P35612 AF NFT

Beta-adducin

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihtjfhxc3dpt2xk5oid2ixl3jjhtd3dto42brc6vh5eedwfm2d7ri/metadata.json
IPFS of structure file: 
bafybeid64opofu4lpj3ivzhbcajhzuowrdkevjkqqwiemxxej4oyymp5im/AF-P35612-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xBeB220F0B5b0C48F46B5DDd3E3b071BC0827f8D6
First NFT owner address (bech32): 
genesis1h6ezpu94krzg7344mhf78vr3hsyz07xk78k92g
Current NFT ID #9613 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
9613
Accession (UniProt):
P35612
Name::
Beta-adducin
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 P35612 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P35612|ADDB_HUMAN Beta-adducin OS=Homo sapiens OX=9606 GN=ADD2 PE=1 SV=3 MSEETVPEAASPPPPQGQPYFDRFSEDDPEYMRLRNRAADLRQDFNLMEQKKRVTMILQSPSFREELEGLIQEQMKKGNNSSNIWALRQIADFMASTSHAVFPTSSMNVSMMTPINDLHTADSLNLAKGERLMRCKISSVYRLLDLYGWAQLSDTYVTLRVSKEQDHFLISPKGVSCSEVTASSLIKVNILGEVVEKGSSCFPVDTTGFCLHSAIYAARPDVRCIIHLHTPATAAVSAMKWGLLPVSHNALLVGDMAYYDFNGEMEQEADRINLQKCLGPTCKILVLRNHGVVALGDTVEEAFYKIFHLQAACEIQVSALSSAGGVENLILLEQEKHRPHEVGSVQWAGSTFGPMQKSRLGEHEFEALMRMLDNLGYRTGYTYRHPFVQEKTKHKSEVEIPATVTAFVFEEDGAPVPALRQHAQKQQKEKTRWLNTPNTYLRVNVADEVQRSMGSPRPKTTWMKADEVEKSSSGMPIRIENPNQFVPLYTDPQEVLEMRNKIREQNRQDVKSAGPQSQLLASVIAEKSRSPSTESQLMSKGDEDTKDDSEETVPNPFSQLTDQELEEYKKEVERKKLELDGEKETAPEEPGSPAKSAPASPVQSPAKEAETKSPLVSPSKSLEEGTKKTETSKAATTEPETTQPEGVVVNGREEEQTAEEILSKGLSQMTTSADTDVDTSKDKTESVTSGPMSPEGSPSKSPSKKKKKFRTPSFLKKSKKKEKVES