Q9C4Z1

Acetyl-CoA decarbonylase/synthase complex subunit delta 2

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeife3moubr562ydv47przeopo6rx6pymc36j5esuncpl3dadw2yrfi/metadata.json

IPFS of structure file:

bafybeigu7moahsx62wsrqntwxtxfem5sj6nrtv37z7pma6synewii2rsmy/AF-Q9C4Z1-F1-model_v2.pdb

First NFT owner address (eip-55):

0x9F605311B7e26e76340423EfAfbE5e2EFc7A0b7C

First NFT owner address (bech32):

genesis1nas9xydhufh8vdqyy0h6l0j79m785zmurgry0u

Current NFT ID #5297 owner (web3):

0x9F605311B7e26e76340423EfAfbE5e2EFc7A0b7C

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
5297
Accession (UniProt):
Q9C4Z1
Name::
Acetyl-CoA decarbonylase/synthase complex subunit delta 2
Experimental Method:
Predicted structure
Sequence source:
METHANOSARCINA THERMOPHILA

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 Q9C4Z1 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9C4Z1|ACDD2_METTE Acetyl-CoA decarbonylase/synthase complex subunit delta 2 OS=Methanosarcina thermophila OX=2210 GN=cdhD2 PE=3 SV=1 MAKKMKLSEITNMFAGMNVEALEGVTIEGDIEIDLGGLGGFDPMLAAALGQESAVLAQHFARIAGMFGYPVSVGAPAAAPAAVSPALAAPKLKDLIPAKFEFSNIEEWTTQVEEVPIGNTSADGGSRGKRILLGGEKALPFFPDAPMPNRNQVTIDVFDMRLGLAKAVKENYDDVMDNPGEWAKKNVEKFNADMITIHLISTDPLIKDTSPKDAAKTVEEVLQAVDVPIAIGGSGNPQKDPLVLAKAAEVAEGERCLLASASLNLDYAAIAEAALKYDHDVLSWTQLDMNAQKELNRKLMKQCNVPRDRIIMDPTTAALGYGLDYAYTNMERIRLAALMGDDELTFPMSSGTTNAWGARESWMVSSPLKEDSDWGPREYRGPIWEIITGLSLAIAGNDLFMMMHPTSVAVLKHMTQTLFGSIEAEPVDIANWIGAEV

Q9C4Z1 AF NFT

MOLNFT AF v1_w

NFT data

MOLNFT Q9C4Z1 research and analysis (ICN3D with VR)

FASTA sequences

We use cookies on this site to enhance your user experience