HLA09357 DQB1*02:29 HLA NFT

DQB1*02:29

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0x00
IPFS of NFT metadata: 
bafybeibfvsbiccdf7k2dzln45icpww2ouj5shbu7ttwdgjxjh7pzigvuou/metadata.json
IPFS of structure file: 
bafybeici7sgq6vfjikp7qpptjax622hgm37fy3z4b4cbax7zyfbi5vgxs4/HLA09357_DQB1*02:29_predicted_with_MetaAI_for_GenesisL1.pdb

MOLNFT HLA

NFT id:
9129
HLA:
DQB1*02:29
Experimental Method:
Predicted structure
pTM:
0.783
pLDDT:
82.200

NFT data

MolNFT HLA is a sequential and structural database of HLA protein sequences from IPD-IMGT/HLA Database and corresponding structures predicted with ESMFold (MetaAI). Prediction done using open models by GenesisL1 blockchain enthusiasts and preserved as regular ERC-721 NFT tokens on GenesisL1 blockchain for public free use, research and entertainment.

https://www.ebi.ac.uk/ipd/imgt/hla/
Barker DJ, Maccari G, Georgiou X, Cooper MA, Flicek P, Robinson J, Marsh SGE
The IPD-IMGT/HLA Database
Nucleic Acids Research (2023) 51:D1053-60

https://github.com/facebookresearch/esm
Evolutionary-scale prediction of atomic level protein structure with a language model
Zeming Lin, Halil Akin, Roshan Rao, Brian Hie, Zhongkai Zhu, Wenting Lu, Nikita Smetanin, Robert Verkuil, Ori Kabeli, Yaniv Shmueli, Allan dos Santos Costa, Maryam Fazel-Zarandi, Tom Sercu, Salvatore Candido, Alexander Rives
bioRxiv 2022.07.20.500902; doi:https://doi.org/10.1101/2022.07.20.500902

MOLNFT HLA09357 DQB1*02:29 research and analysis (ICN3D with VR)

FASTA sequences

>HLA:HLA09357 DQB1*02:29 89 bp DFVCQFKGMCYFTNGTERVRLVSRSIYNREEIVRFDSDVGEFRAVTLLGLPAAEYWNSQKDILERKRAAVDRVCRHNYQLELRTTLQRR