A1UT52 AF NFT

Aspartate--tRNA(Asp/Asn) ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigfvo6oh4ndhvgwljiccai4wmk3wlwgtllse2xjupotdgwfj53br4/metadata.json
IPFS of structure file: 
bafybeicu7i2bkpyudx7u64yuds4hlg2yx5dtz7kfkidgw2okqphv3fq5la/AF-A1UT52-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xd10960F956646DE8b64d3598984c91C2d5Af3D7b
First NFT owner address (bech32): 
genesis16yykp72kv3k73djdxkvfsny3ct2670tm7h5hjv
Current NFT ID #444429 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
444429
Accession (UniProt):
A1UT52
Name::
Aspartate--tRNA(Asp/Asn) ligase
Experimental Method:
Predicted structure
Sequence source:
Bartonella bacilliformis (strain ATCC 35685 / NCTC 12138 / KC583)

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 A1UT52 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A1UT52|SYDND_BARBK Aspartate--tRNA(Asp/Asn) ligase OS=Bartonella bacilliformis (strain ATCC 35685 / NCTC 12138 / KC583) OX=360095 GN=aspS PE=3 SV=1 MHRYRSHNCAALRKCDVGTQVRLSGWVHRVRDHGGILFVDLRDHFGITQIVVNPDSSAFQIMEKVRSEWVICVDGKVCARSDEVINTTLPTGEIEIFADEIEILSKSDELPLPVFGEPDYPEDIRLKYRFLDLRRVTMHKNIMRRTEIISSIRRHMQDSGFTEFTTPLLTASSPEGARDFLVPSRIHQGKFYALPQAPQQYKQLLMMSGFDRYFQIAPCFRDEDPRADRLPGEFYQLDIEMSFVEQEDVLATMEPIIRSVFEEFSDGKLVTQSFPRISYDEAMRKYGSDKPDLRNPIIIEDVSQHFYDSDFKVFAQILANNENAQVWAIPAKTGGNRAFCDRMNGWAQGEGQPGLGYIFWRKEGENFEGAGPIAKNIGEQRTEAIRTQLGLKEGDACFFVAGDPKKFASFAGASRTRIGEELDLIDSKCFSFAWIVDFPFFEWNEDEKKIDFAHNPFSMPQGGMNAVDSQDPLTIKAFQYDLVCNGYEIASGGIRNHSPEMMLKVFNLAGLSREIVEERFGGLYRAFHYGAPPHGGMAAGVDRIVMLLQGVKNLREISLFPMNQQALDLLMSAPSDVSATQLNDLGIRIFPKVNNA