B2S1W3 AF NFT

Phenylalanine--tRNA ligase beta subunit

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeie2zimdyaefy6iu6x6ct4cswzu7os7bg5hp4ksvqo2pihcvvjbf3y/metadata.json
IPFS of structure file: 
bafybeidkfguzaab2b5mc4lsponkiaeupj3zwtsmmqr47fpvuu7pd4uw76q/AF-B2S1W3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x3298b100681D3A2372Bba3b2f282750dD71629B9
First NFT owner address (bech32): 
genesis1x2vtzqrgr5azxu4m5we09qn4pht3v2de5478nd
Current NFT ID #447098 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
447098
Accession (UniProt):
B2S1W3
Name::
Phenylalanine--tRNA ligase beta subunit
Experimental Method:
Predicted structure
Sequence source:
Treponema pallidum subsp. pallidum (strain SS14)

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 B2S1W3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B2S1W3|SYFB_TREPS Phenylalanine--tRNA ligase beta subunit OS=Treponema pallidum subsp. pallidum (strain SS14) OX=455434 GN=pheT PE=3 SV=1 MPKISIHEALFFELLGERCDDDTLERRLRSAKAELECSSFSVREDKEGGSLSPGGEVCDPVQRTRGQASCVREGAFDARLLKIELNDTNRPDLWSTAGLARLLRVHAGGASRAAQYRAFLSDRCTVRDSYGRCVVVDARLQTIRPFIAGFVARGTGLSEVRLWDLIQTQERLASNFGRRRCTLSLGCYRAQDICWPLAYRAVLLAEVSFTPLGMSMPLSGEQILTQHPKGREYGHLLKDYSFVPLLVDARGEVLSLIPITNSASLGAVVTGDTELFIECSGTDMCAVLVAVNSLACDLSDMGMQIEPVQITYSFDTPWGRSVTTPFYFQEKREVAHEQIDRLLGMPLPVADITEAFARMDCAVQVKQGTYVVEPAAYRNDFLHAVDLIEEVMLGRTLDRFSPQVPCSFTVGRLSDLTLLTRKIKHLLVGFGYQEMIFHYLGSAREFCTRMRCTADDLIEIENPLTESYRFVRRSIIPCLLSAELKSAHALYPHRIFEIGKVAFCSPHGEHGTCTQQSLGFLNASQEASYNEVASLVSGLLYCLKLPYQVEEAQDPRFVLGRQASICVHGSRVGIFGEIHPQVLSNWDIRMPCFAGELDVGALLP