B9EBI5 AF NFT

DNA mismatch repair protein MutL

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibyajj5bldfm4bevk6tayh6zplpytugwuvqsu235eyne4bdd6iniu/metadata.json
IPFS of structure file: 
bafybeiaskijv3z7kcwgrn77gtvq5sezra2ghj3n5t6bxqto4pshdfc2pym/AF-B9EBI5-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x8E72F2119bF02e08301950023b4779D3C5F1Eaaa
First NFT owner address (bech32): 
genesis13ee0yyvm7qhqsvqe2qprk3me60zlr642q2f2u4
Current NFT ID #253737 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
253737
Accession (UniProt):
B9EBI5
Name::
DNA mismatch repair protein MutL
Experimental Method:
Predicted structure
Sequence source:
Macrococcus caseolyticus (strain JCSC5402)

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 B9EBI5 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B9EBI5|MUTL_MACCJ DNA mismatch repair protein MutL OS=Macrococcus caseolyticus (strain JCSC5402) OX=458233 GN=mutL PE=3 SV=1 MGIIKTLDSTISNKIAAGEVIERPQSVVKELVENAIDAKSTSITIEVEEAGLSKIKVTDNGSGILEEDLELMFRRHATSKIENEHDLFHIRSLGFRGEALASIASVSKVRVTTCHDGSIGRQIDVIDGETVNRTLAQARQGTEITVESLFYNTPARLKYVKSLHTELGKITDIINRFVISFPYIKFTLVADGRVLIASNGNGKMQEAMAVVYGMKIAQDLVEVNGRTGDYEVHGFIAKPEHTRSNRHYMSLFINGRYIKNFMLTKAILSGYHTLLPVGRYPILAINIVMDPALVDVNVHPTKQEVRLSKESQLMELIERLIKEKIWKQNLIPKVEKKKVLETFQQQKFEYDLLREHRDKTKQSDYSEQTAVNQIDEKFKEQHKTAQLDKQRVPDGESTQKTTGFISDSAAELDTTSEILPEKNESSDVIENISTDTSREKRKIPYMEIVGQVHGTYIIAQNEDGMFMIDQHAAQERIKYEYFKKQIGDVGLEMQSLLIPITVTLSKDEAINLNKINILLKDIGIHLEHFGGNDYIINDIPVWFPDNYEETVQELIDYALQHRQIDLNKFREETAIMMSCKKSIKANHYLRITDMNYLLEELAHTVEPYTCPHGRPIIIQFTTYELEKLFKRVM