Q48PD2 Probable 2-(5''-triphosphoribosyl)-3'-dephosphocoenzyme-A synthase MolNFT, Molecular NFT on GenesisL1

Probable 2-(5''-triphosphoribosyl)-3'-dephosphocoenzyme-A synthase

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeidfv45dja2xhgepslge4uwtm2a7s3bddfvsaoelm6kmataoosh43y/metadata.json

IPFS of structure file:

bafybeifrxmmnfnv3asjsq6rkmtjhvzomqzd3lsvusa7adnxopjmxasvsdy/AF-Q48PD2-F1-model_v2.pdb

First NFT owner address (eip-55):

0x66e4d6BF97F1E37D3f479b250639fc6429e652f4

First NFT owner address (bech32):

genesis1vmjdd0uh783h6068nvjsvw0uvs57v5h5evzh9f

Current NFT ID #226936 owner (web3):

0xE30012A6Af8a0a40153f2882Bd2e0444eC52063c

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
226936
Accession (UniProt):
Q48PD2
Name::
Probable 2-(5''-triphosphoribosyl)-3'-dephosphocoenzyme-A synthase
Experimental Method:
Predicted structure
Sequence source:
Pseudomonas savastanoi pv. phaseolicola (strain 1448A / Race 6)

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 Q48PD2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q48PD2|MDCB_PSE14 Probable 2-(5''-triphosphoribosyl)-3'-dephosphocoenzyme-A synthase OS=Pseudomonas savastanoi pv. phaseolicola (strain 1448A / Race 6) OX=264730 GN=mdcB PE=3 SV=1 MSALQLTPQAASLAERLADLAVDALIAEADLSPKPALVDRRGSGAHTDLHLGLMHSSALSLWPTFKLMADAAGQFNTVGQPLREALGRLGRDGEATMLRTTQGVNTHRGAIWALGLLVTAAALDARNCAPEAVLARAASLAQIKDRQVLVQGSHGNEVVRRYGVMGAREQAQQGFPAVRDFALPQLQRSRAAGSGEQNARLDALLAIMTTLSDTCVLHRAGIEGLHTMQRGAQHVLDVGGSASLAGRRALNQLDQQLLALNASPGGAADLLAACLFIDGLEPALGRVSRSV

Q48PD2 AF NFT

MOLNFT AF v1

NFT data

MOLNFT Q48PD2 research and analysis (ICN3D with VR)

FASTA sequences

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