Q65M31 AF NFT

L-cystine uptake protein TcyP

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibmsxratmdj6bfthmz6lnjwc4z7d5rhq6655a3jy2gcn3zn4dnpzy/metadata.json
IPFS of structure file: 
bafybeihuymzbbvmvkszjih4jjvxobqljy5e4wpuq3eyiynquqrwrgwuu4i/AF-Q65M31-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x3acEaC4964ABedBF9181F5F6256877AD24D75229
First NFT owner address (bech32): 
genesis18t82cjty40kmlyvp7hmz26rh45jdw53f8jez63
Current NFT ID #460344 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
460344
Accession (UniProt):
Q65M31
Name::
L-cystine uptake protein TcyP
Experimental Method:
Predicted structure
Sequence source:
Bacillus licheniformis (strain ATCC 14580 / DSM 13 / JCM 2505 / CCUG 7422 / NBRC 12200 / NCIMB 9375 / NCTC 10341 / NRRL NRS-1264 / Gibson 46)

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 Q65M31 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q65M31|TCYP_BACLD L-cystine uptake protein TcyP OS=Bacillus licheniformis (strain ATCC 14580 / DSM 13 / JCM 2505 / CCUG 7422 / NBRC 12200 / NCIMB 9375 / NCTC 10341 / NRRL NRS-1264 / Gibson 46) OX=279010 GN=tcyP PE=3 SV=1 MTLFVVINIIVMLGLMALLYMMQKKHVSFSKRVFTALGIGIVFGFALHFIYGSSSETITQTSDWFNIAGGGYVKLLQMIVMPLVFISILGAFTKLKLTHNIGKISGLIIGLLIATTAVAAAVGIASALAFDLQAVHVDQGQAETMRGAELEQKSQDMEAKTLPQQIVELLPGNPFLDFTGARPTSTIAVVIFAAFLGIAYLGVNRKQPEQAELFKKMVDAVYAIIMRVVTLILRLTPYGVLAIMTKTIATSDLDSIAKLGKFVIASYAALIVMFIIHLLLITFSGLNPVTYLKKAFPVLVFAFTSRSSAGALPLNIKTQRSLGVPEGIANFAGSFGLSIGQNGCAGIYPAMLAIMIAPTVGQNPLDPSFLFTVIAVVAISSFGVAGVGGGATFAALLVLSALNMPVALAGLLISVEPLIDMGRTALNVSGSMTSGLVTSKVTNELEKDTYQDRTNIIEAEV