P67012 AF NFT

Aspartate--tRNA(Asp/Asn) ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihn4b2jbbcagkibycq3ipro75lpuyjscpy2upneynvhf62nnqpg7i/metadata.json
IPFS of structure file: 
bafybeiaatgbyfgncfkwwo7uww6jdkiy4zn66cyo7zynpueov5g53fk3evm/AF-P67012-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x40B9C9d5F084D34d026E9d5Dd10501AcdF6d6152
First NFT owner address (bech32): 
genesis1gzuun40ssnf56qnwn4wazpgp4n0k6c2jdg88yn
Current NFT ID #444462 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
444462
Accession (UniProt):
P67012
Name::
Aspartate--tRNA(Asp/Asn) ligase
Experimental Method:
Predicted structure
Sequence source:
BRUCELLA MELITENSIS BIOTYPE 1 (STRAIN 16M / ATCC 23456 / NCTC 10094)

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 P67012 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P67012|SYDND_BRUME Aspartate--tRNA(Asp/Asn) ligase OS=Brucella melitensis biotype 1 (strain 16M / ATCC 23456 / NCTC 10094) OX=224914 GN=aspS PE=3 SV=1 MHRYRSHTCAALRKTDVGSNVRLSGWVHRVRDHGGILFIDLRDHYGITQIVADPDSPAFKVAETVRGEWVIRVDGEVKARADDAVNTNLPTGEVEIFATEIEVLSPAKELPLPVFGEPDYPEDIRLKYRFLDLRRETLHKNIMSRTKIIAAMRRRMTEIGFNEFSTPILTASSPEGARDFLVPSRIHPGKFYALPQAPQQYKQLLMVAGFDRYFQIAPCFRDEDPRADRLPGEFYQLDLEMSFVTQEEVWETMEPVMRGIFEEFAEGKPVTKVFRRIAYDDAIRTYGSDKPDLRNPIEMQAVTDHFAGSGFKVFANMIANDAKVEVWAIPAKTGGSRAFCDRMNSWAQSEGQPGLGYIFWRKEGDKLEGAGPIAKNIGEERTEAIRKQMGLEDGDACFFVAGLPSKFYKFAGDARTRAGEELNLVDRDRFELAWIIDFPFYEWDEDNKKIDFAHNPFSMPQGGMDALENMDPLEIKAYQYDLVCNGFEIASGSIRNQLPEVMVKAFEKVGLSQQDVEERFGGLYRAFQYGAPPHGGMAAGIDRVIMLLVGAKNLREISLFPMNQQALDLLMGAPSEVSPAQLRDLHVRLAPVQKS