A4Y5Y9 AF NFT

Biosynthetic arginine decarboxylase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiem7rkyyqt3gizkkik7utcn6qaa5y2r342s2dzyi3kzg4nd4rr3ni/metadata.json
IPFS of structure file: 
bafybeihgzpmgdru5ser5qbyx7cozmthvkjn7ugj4l6h3oxsixqzfmuy3vm/AF-A4Y5Y9-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x78Cc7f9BF18AF8279e492D45EE7Fe9d7cC6f6D07
First NFT owner address (bech32): 
genesis10rx8lxl33tuz08jf94z7ullf6lxx7mg8844d65
Current NFT ID #434188 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
434188
Accession (UniProt):
A4Y5Y9
Name::
Biosynthetic arginine decarboxylase
Experimental Method:
Predicted structure
Sequence source:
Shewanella putrefaciens (strain CN-32 / ATCC BAA-453)

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 A4Y5Y9 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A4Y5Y9|SPEA_SHEPC Biosynthetic arginine decarboxylase OS=Shewanella putrefaciens (strain CN-32 / ATCC BAA-453) OX=319224 GN=speA PE=3 SV=1 MNDWSIDDARAGYNVTHWSQGFYGISDQGEVTVSPDPKNPEYKIGLNELAKDMVKAGVALPVLVRFPQILHHRVNSLCQAFDQAIQKYEYQADYLLVYPIKVNQQQTVVEEILASQASKEVPQLGLEAGSKPELMAVLAMAQKASSVIVCNGYKDNEYIRLALIGEKLGHKVYIVLEKLSELKMVLAESKRLGVTPRLGLRARLAFQGKGKWQASGGEKSKFGLSAAQILTVVDQLKQNDMLDSLQLLHFHLGSQIANIRDIRQGVSEAGRFYCELRELGASVNCFDVGGGLAVDYDGTRSQSNNSMNYGLTEYANNIVNVLTDICNEYAQPMPRIISESGRYLTAHHAVLITDVIGTEAYQPENIQPPAEESPQLLHNMWHSWSEISGRADQRALIEIYHDSQSDLQEAQSLFALGQLSLAERAWAEQANLRVCHEVQGLLSTKNRYHRPIIDELNEKLADKFFVNFSLFQSLPDAWGIDQVFPVLPLSGLDKAPERRAVMLDITCDSDGIVDQYVDGQGIETTLPVPAWSAESPYLIGFFLVGAYQEILGDMHNLFGDTNSAVVRIEENGVTNIESVLAGDTVADVLRYVNLDAVAFMRTYEELVNLHIEEDERAQILEELQVGLKGYTYLEDFS