P97878 AF NFT

Exocyst complex component 5

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiardm7sjzmsxwqkjbgoss2adjkwhrv6yjsb7va52mhaykdqspkn6i/metadata.json
IPFS of structure file: 
bafybeihntn6y5gvc2i4c6n6aczxavedylqefmb4mieirxvnnqi2nss6j3q/AF-P97878-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x43c3Fe0a204231f7E4956aa82BbafBdc59917943
First NFT owner address (bech32): 
genesis1g0pluz3qggcl0ey4d25zhwhmm3vez72rnqhwas
Current NFT ID #122537 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
122537
Accession (UniProt):
P97878
Name::
Exocyst complex component 5
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 P97878 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P97878|EXOC5_RAT Exocyst complex component 5 OS=Rattus norvegicus OX=10116 GN=Exoc5 PE=1 SV=1 MATTAELFEEPFVADEYIERLVWRTPGGGSRGGPEAFDPKRLLEEFVNHIQELQIMDERIQRKVEKLEQQCQKEAKEFAKKVQELQKSNQVAFQHFQELDEHISYVATKVCHLGDQLEGVNTPRQRAVEAQKLMKYFNEFLDGELKSDVFTNPEKIKEAADVIQKLHLIAQELPFDRFSEVKSKIASKYHDLECQLIQEFTSAQRRGEVSRMREVAAVLLHFKGYSHCIDVYIKQCQEGAYLRNDIFEDAAILCQRVNKQVGDIFSNPEAVLAKLIQNVFEVKLQSFVKDQLEECRKSDAEQYLKSLYDLYTRTTSLSSKLMEFNLGTDKQTFLSKLIKSIFVSYLENYIEVEIGYLKSRSAMILQRYYDSKNHQKRSIGTGGIQDLKERIRQRTNLPLGPSIDTHGETFLSQEVVVNLLQETKQAFERCHRLSDPSDLPRNAFRIFTILVEFLCIEHIDYALETGLAGIPSSDSRNANLYFLDVVQQANTIFHLFDKQFNDHLMPLISSSPKLSECLQKKKEIIEQMEMKLDTGIDRTLNCMIGQMKHILAAEQKKTDFKPEDENNVLIQYTNACVKVCAYVRKQVEKIKNSMDGKNVDTVLMELGVRFHRLTYEHLQQYSYSCMGGMLAICDVAEYRKCAKDFKIPMVLHLFDTLHALCNLLVVAPDNLKQVCSGEQLANLDKNILHSFVQLRADYRSARLARHFS