A0KMV4 AF NFT

N-succinylarginine dihydrolase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibmb2y4wtmftmp3jtqunvwk4wx45cexc3mvbt4suboubccsa26wnu/metadata.json
IPFS of structure file: 
bafybeig4im3hklqjfga63xqjmhxcimxmneanj226kkt7ygvdxnufgl4cmm/AF-A0KMV4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x403EcfA800ce17640bdC169169720B7Bf7e06A2b
First NFT owner address (bech32): 
genesis1gqlvl2qqectkgz7uz6gkjust00m7q63trkhld3
Current NFT ID #29850 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
29850
Accession (UniProt):
A0KMV4
Name::
N-succinylarginine dihydrolase
Experimental Method:
Predicted structure
Sequence source:
Aeromonas hydrophila subsp. hydrophila (strain ATCC 7966 / DSM 30187 / BCRC 13018 / CCUG 14551 / JCM 1027 / KCTC 2358 / NCIMB 9240 / NCTC 8049)

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 A0KMV4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A0KMV4|ASTB_AERHH N-succinylarginine dihydrolase OS=Aeromonas hydrophila subsp. hydrophila (strain ATCC 7966 / DSM 30187 / BCRC 13018 / CCUG 14551 / JCM 1027 / KCTC 2358 / NCIMB 9240 / NCTC 8049) OX=380703 GN=astB PE=3 SV=1 MKHFEVNFDGLVGPTHNYAGLSYGNVASQNNAKEASNPKEAAKQGLRKMKALTELGMTQGVLAPQERPDLATLRRLGFTGNDASVLAQAAKQAPAVLAACYSASSMWTANAATVSPSADTQDGRIHFTPANLTNKFHRSLEPEVTGRILRAVFNNDRHFYHHQHLPENDHFGDEGAANHTRLCRAYGESGVELFVYGRSAFDVSQPAPKRYPARQTLEASQAIARLHGLGDESAVFIQQNPDVIDQGVFHNDVIAVGNQNVLFFHQQAFLNTASALAEVRTKFGDGELHFIEVPTAEVSVQDAVKSYLFNTQILTLPSGEMAIIAPTECRDNPAVSAYLTKLVTLGTPIKGVHYMDVKQSMRNGGGPACLRLRVAMNDTELAAVNPACLITDSQFARLDGWVDRHYRDSLALDDLRDPALVMESRTALDELTQILKLGSVYPFQR