Q5LCK2 AF NFT

Aspartate--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiclnzq2vw3j2u6xvwajsglppmuoznk7hilzqaelfm6smnn7toz6pm/metadata.json
IPFS of structure file: 
bafybeifxoa2vgkge3yrlujrme3xxt4arwi4bx3rxqmrykbljlkpuadqcba/AF-Q5LCK2-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7Be4C5B3cE1a26874f0703a2AeAd5Eb8910912Fc
First NFT owner address (bech32): 
genesis100jvtv7wrgngwnc8qw32at27hzgsjyhudaye34
Current NFT ID #444923 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
444923
Accession (UniProt):
Q5LCK2
Name::
Aspartate--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Bacteroides fragilis (strain ATCC 25285 / DSM 2151 / CCUG 4856 / JCM 11019 / NCTC 9343 / Onslow)

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 Q5LCK2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q5LCK2|SYD_BACFN Aspartate--tRNA ligase OS=Bacteroides fragilis (strain ATCC 25285 / DSM 2151 / CCUG 4856 / JCM 11019 / NCTC 9343 / Onslow) OX=272559 GN=aspS PE=3 SV=1 MFRTHTCGELRISDVNKQVKLSGWVQRSRKMGGMTFVDLRDRYGITQLVFNEEIDAELCERANKLGREFVIQIVGTVNERFSKNSHIPTGDIEIIVSELNILNSAITPPFTIEDNTDGGDDIRMKYRYLDLRRSAVRSNLELRHKMTIEVRSYLDKLGFLEVETPVLIGSTPEGARDFVVPSRMNPGQFYALPQSPQTLKQLLMVSGFDRYFQIAKCFRDEDLRADRQPEFTQIDCEMSFVEQEDVITTFEGMAKHLFKVIRNIELTEPFPRMPWSEAMRLYGSDKPDIRFGMQFVELMDILKGHGFSVFDNATYIGGICAEGAAGYTRKQLDALTEFVKKPQIGAKGMVYARIEADGTVKSSVDKFYTQEVLQQLKEAFGAKPGDLILILSGDDAMKTRKQLCELRLEMGNQLGLRDKNTFACLWVVDFPLFEWSEEEGRLMAMHHPFTSPKPEDIHLLDTNPAAVRANAYDMVINGVEVGGGSIRIHDSQLQNKMFELLGFTPERAQEQFGFLMNAFKFGAPPHGGLAYGLDRWVSLFAGLDSIRDCIAFPKNNSGRDVMLDAPAALDPSQLEELNLIVDIKE