P9WN05 AF NFT

Probable dolichyl-phosphate-mannose--protein mannosyltransferase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiebt6hobi27d6xyrc2bkmbhx7bj6psc3zlizmlyhgg5brkthfj4cq/metadata.json
IPFS of structure file: 
bafybeifl5fpk3s7qrcwcgzxkhxe6gtvfpvpcunlh75dec36ce7d4k2vzsi/AF-P9WN05-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xaa53776A41fB2e67da75A96E8a53746b6874aAB4
First NFT owner address (bech32): 
genesis14ffhw6jplvhx0kn449hg55m5dd58f245h56u30
Current NFT ID #303606 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
303606
Accession (UniProt):
P9WN05
Name::
Probable dolichyl-phosphate-mannose--protein mannosyltransferase
Experimental Method:
Predicted structure
Sequence source:
MYCOBACTERIUM TUBERCULOSIS (STRAIN ATCC 25618 / H37RV)

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 P9WN05 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P9WN05|PMT_MYCTU Probable dolichyl-phosphate-mannose--protein mannosyltransferase OS=Mycobacterium tuberculosis (strain ATCC 25618 / H37Rv) OX=83332 GN=pmt PE=1 SV=2 MTARPPESCVLAKDRPEEPVVPVVSPGPLVPVADFGPLDRLRGWIVTGLITLLATVTRFLNLGSLTDAGTPIFDEKHYAPQAWQVLNNHGVEDNPGYGLVVHPPVGKQLIAIGEAIFGYNGFGWRFTGALLGVVLVALVVRIVRRISRSTLVGAIAGVLLICDGVSFVTARTALLDGFLTFFVVAAFGALIVDRDQVRERMHIALLAGRSAATVWGPRVGVRWWRFGAGVLLGLACATKWSGVYFVLFFGAMALAFDVAARRQYQVQRPWLGTVRRDVLPSGYALGLIPFAVYLATYAPWFASETAIDRHAVGQAVGRNSVVPLPDAVRSLWHYTAKAFHFHAGLTNSAGNYHPWESKPWTWPMSLRPVLYAIDQQDVAGCGAQSCVKAEMLVGTPAMWWLAVPVLAYAGWRMFVRRDWRYAVVLVGYCAGWLPWFADIDRQMYFFYAATMAPFLVMGISLVLGDILYHPGQGSERRTLGLIVVCCYVALVVTNFAWLYPVLTGLPISQQTWNLEIWLPSWR