B3WCQ5 AF NFT

UvrABC system protein B

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiali2n4qnudxgs7hq7cbgx52oykybtp2izcmf226f4drdquukdbq4/metadata.json
IPFS of structure file: 
bafybeiejuq5tehpsdvyhg5ywvb6cb2ykubvd6y5uzmuhj2djxt65t6d3wu/AF-B3WCQ5-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x5881B09f2D8e743400698633641fc1cD2Ed2BE6F
First NFT owner address (bech32): 
genesis1tzqmp8ed3e6rgqrfscekg87pe5hd90n0e7l5st
Current NFT ID #493335 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
493335
Accession (UniProt):
B3WCQ5
Name::
UvrABC system protein B
Experimental Method:
Predicted structure
Sequence source:
Lacticaseibacillus casei (strain BL23)

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 B3WCQ5 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B3WCQ5|UVRB_LACCB UvrABC system protein B OS=Lacticaseibacillus casei (strain BL23) OX=543734 GN=uvrB PE=3 SV=1 MIERIADRKFDLVSPYQPAGDQPQAIAKLTKGFEEGKKEQILLGATGTGKTFTMSNIIANLNKPTLILSHNKTLAGQLYGEFKEFFPHNAVEYFVSYYDYYQPEAYVPSTDTYIEKDSAINDEIDKLRHSATSALLERNDVIVVASVSSIFGLGDPHEYKNHVLSLRTGMTIDRNTLLRQLVDIQFDRNDIDFQRGRFRVRGDVVEIFPASRDDHAIRVEFFGDEIDRITEVDALTGEVIGTRDHVAIFPATHFMTSDEQMQRAIKSIAAELEAQLKVLRSENKLLEAQRLEQRTNYDIEMMREMGFTSGIENYSRHMDGRKPGEPPYTLLDFFPKDFNIMVDESHVTMPQIRGMYNGDRARKQMLVNYGFRLPSALDNRPLKINEFEQHVHRILYVSATPGPYELDRVPKDDIAEQIIRPTGLLDPKIEVRPVMGQIDDLVGEINKRVDAHERVFITTLTKKMAEDLTDYLKDMGIKVRYLHSDIKTLERTQIIRDLRLGKFDVLIGINLLREGIDVPEVSLIAILDADKEGFLRAERSLIQTIGRASRNEHGKVIMYADKVTDSMKAAIDETQRRRTIQEKFNEEHHITPKTIIKPIRAAISSYEQSDDDKAEAKKTFAEVDYEDMSKADKKELVANLRSQMQAAAKKLDFEQAASLRDTILELQADMS