Q0J9J6 AF NFT

Crossover junction endonuclease EME1

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeia5iv5il3dzm3c7hlgkmqf2vb2ia3nd5yzzy7lpnmwdkwf646ykci/metadata.json
IPFS of structure file: 
bafybeig367ywsamyqq5oiwkixhbjjo4wqeor65s3ps645qahbgoh2lcx4y/AF-Q0J9J6-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x3BFd9938226F8990658D1862a21a8b24B008D0c8
First NFT owner address (bech32): 
genesis1807ejwpzd7yeqevdrp32yx5tyjcq35xg84csa3
Current NFT ID #116163 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
116163
Accession (UniProt):
Q0J9J6
Name::
Crossover junction endonuclease EME1
Experimental Method:
Predicted structure
Sequence source:
ORYZA SATIVA SUBSP. JAPONICA

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 Q0J9J6 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q0J9J6|EME1_ORYSJ Crossover junction endonuclease EME1 OS=Oryza sativa subsp. japonica OX=39947 GN=EME1 PE=2 SV=1 MASHAAVVEIIDDDDDDDDDVAAASTPPALHKRSHAVAAAAPDSPDAFSPSPPDPKRRQLAASTIVLDDTPTPPKRRPPPVAADRSASVVADTPRSFVPCSLRNRAIAGDTPDSVLPSPSFHLDAPDSATPGSDVPCSVGLDDIVPETPGFNSPRLARPPAVPGLTSPMTARKFSGVSCPISLDSDDELDDTVYRESLTRTPSNMAKPEHAIQPCTTSCTDKVENTKSTDKKDYSKSNVGYQTNNSACKNNGTTSYNQPPRANSPCEDSTLKEADPFINNHCPQEENALPIEERKKKQQEEKRLKKEKKAREIEEKKQKRLETKKQKEAMKAELAELKKLEKEKKKWESGKLATKCIVAEIDSSVIESGSVGGHLVQGFHEKGLCFRVTSNSIKGSILWKMQIPNEFTQDQASTSQVPYILFVLQAEEFCDLVSGGTLLDHVQKVRRQYPEFTICYVTNKLMSFIKRREQNQYNKTTSNSNSWKRPPVEEALCKLATHYARVRSRHCTDEAEVTEHIVGLTYSLANCKFRKPLTWLSVHANGSNISKGCVDKDRIKKSAWLKSLVAIPGVSPGQAIAIEKKYPSMRSLLNVYMDDSKSVHEKEHLLEDLRLEGPLGDFKRRLGPACSKKVYTILMAQNGAAEVEVDRRGA