HLA02017 DRB1*07:09 HLA NFT

DRB1*07:09

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0x00
IPFS of NFT metadata: 
bafybeidf2g5dmkg4xbvnpokdjigaji4pbok2uqxulkoy55ftohf53jf23e/metadata.json
IPFS of structure file: 
bafybeih6quoypc2wjec4uo24qwy42ql24tretlhq6ktwlpz3aod6p5exna/HLA02017_DRB1*07:09_predicted_with_MetaAI_for_GenesisL1.pdb

MOLNFT HLA

NFT id:
1918
HLA:
DRB1*07:09
Experimental Method:
Predicted structure
pTM:
0.489
pLDDT:
76.100

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 HLA02017 DRB1*07:09 research and analysis (ICN3D with VR)

FASTA sequences

>HLA:HLA02017 DRB1*07:09 266 bp MVCLKLPGGSCMAALTVTLMVLSSPLALAGDTQPRFLWQGKYKCHFFNGTERVQFLERFFYNQEEFVRFDSDVGEYRAVTELGRPVAESWNSQKDILEDRRGQVDTVCRHNYGVGESFTVQRRVHPEVTVYPAKTQPLQHHNLLVCSVSGFYPGSIEVRWFRNGQEEKAGVVSTGLIQNGDWTFQTLVMLETVPRSGEVYTCQVEHPSVMSPLTVEWRARSESAQSKMLSGVGGFVLGLLFLGAGLFIYFRNQKGHSGLQPTGFLS