B7GSF9 AF NFT

Chromosomal replication initiator protein DnaA

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiajo3bgdkr2wxrdfgwxnpyn6mzzuqhyluwxra3usbosyedvtnbicq/metadata.json
IPFS of structure file: 
bafybeif7cmxmqtgw2fp27bcnv77dxiyoy4xbbaupd4bypse5hldlzsr6f4/AF-B7GSF9-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x944ed3Ad5F85075b3157aaAaE8CDf0E6fa419f4B
First NFT owner address (bech32): 
genesis1j38d8t2ls5r4kv2h424w3n0sumayr86tm5qxp8
Current NFT ID #99575 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
99575
Accession (UniProt):
B7GSF9
Name::
Chromosomal replication initiator protein DnaA
Experimental Method:
Predicted structure
Sequence source:
BIFIDOBACTERIUM LONGUM SUBSP. INFANTIS (STRAIN ATCC 15697 / DSM 20088 / JCM 1222 / NCTC 11817 / S12)

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 B7GSF9 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B7GSF9|DNAA_BIFLS Chromosomal replication initiator protein DnaA OS=Bifidobacterium longum subsp. infantis (strain ATCC 15697 / DSM 20088 / JCM 1222 / NCTC 11817 / S12) OX=391904 GN=dnaA PE=3 SV=1 MVNASGDPVIEAAHIWSDTLTVLKHSASLSPREKGWLEGVVPEGVFGSTIVLCVDNNDTLQAIQGDLNDSLLQALRTVTGENMFPAFKVVPKTEPEPLSAAKPAQPYPSEISPTVAEFGKESYGAKPVAAPREPMPATESQFPVGQQKMNRDPETHLNKNFTFDSFVPGDSNRFARTVALAVAEGSGQDFNPLCIYGGSGLGKTHLLNAIGNYALVKDPGLKVRYVTSEEFTNEFIDALQNPNQSQGQIAEFNRRYRQVDVLLIDDIQFLGGKEATLDQFFHTFNALHQANKRIVIASDVAPKNLKGFEARLISRFESGLTVDVKPPDLETRIAILRMIASMNGSKIPSDVLDLIAERFTENIRELEGALTRVTAVASLSNQPVTRALAEQTLQDFFTTDVEIKPTDIISQVAKYFHLTFEDLVGKSRTKNVAVPRQIAMYLAREMTSMSLMDIGQVFGGRDHTTVMHACTRISDRMQQKQEIYNYVMELTVRLKQSNTN