P44038 AF NFT

Translocation and assembly module subunit TamA

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihmadufxyasxb6yitj7egl7y2lnorn6yr2f6pv5eoxg2ya4xoep7e/metadata.json
IPFS of structure file: 
bafybeidfqfcwcq2smhu6pcrog3fqfpmlcxgk7iakemymtu44pgfn7ok27i/AF-P44038-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x5094539FB3326c41CCb25b4b551912F9816d2CFb
First NFT owner address (bech32): 
genesis12z2988anxfkyrn9jtd942xgjlxqk6t8mz2pm67
Current NFT ID #457750 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
457750
Accession (UniProt):
P44038
Name::
Translocation and assembly module subunit TamA
Experimental Method:
Predicted structure
Sequence source:
HAEMOPHILUS INFLUENZAE (STRAIN ATCC 51907 / DSM 11121 / KW20 / RD)

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 P44038 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P44038|TAMA_HAEIN Translocation and assembly module subunit TamA OS=Haemophilus influenzae (strain ATCC 51907 / DSM 11121 / KW20 / Rd) OX=71421 GN=tama PE=1 SV=1 MKKKSLKLTALFLALSCFPAFAEQTVDIEVQGIRGFRAVRNTDLNVNLINKEEMDGSERYQHLVTKAVDRGLRVFGYYESSVRFERKQRQGKRDLLIAHVTPGEPTKIAGTDVQIEGEAAQDENFNALRKNLPKDGVLVEHQTYDDYKTAISRLALNRGYFDGNFKISRLEISPETHQAWWRMLFDSGVRYHYGNITFSHSQIRDDYLNNILNIKSGDPYLMNNLSDLTSDFPSSNWFSSVLVQPNVNHKSKTVDVEIILYPRKKNAMELGVGFSTDGGVHGQIGWTKPWINSRGHSLRSNLYLSAPKQTLEATYRMPLLKNPLNYYYDFAVGWEGEKENDTNTRVLTLSALRYWNNAHGWQYFGGLRMRYDSFTQADITDKTLLLYPTVGFTRTRLRGGSFATWGDVQKITFDLSKRIWLSESSFIKVQASSAWVRTYAENHRVVARAEIGYLHTKGIEKIPPTLRFFAGGDRSVRGYGYKKIAPKNRNGKLVGGSRLLTTSLEYQYQVYPNWWAATFADSGLAADNYTAKELRYGTGVGVRWASPVGAIKFDIATPIRDKDNSKNIQFYIGLGTEI