Q2K9L9 AF NFT

Elongation factor G

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihahdbq2ov5uxnxuk62zpeih6tpd7dxvbpzmzqd7ovsvbfulu774q/metadata.json
IPFS of structure file: 
bafybeigdtl54x64hslgnvmg4k5d3ki6ekj4k3fx6knrk2z4qemco45mc2a/AF-Q2K9L9-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xe91E8c598DD1aF4C8bD2A5c521dfF9700c07ed65
First NFT owner address (bech32): 
genesis1ay0gckvd6xh5ez7j5hzjrhlewqxq0mt94lcp95
Current NFT ID #111641 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
111641
Accession (UniProt):
Q2K9L9
Name::
Elongation factor G
Experimental Method:
Predicted structure
Sequence source:
RHIZOBIUM ETLI (STRAIN CFN 42 / ATCC 51251)

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 Q2K9L9 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q2K9L9|EFG_RHIEC Elongation factor G OS=Rhizobium etli (strain CFN 42 / ATCC 51251) OX=347834 GN=fusA PE=3 SV=1 MAREYKIEDYRNFGIMAHIDAGKTTTTERILYYTGKSHKIGEVHDGAATMDWMEQEQERGITITSAATTTFWKGRDGKMRRFNIIDTPGHVDFTIEVERSLRVLDGAIALLDANAGVEPQTETVWRQAEKYNVPRMIFCNKMDKTGADFYRSVEMIKTRLGATAVVMQLPIGAESDFKGVVDLVEMNALIWRDESLGAQWDVVEIPDDLKAKAEEYREKLIETVVEIDEAAMEAYLEGNMPDNDKIRELVRRGTIDVKFHPMFCGTAFKNKGVQPLLDAVVDYLPSPLDIPAIKGIDFKTEADIERHADDAEPLSMLAFKIMNDPFVGSLTFARIYSGKLEKGSSVLNTVKDKRERVGRMLQMHSNSREDIEEAFAGDIVALAGLKETTTGDTLCDPLKPVILERMEFPEPVIQIAIEPKSKGDQEKMGLALNRLAAEDPSFRVKTDQESGQTIIAGMGELHLDIIVDRMRREFKVEANVGAPQVAYRETITRQTEEDYTHKKQTGGTGQFARVKIIFEPNPEGEDFKFESKIVGGAVPKEYIPGVQKGIESVLSSGPLAGFPMLGVKATLIDGAFHDVDSSVLAFEIASRACFREAAKKAGAQLLEPMMKVEVVTPEDYVGDVIGDLNSRRGQIQGQESRGIAVVISANVPLANMFKYVDNLRSMSQGRAQYTMTFDHYAPVPSNVATEIQAKYSGQK