,8,6,6,6,8,7,8,6,8,8,6,8,6,6,7,7,7,6,6(...TRUNCATED) | [[19.770000457763672,0.6010000109672546,3.7639999389648438],[17.91900062561035,1.8109999895095825,0.(...TRUNCATED) | 1 | [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0(...TRUNCATED) |
End of preview. Expand
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PPI: Protein-Protein Interfaces
Overview
This task relates to predicting which pairs of amino acids, spanning two different proteins, will interact upon binding (when they form a complex).
Amino acids are defined as interacting if any of their heavy atoms are within 6 Angstroms from one another.
Datasets
- splits:
- DIPS-split: DIPS dataset, split by sequence identity (see add. inf.)
Format
Each entry in the dataset contains the following keys:
- ['input_ids'] The set of atomic numbers for both the proteins in the complex concatenated together.
- ['coords'] The 3D coordinates for both the proteins in the complex concatenated together.
- ['label'] 1 for interacting, 0 for not interacting.
- ['token_type_ids'] A mask that corresponds to which inputs_ids/coords belong to the two individual proteins involved in the complex (0 for protein 1 , 1 for protein 2)
Additional Information
The ensemble consists of a given protein complex, with subunits corresponding to the two individual proteins involved in the complex.
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{paszke2019advances,
title={Advances in neural information processing systems 32},
author={Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and others},
journal={Curran Associates, Inc},
pages={8024--8035},
year={2019}
}
@article{vreven2015updates,
title={Updates to the integrated protein--protein interaction benchmarks: docking benchmark version 5 and affinity benchmark version 2},
author={Vreven, Thom and Moal, Iain H and Vangone, Anna and Pierce, Brian G and Kastritis, Panagiotis L and Torchala, Mieczyslaw and Chaleil, Raphael and Jim{\'e}nez-Garc{\'\i}a, Brian and Bates, Paul A and Fernandez-Recio, Juan and others},
journal={Journal of molecular biology},
volume={427},
number={19},
pages={3031--3041},
year={2015},
publisher={Elsevier}
}
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