Q9D2N4 AF NFT

Dystrobrevin alpha

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibinryx7eeisfitcpaxioihvwxohhj3my2jskfmrg3chsklhyibqe/metadata.json
IPFS of structure file: 
bafybeifyijfijhof2mjo4clvf7wwtebbrpekxk6aum2cvnrifbtend3efu/AF-Q9D2N4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x0D0A8CE69481d1cA49F4CC8CC1d359Fb141cB96c
First NFT owner address (bech32): 
genesis1p59gee55s8gu5j05ejxvr56elv2pewtvfrnesv
Current NFT ID #106615 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
106615
Accession (UniProt):
Q9D2N4
Name::
Dystrobrevin alpha
Experimental Method:
Predicted structure
Sequence source:
MUS MUSCULUS

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 Q9D2N4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9D2N4|DTNA_MOUSE Dystrobrevin alpha OS=Mus musculus OX=10090 GN=Dtna PE=1 SV=2 MIEDSGKRGNTMAERRQLFAEMRAQDLDRIRLSTYRTACKLRFVQKKCNLHLVDIWNVIEALRENALNNLDPNIELNVARLEAVLSTIFYQLNKRMPTTHQIHVEQSISLLLNFLLAAFDPEGHGKISVFAVKMALATLCGGKIMDKLRYIFSMISDSSGVMVYGRYDQFLREVLKLPTAVFEGPSFGYTEQSARSCFSQQKKVTLNGFLDTLMSDPPPQCLVWLPLLHRLANVENVFHPVECSYCHSESMMGFRYRCQQCHNYQLCQDCFWRGHAGGSHSNQHQMKEYTSWKSPAKKLTNALSKSLSCASSREPLHPMFPDQPEKPLNLAHIVPPRPVTSMNDTLFSHSVPSSGSPFITRSSPPKDSEVEQNKMLARAAPAFLKGRGIQYSLNVADRLADEHVLIGLYVNMLRNDPPCMLESSNRLDEEHRLIARYAARLAAESSSSQPTQQRSAPDISFTIDANKQQRQLIAELENKNREILQEIQRLRVEHEQASQPTPEKAQQNPTLLAELRLLRQRKDELEQRMSALQESRRELMVQLEGLMKLLKEEELKQGTQGASSPRSSPSHTISRPIPMPIRSASACPTPTHTPQDSLTGVGGDVQEAFAQSSRRNLRSDLLVAADSITNTMSSLVKELNSEVASETESTVDSEFSRPQFEDLAPSPTSEKAFLAQIHSRKPGYIHGGAASTTHGDMVPEDGDPYTQPEDGNYENESVRQLENELQLEEYLKQKLQDEAYQVSLQG