B0TQX3 AF NFT

Biosynthetic arginine decarboxylase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeicnuurpucrfnsw3xhpmgoykovfgpc3k5imrxdiwsbaog7eimobp3a/metadata.json
IPFS of structure file: 
bafybeiezyownbzhmwdflyyec7w3wks27nohbobyt3cwfc4egyrqbhsfcsi/AF-B0TQX3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x78Cc7f9BF18AF8279e492D45EE7Fe9d7cC6f6D07
First NFT owner address (bech32): 
genesis10rx8lxl33tuz08jf94z7ullf6lxx7mg8844d65
Current NFT ID #434184 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
434184
Accession (UniProt):
B0TQX3
Name::
Biosynthetic arginine decarboxylase
Experimental Method:
Predicted structure
Sequence source:
Shewanella halifaxensis (strain HAW-EB4)

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 B0TQX3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B0TQX3|SPEA_SHEHH Biosynthetic arginine decarboxylase OS=Shewanella halifaxensis (strain HAW-EB4) OX=458817 GN=speA PE=3 SV=1 MSNWSIDDARASYNVNHWSQGLYGISDDGEVTVSPDPSRPECKIGLNEMAKDMVKSGVALPVLVRFPQILHHRVNSLCQAFNQAIQKYQYENDYLLVYPIKVNQQQTVVEEILASQVEKEVPQLGLEAGSKPELMAVLAMAQKASSVIICNGYKDKEYIRLALIGEKLGHKVYIVLEKISELKVVLEQAKELGVTPRLGLRVRLAFQGKGKWQASGGEKSKFGLSAAQVLQVITSLKQENMLDSLELLHFHLGSQIANIRDIRQGVSEAGRFYCELMKLGANVKCFDVGGGLAVDYDGTRSQSSHSMNYGLTEYANNIVSVLTDMCKEYEQPMPRIISESGRYLTAHHAVLLTDVIGTEAYKPEDIQPPAEDAPQLLHNMWQSWVEVSGKADQRALIEIFHDCQSDLTEVHSLFAVGQVGLAERAWAEQVNLRVCYELQGSMSAKYRFHRPIIDELNEKLADKFFVNFSLFQSLPDAWGIDQVFPVMPLSGLDKAPESRAVMLDITCDSDGTIDQYVDGQGIETTLPVPAWTQESPYLIGFFLVGAYQEILGDMHNLFGDTNSAVVRLDEDARTNVESVLAGDTVADVLRYVNLDAVSFMRTYEELVNKHIAEDERANILEELQLGLKGYTYLEDFS