Q19AZ8 AF NFT

Prothrombin

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeiaj7ww3ymmdwuzh7qckyoks3w4iw754k3yl7y2rhpky3wkymoufze/metadata.json

IPFS of structure file:

bafybeid4s3e265o2ytih4bvvhdxi7cwomeeywxtc3yjj5pmmclpuqcusvi/AF-Q19AZ8-F1-model_v2.pdb

First NFT owner address (eip-55):

0x5c4adF1416281C09AE8eE1cbb80fF7e44cE86F97

First NFT owner address (bech32):

genesis1t39d79qk9qwqnt5wu89msrlhu3xwsmuhlku3xz

Current NFT ID #465129 owner (web3):

0xAd557e6f6A692F288Eb46BbD1Af60EBFddb60Ea0

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
465129
Accession (UniProt):
Q19AZ8
Name::
Prothrombin
Experimental Method:
Predicted structure
Sequence source:
SUS SCROFA

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 Q19AZ8 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q19AZ8|THRB_PIG Prothrombin OS=Sus scrofa OX=9823 GN=F2 PE=2 SV=1 MAHVGGLWLHGCLALAVLVSLVHSQHVFMAPQQALSLLQRARRANSGFFEEMRKGNLERECVEEQCSREEAYEALESPSETDAFWAKYTACESVRKSREKLVECLEGNCAEGLGMNYRGNISVTRSGIECQLWRSRYPHKPEVNSTMYPGADLRENFCRNPDGSITGPWCYTTSPTVRREACSIPVCGQGRVTAELIPRSGGSTVNVSPPLETCVPERGRQYQGRLAVTSHGSPCLAWGSSQAKALSKDQDFNPAVPLVENFCRNPDGDQEGAWCYVAGQPGDFEYCDLDYCEEPVDEEVGDALGENADAAIEGRTTADDFQPFFNEKTFGAGEADCGLRPLFEKSSLEDKTEKELFESYIEGRIVEGSDAEIGLAPWQVMIFRKSPQELLCGASLISDRWVLTAAHCLLYPPWDKNFTENDLLVRIGKHSRTRYERNIEKISMLEKIYIHPRYNWRENLDRDIALLKLRKPITFSDYIHPVCLPDKETATKLLRAGYKGRVTGWGNLKETWTTSASEVQPSVLQVVNLPIVERLVCKASTRIRITDNMFCAGYKPDEGKRGDACEGDSGGPFVMKSPFNNRWYQMGIVSWGEGCDRDGKYGFYTHVFRLKKWMQKVIDRFGG

MOLNFT AF v1_w

NFT data

MOLNFT Q19AZ8 research and analysis (ICN3D with VR)

FASTA sequences

We use cookies on this site to enhance your user experience