Q05764 AF NFT

Beta-adducin

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeia4mklf4y3wnjovpzcohh3iuou5wwomerc6sexil6xwszq2twmogq/metadata.json
IPFS of structure file: 
bafybeiaq4zldd7aaidyje3wogszbekkdxru73srxo7fautmmrkajr2imsu/AF-Q05764-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7b996410Da79507A3D80841daE0455C84DAf7E51
First NFT owner address (bech32): 
genesis10wvkgyx609g850vqssw6upz4epx67lj3eh845m
Current NFT ID #9649 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
9649
Accession (UniProt):
Q05764
Name::
Beta-adducin
Experimental Method:
Predicted structure
Sequence source:
RATTUS NORVEGICUS

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 Q05764 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q05764|ADDB_RAT Beta-adducin OS=Rattus norvegicus OX=10116 GN=Add2 PE=1 SV=4 MSEDTVPEAASPPPSQGQHYFDRFSEDDPEYLRLRNRAADLRQDFNLMEQKKRVTMILQSPSFREELEGLIQEQMKKGNNSSNIWALRQIADFMASTSHAVFPASSMNFSMMTPINDLHTADSLNLAKGERLMRCKISSVYRLLDLYGWAQLSDTYVTLRVSKEQDHFLISPKGVSCSEVTASSLIKVNILGEVVEKGSSCFPVDTTGFSLHSAIYAARPDVRCAIHLHTPATAAVSAMKCGLLPVSHNALLVGDMAYYDFNGEMEQEADRINLQKCLGPTCKILVLRNHGMVALGDTVEEAFYKVFHLQAACEVQVSALSSAGGTENLILLEQEKHRPHEVGSVQWAGSTFGPMQKSRLGEHEFEALMRMLDNLGYRTGYTYRHPFVQEKTKHKSEVEIPATVTAFVFEEDGVPVPALRQHAQKQQKEKTRWLNTPNTYLRVNVADEVQRNMGSPRPKTTWMKADEVEKSSSGMPIRIENPNQFVPLYTDPQEVLDMRNKIREQNRQDIKSAGPQSQLLASVIAEKSRSPSTESQLASKGDADTKDELEETVPNPFSQLTDQELEEYKKEVERKKLEQEQEGEKDAATEEPGSPVKSTPASPVQSPTRAGTKSPAVSPSKASEDAKKTEVSEANTEPEPEKPEGVVVNGKEEEPCVEEVLSKGPGQMTTNADTDGDSYKDKTESVTSGPLSPEGSPSKSPSKKKKKFRTPSFLKKSKKKEKVES