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AEX-2-1_FLP-13-3
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AEX-2-1_FLP-13-4
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AEX-2-1_FLP-13-5
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AEX-2-1_FLP-13-6
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AEX-2-1_FLP-13-7
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AEX-2-1_FLP-14-1
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AEX-2-1_FLP-14-2
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AEX-2-1_FLP-15-1
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AEX-2-1_FLP-15-2
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AEX-2-1_FLP-15-3
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AEX-2-1_FLP-16-1
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AEX-2-1_FLP-16-2
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AEX-2-1_FLP-17-1
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AEX-2-1_FLP-17-2
|
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AEX-2-1_FLP-17-3
|
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AEX-2-1_FLP-17-4
|
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AEX-2-1_FLP-18-1
|
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AEX-2-1_FLP-18-2
|
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AEX-2-1_FLP-18-3
|
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AEX-2-1_FLP-18-4
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AEX-2-1_FLP-18-5
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AEX-2-1_FLP-18-6
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AEX-2-1_FLP-18-7
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AEX-2-1_FLP-18-8
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AEX-2-1_FLP-19-1
|
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AEX-2-1_FLP-19-2
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AEX-2-1_FLP-2-1
|
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AEX-2-1_FLP-2-2
|
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AEX-2-1_FLP-20-1
|
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AEX-2-1_FLP-20-2
|
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AEX-2-1_FLP-20-3
|
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AEX-2-1_FLP-21-1
|
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AEX-2-1_FLP-22-1
|
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327,
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AEX-2-1_FLP-23-1
|
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171,
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AEX-2-1_FLP-23-2
|
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171
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333,
77
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[
77,
333
]
] |
AEX-2-1_FLP-23-3
|
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AEX-2-1_FLP-24-1
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AEX-2-1_FLP-25-1
|
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AEX-2-1_FLP-25-2
|
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AEX-2-1_FLP-26-1
|
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AEX-2-1_FLP-26-2
|
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AEX-2-1_FLP-26-3
|
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AEX-2-1_FLP-26-4
|
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AEX-2-1_FLP-26-5
|
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331,
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AEX-2-1_FLP-27-1
|
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327,
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AEX-2-1_FLP-27-3
|
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AEX-2-1_FLP-27-4
|
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255,
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330,
164
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[
252,
358
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] |
AEX-2-1_FLP-28-1
|
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164,
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] |
AEX-2-1_FLP-3-1
|
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329
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255,
323
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231,
328
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] |
AEX-2-1_FLP-3-2
|
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235
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166
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AEX-2-1_FLP-3-3
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AEX-2-1_FLP-3-4
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AEX-2-1_FLP-3-5
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AEX-2-1_FLP-3-6
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AEX-2-1_FLP-3-7
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AEX-2-1_FLP-3-8
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AEX-2-1_FLP-3-9
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AEX-2-1_FLP-32-1
|
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AEX-2-1_FLP-33-1
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AEX-2-1_FLP-33-2
|
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AEX-2-1_FLP-34-1
|
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252,
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AEX-2-1_FLP-34-2
|
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AEX-2-1_FLP-34-3
|
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AEX-2-1_FLP-34-4
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AEX-2-1_FLP-4-1
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AEX-2-1_FLP-4-2
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AEX-2-1_FLP-5-1
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AEX-2-1_FLP-5-2
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AEX-2-1_FLP-5-3
|
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AEX-2-1_FLP-6-1
|
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AEX-2-1_FLP-6-2
|
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AEX-2-1_FLP-7-1
|
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AEX-2-1_FLP-7-2
|
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AEX-2-1_FLP-7-3
|
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AEX-2-1_FLP-7-4
|
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332,
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] |
AEX-2-1_FLP-7-5
|
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158
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171,
329
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] |
AEX-2-1_FLP-8-1
|
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325,
162
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92
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327,
231
]
] |
AEX-2-1_FLP-8-2
|
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327
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327,
92
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[
95,
327
]
] |
AEX-2-1_FLP-9-1
|
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326,
171
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171,
328
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] |
AEX-2-1_FLP-9-2
|
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327
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[
259,
326
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] |
AEX-2-1_NLP-1-1
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DeorphaNN
DeorphaNN is a graph neural network that predicts peptide agonists for G protein-coupled receptors (GPCRs) by integrating active-state GPCR-peptide predicted structures, interatomic interactions, and deep learning protein representations.
Dataset Details
GPCR-peptide complexes from the nematode, C. elegans.
Dataset Description
Each of the 20035 GPCR-peptide complexes were run through AlphaFold-Multimer with active state templates. This repo contains the relaxed predicted strucutre of the model with the highest peptide pLDDT per GPCR-peptide complex, as well as regions of the pair representation averaged across all five models. The pair representation is processed to include a GPCR and peptide-specific region ({GPCR}_gpcr_T.hdf5 and {GPCR}_pep_T.hdf5) and the interaction region of the pair representation ({GPCR}_interaction.hdf5)
Dataset Sources
Beets et al. Cell Reports, 2023
Code
The DeorphaNN repo can be found at https://github.com/Zebreu/DeorphaNN
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