F1SY68 AF NFT

Cytochrome P450 monooxygenase 67

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeibwaqj3ocvbmz6jmzwjrxzffiro2zfnhdeqpcw6eyym5nkwgekf2e/metadata.json

IPFS of structure file:

bafybeihrooso7rasfmdlp3yuy456hcik4fa2kopnuympz7ebjhupmzrkgi/AF-F1SY68-F1-model_v2.pdb

First NFT owner address (eip-55):

0xd27f4D98eE625C1f8E81f7ac0eF38f876f24543e

First NFT owner address (bech32):

genesis16fl5mx8wvfwplr5p77kqauu0sahjg4p7w0r097

Current NFT ID #81953 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
81953
Accession (UniProt):
F1SY68
Name::
Cytochrome P450 monooxygenase 67
Experimental Method:
Predicted structure
Sequence source:
Postia placenta (strain ATCC 44394 / Madison 698-R)

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 F1SY68 research and analysis (ICN3D with VR)

FASTA sequences

>sp|F1SY68|CY067_POSPM Cytochrome P450 monooxygenase 67 OS=Postia placenta (strain ATCC 44394 / Madison 698-R) OX=561896 GN=CYP067 PE=2 SV=1 MQLPVQLSPPLALAVLSIAACQIALVWWFQRKRTNPLPPGPSALPFLGNAHQIPLQYPERIFSQWARTYGGVMYLRLFKKSVLILDSVKAAQDLMDKRGAKFSDRPQLTLITDVFAFKPMMFTMPYGDLWRRHRKWYQASLESKAALDTYNAVQETETCTLLSALVSEPEHFADQVKRFTGAILLEIVYGHAVTSVKDDLIRLSDEMMTQAVSAGSLVATLLDFFPFLMHIPEWFPGGGFKREGARVRHLMRQLLDVPFNEVQQAMLEGSGKACLTTYMLEEQAEHGDLTPDDVDNIKGAATLLFIAGTDTTITSLLTFFLAMVLHPEVVHKAQAEIDRVVGRTRLPGLMDRDALPYLDQVLKEVYRWNPPVPLGIPHQVRDDDVYNGRHIPGGSMVVSNIWSMSRDPDTYEDADRFWPERYEGKSPDELARSDPRRIVYGFGRRLCPGRFLADSSIWLAVARVIATLDIRKVRDAEGKEITPSAEFISGAVSHPKPFSLDIRPRDEVAAKLIAQ

MOLNFT AF v1_w

NFT data

MOLNFT F1SY68 research and analysis (ICN3D with VR)

FASTA sequences

We use cookies on this site to enhance your user experience