Q5AR49 AF NFT

FAD-linked oxidoreductase asqF

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiegi4kp3okzlx5fpaffzhsadbsl6sc5a6umzinuj35dvhwzabgjpq/metadata.json
IPFS of structure file: 
bafybeifba3dr5nfmqckrkt6ecxf7kbnzpjdsrmoni46y5km4ov75yyspxu/AF-Q5AR49-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x79a905d858Ce72991FD6E7a9C6498620f42E146D
First NFT owner address (bech32): 
genesis10x5stkzceeefj87ku75uvjvxyr6zu9rds9d8xj
Current NFT ID #29101 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
29101
Accession (UniProt):
Q5AR49
Name::
FAD-linked oxidoreductase asqF
Experimental Method:
Predicted structure
Sequence source:
EMERICELLA NIDULANS (STRAIN FGSC A4 / ATCC 38163 / CBS 112.46 / NRRL 194 / M139)

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 Q5AR49 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q5AR49|ASQF_EMENI FAD-linked oxidoreductase asqF OS=Emericella nidulans (strain FGSC A4 / ATCC 38163 / CBS 112.46 / NRRL 194 / M139) OX=227321 GN=asqH PE=3 SV=1 MALFRLSAAIVVIFLYIWSPSQRIQCRCRSFERCWPSQQDWSALNNSISGHLVNPRPVAYVCHDPDFDHDACEHVRYMANNSLWRASMPGALQNTVWESSLVSTQTCLPFSAREQPCNQGRIPLYAAVVESKKEVQTAVRFARKYNLRLVIRNTGHDGAGSSSGPESFQIFTHRLNSILYHSNFCPGGSHSKYQTCAGPAVSIGAGVMFRDLYARGAERGFVVTGGDSGTVGAAGGFIQGGGVPAFMGYTWGLAVDNVLEFEVVVATGQLVIANADENADLFWALRGGGGGSFGIVVRVTMRTYPDLPTLKGELTVSGNRHDPSFWTEDIAGLLNALRAFNHLDAPGVFRLIQTSAKGSISAVLEVYLLNRTLAEDLTRMMGPILGTSRRKYNISPITVGKISSFANPNEPTITEFFGSTILSRNFFESPNGPLVMAKRMAAINLDPGDGLLTSNLGGRINNENSDLPLHPAWRSSAHLVSLVVNVDTSLRARERAMVRLTDELMPMLYAIDSSQWVSYSNMGNPNEPDFKERYWGMRNYRRLVSIKKKWDPKDLFIARVGVRSDGWDSEGMCRT