E3RP32 AF NFT

Nucleolar protein 9

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibzpok445zlsg6utd3h2e6o5vquwc6h4z2bhaanslmlgyjwjmiljy/metadata.json
IPFS of structure file: 
bafybeihvxvdtvidm4prcw6jcxcuuim6dswd7vhmjgiw56wtgldnwjkbt74/AF-E3RP32-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x84eb910c3679c45BCF3d993cb26DBa05DC144f1f
First NFT owner address (bech32): 
genesis1sn4ezrpk08z9hneany7tymd6qhwpgncllzh6x8
Current NFT ID #267377 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
267377
Accession (UniProt):
E3RP32
Name::
Nucleolar protein 9
Experimental Method:
Predicted structure
Sequence source:
Pyrenophora teres f. teres (strain 0-1)

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 E3RP32 research and analysis (ICN3D with VR)

FASTA sequences

>sp|E3RP32|NOP9_PYRTT Nucleolar protein 9 OS=Pyrenophora teres f. teres (strain 0-1) OX=861557 GN=nop9 PE=3 SV=1 MPKEHKKRGRREDQKKRKRDHDDESASKRSRKEDVDHVQAENPLQHVANHVPRQDAAPFYGMLDEQEQEYFKKADEMLELNQFESPEDRRIFLASVCKEAEGKELKMATSQTSRLLERLILLASEDQLKSLFQTFSGHFLNLVQNRFASHCCETLFIKAASAVSQENASIKTEALNTPPASDPDEIIVSMENLFLYTLGELEGNIGFLMTEKYASHVLRVLLVILSGEPLEKQAKSVTQSKKKEKVTVSGAGDERILEKRVVPQSFLEALEKVISDSVSGIEPHYLRSLAIHPLGGPTLQLLLKLELSHFGKSRAKDEKSIIHRLLPDNPIAEGTESAILINGLVYDSVGSHLLETIIEHAPGKLFKQIYGEFFKERMGSLARNEIAGYVVGRILERLGKDDLEEAMRQIVDQIPSLVERNRTAPIKTLIERCVAREVDCSPIKAQLETAYAGPHGFEVTRILKLNEDDGKPRARHGESNEKVHGSLLAQTMMTVDGPLGQLVFDSLANLSPELSIQLARDGTASRTLQAALVSRNATVIFRRKMIQQFYGKIGELALDPKASHVVDAIWYGTVGLAFIRERIAEELAENENSLRESQVGRKVWKNWQMDLYKRRRNDWVAQARTTAGNEVFQSFPDESQSDAAAPARNHRTSRHMSAIELARQKFAAAKAAQAKDGKKPKKGSNRTNGSSETPKSLVAQ