Q65SD7 AF NFT

DNA mismatch repair protein MutL

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihtxnwo3oc5izlxok4ncc7ki6oeq2ltwqoqlt4mft22ynluvglydi/metadata.json
IPFS of structure file: 
bafybeifhovskp7zkqg7dh6yc42c3gyruuo7dmlbzjxbwaczsncpaooh7ci/AF-Q65SD7-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xB2a13B905dBaBb1935B122EC19E2A92ca9a472EA
First NFT owner address (bech32): 
genesis1k2snhyzah2a3jdd3ytkpnc4f9j56guh2zzjywf
Current NFT ID #253739 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
253739
Accession (UniProt):
Q65SD7
Name::
DNA mismatch repair protein MutL
Experimental Method:
Predicted structure
Sequence source:
MANNHEIMIA SUCCINICIPRODUCENS (STRAIN MBEL55E)

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 Q65SD7 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q65SD7|MUTL_MANSM DNA mismatch repair protein MutL OS=Mannheimia succiniciproducens (strain MBEL55E) OX=221988 GN=mutL PE=3 SV=1 MPIHILPPQLANQIAAGEVVERPASVVKELVENSLDAGASRIQIDIENGGATLIRIRDNGLGIAKEDLSLALARHATSKISCLDDLEAILSLGFRGEALASISSVSRLTLTSRTAEQKEAWQVYAQGRDMETTIKPASHPVGTTVEVANLFFNTPARRKFLRTEKTEFAHIDEVVRRIALAKPQIAFTLTHNGKILRQYKSAVEIEQKLKRVSAICGEDFVQNALQIDWKHDNLHLSGWVAVPNFHRPQNDLSYSYVNGRMIRDKVINHAIRQAYGDYLTNEQYPAFVLYLDLDPNEVDVNVHPTKHEVRFHQARLIHDFICQGVGNALQSEQADFARYDTPASADEIQEPAANWHSSLIKPNRSAAGHNIFESASDKNISGANTYSHGSAKINRFSTKFAENIPHFSTKSVSKTEQKLYGNLLTTPAEAKKNTAINAESENSFEKNVSTPQQSTQLSGQFLHSLALVKNQALLLQQGQDFYLLPLAKLQKLKFELTLQQPDIAQQPLLIPILFRLNERQLAQWQKQKNFFLQSGFEFDENPAQHRITLNKVPSCLRQQNLQGCVIRLLEENHEKISDFLTALCNQLQLNEIHVLADALTLLTEVELLLKTQNKIQLAQLLISVDFTQYLQ