B1KRD4 AF NFT

Biosynthetic arginine decarboxylase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidqkf2ofsrbfedu4bv2q7znwqbeca2lyav5iom6gojh3isn3lhbuq/metadata.json
IPFS of structure file: 
bafybeidcxh4owlnwpuctd64u62ishyvhwg62uuza2hd2frnqiw3ld4l2jy/AF-B1KRD4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x4E86D2439266DCa1580a1734488545A520deFE4E
First NFT owner address (bech32): 
genesis1f6rdysujvmw2zkq2zu6y3p2955sdaljwfw8v9t
Current NFT ID #434195 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
434195
Accession (UniProt):
B1KRD4
Name::
Biosynthetic arginine decarboxylase
Experimental Method:
Predicted structure
Sequence source:
Shewanella woodyi (strain ATCC 51908 / MS32)

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 B1KRD4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B1KRD4|SPEA_SHEWM Biosynthetic arginine decarboxylase OS=Shewanella woodyi (strain ATCC 51908 / MS32) OX=392500 GN=speA PE=3 SV=1 MSNWSINDARTGYNVNYWSQGLYGISDEGEATVSPDPTRPECSIGLNELAKDMVKSGVNLPVLVRFPQILHHRVNSLCQAFNQAIQKYQYQADYLLVYPIKVNQQQTVVEEILASQVEKEVPQLGLEAGSKPELMAVLAMAQKASSVIICNGYKDIEYIRLALIGEKLGHKVYIVLEKLSELKTVLEESKKLGVTPRLGLRVRLAFQGKGKWQASGGEKSKFGLSASQVLTVIESLKSEEMLDSLQLLHFHLGSQIANIRDIRQGVSEAGRFYCELQKLGANVKCFDVGGGLAVDYDGTRSQSSSSMNYGLTEYANNIVSVLTDICNEYEQPMPRIISESGCYLTAHHAVLITDVIGTEAYKPEDIQPPAEDAPQLLHNMWHSWNEISGRADQRALIEIYHDCQSDLTEVHSLFALGQLSLTDRAWAEQVNLRVCHELQGVMSSKYRFHRPIIDELTEKLADKFFVNFSLFQSLPDAWGIDQVFPIMPLSGLDKAPERRAVMLDITCDSDGTIDQYVDGQGIETTLPVPAWSAESPYLIGFFLVGAYQEILGDMHNLFGDTNSAVIRLDDDGRTNIESVLAGDTVADVLRYVNLDAVSFMRTYEELVNKHIQEDERANILEELQLGLKGYTYLEDFS