A7FMY1 AF NFT

DNA mismatch repair protein MutL

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeicgzux6kic6skmkfuh3qaq2wuwo2ae2dte2xk7up7x3jcazak65yi/metadata.json
IPFS of structure file: 
bafybeie4fqkck6nmjm6nz3q7yiify66z2n5pbk2vbh2lyo63y2x6y6c3ce/AF-A7FMY1-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x1689a1235E93f193D2544B7D6Eb531894Ac60917
First NFT owner address (bech32): 
genesis1z6y6zg67j0ce85j5fd7kadf3399vvzghu5mu4q
Current NFT ID #253946 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
253946
Accession (UniProt):
A7FMY1
Name::
DNA mismatch repair protein MutL
Experimental Method:
Predicted structure
Sequence source:
Yersinia pseudotuberculosis serotype O:1b (strain IP 31758)

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 A7FMY1 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A7FMY1|MUTL_YERP3 DNA mismatch repair protein MutL OS=Yersinia pseudotuberculosis serotype O:1b (strain IP 31758) OX=349747 GN=mutL PE=3 SV=1 MPIQILPPQLANQIAAGEVVERPASVVKELVENSLDAGATRIDIDIERGGAKLIRIRDNGCGISKDDLALALARHATSKISSLEDLEAILSMGFRGEALASISSVSRLILTSRTAEQSEAWQAYAEGRDMAVTIKPAAHPVGSTLEVLDLFYNTPARRKFMRTEKTEFGHIDEVVRRIALARFDVAINLNHNGKLIRQYRAAPDPAQHERRLASICGPAFLQHALAIAWQHGDLNIHGWVADPAASHTLSEMQYCYVNNRMMRDRLINHAIRQAYQDRLNDAQQPAYVLYLDIDPHQVDVNVHPAKHEVRFHQARLVHDFIYQAVTAVLQQTNAPILNISEEGEVDAPRWQQENRVAAGTNKYAQPEAAKSSAAEQAVARERSSARERAAPAYKEDHPYQKQQGELYRQLLQPSAAAKPATSPAAIPASSVSSPSIPVQRITQAEEPLHGDNYSFGRVLTVFPPCYALIEYQGGVALLSLTVAERWLKQAQLSPPEEGLRPQPLLIPLKITLDKNEIAACQNHEKLLITMGIELSVEQGRATLRAVSLPLRQQNLQKLIPELLGYLSQHEEISPDTLATWLARHLGSEHEVWNVSQAIQLLTEVERLCPQLVQSPPAGLLQPIDIKAALATLTHE