Q2S6X1 AF NFT

Elongation factor G 2

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidet4rskn6fzwkyiy6enjwi44mjauwidejqs42fbh72vjqmzrd7m4/metadata.json
IPFS of structure file: 
bafybeie66shehnrovl7xi73fvcgu7gbgapvvej5jgtzxdl6ytxrypqyub4/AF-Q2S6X1-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x1D1bB2f51A09dE3363CF393564D7E3b16D358D88
First NFT owner address (bech32): 
genesis1r5dm9ag6p80rxc708y6kf4lrk9kntrvg3wkpqt
Current NFT ID #111077 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
111077
Accession (UniProt):
Q2S6X1
Name::
Elongation factor G 2
Experimental Method:
Predicted structure
Sequence source:
Hahella chejuensis (strain KCTC 2396)

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 Q2S6X1 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q2S6X1|EFG2_HAHCH Elongation factor G 2 OS=Hahella chejuensis (strain KCTC 2396) OX=349521 GN=fusA2 PE=3 SV=1 MKLQKLRNIGIIAHVDAGKTTLTERLLHFTGALHSMGEVHHGGTVTDHMVQERQRGITIASAAVTVGWRDHRINIIDTPGHIDFNIEVNRSLRVLDGAVVVFDSVAGVEPQSETNWRLADQYGVPRICLVNKMDRIGADYLRVVAMIRERLGAQPLVVHLPVFVEETYVGLIDLTTMSLHRWNADDGWKYSSEEITPEYQEQAAQYRAQLEETLVELDDELLEGWFNGATLQADDLKRLIRQGVVSGAFVPVLCASAFKNKGVQMVLDAVVDYLPSPQEVKGMETVDGAQIVDADVDGAFAALAFKVVNDKHGALTYVRVYRGTLQSGSRVLNTNVGQYERIGRIYEMHADRKVARDRIGAGDIVALVGMKHTQTGDTLCAPEAPLVLERINAPEPVMDIVIEPKSRQDQDRLGEALRAIVGEDPSLRLSTGAAGETLVSGMGELHLEIVVDRLQTDFDIAVTVGRPQVAYRETITQSAAVDYVYKKQKGGPGQFAEVRMRFEPIAGDGIEFESQIVGAAIPREYIPAVEDGVRQAARSGVLGGYPCGGFKAVLLDGAYHAQDSSQLAFSVAGREAFKEAMAQATPRLLEPVMAVEIVTPRDHVGDCIGDLMRRRGSILNQLDRGDACVINAEAPLAEMFGYIGDLRTMTAGRASFSMTFSHYAETPQGVADAVLNAD