P9WN04 AF NFT

Probable dolichyl-phosphate-mannose--protein mannosyltransferase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeieyrrws5tfjaqti4vrtbbug2klefd5o5rnadf7knhstt3rht5d4bu/metadata.json
IPFS of structure file: 
bafybeihdaunn7fok2zkynaxni6slmtw3zbrmmby7n4iinpwhr2eacjtzpa/AF-P9WN04-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x0D671490EE06E75975e90D7F99F73B20BE618744
First NFT owner address (bech32): 
genesis1p4n3fy8wqmn4ja0fp4lenaemyzlxrp6y5ma6w5
Current NFT ID #303605 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
303605
Accession (UniProt):
P9WN04
Name::
Probable dolichyl-phosphate-mannose--protein mannosyltransferase
Experimental Method:
Predicted structure
Sequence source:
MYCOBACTERIUM TUBERCULOSIS (STRAIN CDC 1551 / OSHKOSH)

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 P9WN04 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P9WN04|PMT_MYCTO Probable dolichyl-phosphate-mannose--protein mannosyltransferase OS=Mycobacterium tuberculosis (strain CDC 1551 / Oshkosh) OX=83331 GN=pmt PE=3 SV=2 MTARPPESCVLAKDRPEEPVVPVVSPGPLVPVADFGPLDRLRGWIVTGLITLLATVTRFLNLGSLTDAGTPIFDEKHYAPQAWQVLNNHGVEDNPGYGLVVHPPVGKQLIAIGEAIFGYNGFGWRFTGALLGVVLVALVVRIVRRISRSTLVGAIAGVLLICDGVSFVTARTALLDGFLTFFVVAAFGALIVDRDQVRERMHIALLAGRSAATVWGPRVGVRWWRFGAGVLLGLACATKWSGVYFVLFFGAMALAFDVAARRQYQVQRPWLGTVRRDVLPSGYALGLIPFAVYLATYAPWFASETAIDRHAVGQAVGRNSVVPLPDAVRSLWHYTAKAFHFHAGLTNSAGNYHPWESKPWTWPMSLRPVLYAIDQQDVAGCGAQSCVKAEMLVGTPAMWWLAVPVLAYAGWRMFVRRDWRYAVVLVGYCAGWLPWFADIDRQMYFFYAATMAPFLVMGISLVLGDILYHPGQGSERRTLGLIVVCCYVALVVTNFAWLYPVLTGLPISQQTWNLEIWLPSWR