Q9HB96 Fanconi anemia group E protein MolNFT, Molecular NFT on GenesisL1

Fanconi anemia group E protein

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeievd4xanowiajvlhbd3i7s62vonlcl2adovynsztzo57ip5xejoay/metadata.json

IPFS of structure file:

bafybeic7aspap73vzmrzsbyak32gzaaziss5v23qw6g5zjccfb3v757mti/AF-Q9HB96-F1-model_v2.pdb

First NFT owner address (eip-55):

0x3CD694Bb4B687b1E23f95579904aDaE5a32c9FE0

First NFT owner address (bech32):

genesis18ntffw6tdpa3ugle24ueqjk6uk3je8lqvldst0

Current NFT ID #126564 owner (web3):

0x560C3688d3CACd8C45f90Cc8822C42baFa3B0548

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
126564
Accession (UniProt):
Q9HB96
Name::
Fanconi anemia group E protein
Experimental Method:
Predicted structure
Sequence source:
HOMO SAPIENS

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 Q9HB96 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9HB96|FANCE_HUMAN Fanconi anemia group E protein OS=Homo sapiens OX=9606 GN=FANCE PE=1 SV=1 MATPDAGLPGAEGVEPAPWAQLEAPARLLLQALQAGPEGARRGLGVLRALGSRGWEPFDWGRLLEALCREEPVVQGPDGRLELKPLLLRLPRICQRNLMSLLMAVRPSLPESGLLSVLQIAQQDLAPDPDAWLRALGELLRRDLGVGTSMEGASPLSERCQRQLQSLCRGLGLGGRRLKSPQAPDPEEEENRDSQQPGKRRKDSEEEAASPEGKRVPKRLRCWEEEEDHEKERPEHKSLESLADGGSASPIKDQPVMAVKTGEDGSNLDDAKGLAESLELPKAIQDQLPRLQQLLKTLEEGLEGLEDAPPVELQLLHECSPSQMDLLCAQLQLPQLSDLGLLRLCTWLLALSPDLSLSNATVLTRSLFLGRILSLTSSASRLLTTALTSFCAKYTYPVCSALLDPVLQAPGTGPAQTELLCCLVKMESLEPDAQVLMLGQILELPWKEETFLVLQSLLERQVEMTPEKFSVLMEKLCKKGLAATTSMAYAKLMLTVMTKYQANITETQRLGLAMALEPNTTFLRKSLKAALKHLGP

Q9HB96 AF NFT

MOLNFT AF v1

NFT data

MOLNFT Q9HB96 research and analysis (ICN3D with VR)

FASTA sequences

We use cookies on this site to enhance your user experience