A6ZRW3 AF NFT

Mitochondrial import receptor subunit TOM70

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibp6ag22eflxl4o33iiscqrwqo7xcory62iwlwj3mhbrbqdipcqsq/metadata.json
IPFS of structure file: 
bafybeihzhqlwyv46vdm2f6sfjfxm5j3tfcvtk47jvtdw5m2uesfwj46rvm/AF-A6ZRW3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x787c856c246D46194820F4350135EC4a88a6Ce76
First NFT owner address (bech32): 
genesis10p7g2mpyd4rpjjpq7s6szd0vf2y2dnnk6nzlk5
Current NFT ID #469860 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
469860
Accession (UniProt):
A6ZRW3
Name::
Mitochondrial import receptor subunit TOM70
Experimental Method:
Predicted structure
Sequence source:
SACCHAROMYCES CEREVISIAE (STRAIN YJM789)

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 A6ZRW3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A6ZRW3|TOM70_YEAS7 Mitochondrial import receptor subunit TOM70 OS=Saccharomyces cerevisiae (strain YJM789) OX=307796 GN=TOM70 PE=3 SV=1 MKSFITRNKTAILATVAATGTAIGAYYYYNQLQQQQQRGKKNTINKDEKKDTKDSQKETEGAKKSTAPSNPPIYPVSSNGEPDFSNKANFTAEEKDKYALALKDKGNQFFRNKKYDDAIKYYNWALELKEDPVFYSNLSACYVSVGDLKKVVEMSTKALELKPDYSKVLLRRASANEGLGKFADAMFDLSVLSLNGDFNDASIEPMLERNLNKQAMSKLKEKFGDIDTATATPTELSTQPAKERKDKQENLPSVTSMASFFGIFKPELTFANYDESNEADKELMNGLSNLYKRSPESYDKADESFTKAARLFEEQLDKNNEDEKLKEKLAISLEHTGIFKFLKNDPLGAHEDIKKAIELFPRVNSYIYMALIMADRNDSTEYYNYFDKALKLDSNNSSVYYHRGQMNFILQNYDQAGKDFDKAKELDPENIFPYIQLACLAYRENKFDDCETLFSEAKRKFPEAPEVPNFFAEILTDKNDFDKALKQYDLAIELENKLDGIYVGIAPLVGKATLLTRNPTVENFIEATNLLEKASKLDPRSEQAKIGLAQMKLQQEDIDEAITLFEESADLARTMEEKLQAITFAEAAKVQQRIRSDPVLAKKIQETLAKLREQGLM