B0TU66 AF NFT

DNA mismatch repair protein MutL

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeib7nlj6n6fr5q45krosss5jsjhttfk3x4nla7twqayiw33vrhds4i/metadata.json
IPFS of structure file: 
bafybeiceek2rfd3y3otokftblqjwvdbx2tjc47ca6oiyygctnkytigvq2u/AF-B0TU66-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xFE12884Eff419603b6dFefe423f9b5276dad6aD4
First NFT owner address (bech32): 
genesis1lcfgsnhlgxtq8dklaljz87d4yak666k5zs55ff
Current NFT ID #253839 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
253839
Accession (UniProt):
B0TU66
Name::
DNA mismatch repair protein MutL
Experimental Method:
Predicted structure
Sequence source:
Shewanella halifaxensis (strain HAW-EB4)

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 B0TU66 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B0TU66|MUTL_SHEHH DNA mismatch repair protein MutL OS=Shewanella halifaxensis (strain HAW-EB4) OX=458817 GN=mutL PE=3 SV=1 MAIEKLPPQLANQIAAGEVVERPASVIKELVENSLDAGATRVDIEIEKGGSKLIRIRDNGSGIPKADLCLALSRHATSKLKSLDDLEAILSFGFRGEALASISSVSRLILTSRTAEQAEAWQAHAEGTEMAVKVLPAAHPVGSTVEAVDLFFNTPARRRFLKSDKTEFTHIDEWLKRIALARRDIHFTLKHNGKTVRNYRPANTESQYIQRLALVCGKAFAETCLRIECQHNDLSLSGYLQSPSSANGYSETQYFYVNGRLVKDRLVNHAVRQAFAQYAEGVSPGYVLMLDLDPHQVDVNVHPAKHEVRFHQSRYVHDFILQALQSAISQSMELALNNEPEIQQSPDRQVSPTRGAVTAPLYSESIERKPSVSYDVRDSHSVTNQRDYSSGSSSYRSPLKPSARNGDVSLPSQSSIRAYGELLSTQSSSTHSDRVLSTQQNNYAVRSPAGNQNGLAASNSHAASMPAVIAGEFWVLVRDDKISLLSISMVARAVLKAEIAAKFSQGLVGQPLLMPVAVAVDDDWLAIIENREQLLRKLGIELSIRLGQLIIKKVPPYLRNSQLAVLIPELLQWIQLELPSDAAVVKWLAEQGANRFTSAGEAWFGLNALPDDVQRELYNLSQDLPWEQWMKENQSDR