A1RIY0 AF NFT

Methionine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigut7m5rgeypelnsmv6rl2xf6iqir46xmrl6n74lrbrr6ldqlxcaq/metadata.json
IPFS of structure file: 
bafybeiextr54fxdnl27vb5eoth2fjsuj3765qcshg3el4j5utiflqhpczu/AF-A1RIY0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x4E86D2439266DCa1580a1734488545A520deFE4E
First NFT owner address (bech32): 
genesis1f6rdysujvmw2zkq2zu6y3p2955sdaljwfw8v9t
Current NFT ID #450982 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
450982
Accession (UniProt):
A1RIY0
Name::
Methionine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Shewanella sp. (strain W3-18-1)

NFT data

MolNFT AF v1 is an AlphaFold database of AI predicted Swiss-Prot protein sequences preserved as regular ERC-721 NFT tokens on GenesisL1 blockchain for public free use, research and entertainment:

https://alphafold.ebi.ac.uk/
Jumper, J., Evans, R., Pritzel, A. et al. Highly accurate protein structure prediction with AlphaFold. 
Nature 596, 583–589 (2021). https://doi.org/10.1038/s41586-021-03819-2

MOLNFT A1RIY0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A1RIY0|SYM_SHESW Methionine--tRNA ligase OS=Shewanella sp. (strain W3-18-1) OX=351745 GN=metG PE=3 SV=1 MATSQRKILVTSALPYANGPIHLGHMLEYIQTDIWSRYQKLRGHECHYICADDAHGTPIMLKAQQLGLAPEEMIAQVNKEHQQDFADFNIAFDNYHSTHSDENRVLASDIYLKLRTNGYIKSKSISQLFDPEKSMFLPDRFVKGTCPKCKSPDQYGDNCDACGATYSPTELINPKSAVSGATPVMKDTEHFFFDLPAFEGMLKEWTRSGALQTEMANKLDEWFEQGLQQWDITRDAPYFGFEIPDAPGKYFYVWLDAPIGYMGSFKNLCDKRPELSFDEFWAKDSKAEVYHFIGKDIVYFHSLFWPAMLHGSGYRQPNSVYAHGYVTVNGAKMSKSKGTFIKARTYLDHLDPEYLRYYYAAKLSSRIDDLDLNLEDFAQRVNSDLVGKLVNLASRTAGFITKRFDGKLAKIADTTLTEAFLAKQEQIAEFYETREYGKAMREIMALADIANGFVADAAPWQMVKQDDQQEAAHQVCSNALNLFRILVTYLKPVLPRLAQDVEAFFQQTLTWDGLAQDMAGHEISPFKAMMQRVELDKVNAMVADSKENLQVTADVPKTAKPEKTVESSNVSSEPLVDDPISETINFDDFAKIDLRIARIVKAEHVAEADKLLKLQLDIGGETRQVFAGIKSAYSPEDLEGKLTVMVANLAPRKMRFGMSEGMVLAAGPGGSDLWILEPHEGAQPGMRVK