P12616 Fimbrial subunit type 2 MolNFT, Molecular NFT on GenesisL1

Fimbrial subunit type 2

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeig3yhkab2d4dwqevxrs25uuxzfihmihlzjedpcigwmn36g2y24jay/metadata.json

IPFS of structure file:

bafybeidphd2hzwvtfncds4fbewi3exhwpwzzxny7ghfbj6m6ugb7cxew34/AF-P12616-F1-model_v2.pdb

First NFT owner address (eip-55):

0xb64DEeDEE372f6B93106C4D05EA5568323EeD16E

First NFT owner address (bech32):

genesis1kex7ahhrwtmtjvgxcng9af2ksv37a5twwzcdz3

Current NFT ID #132934 owner (web3):

0xb372bb7a2b2Ec8a5C7833c6f407cB1344601193d

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
132934
Accession (UniProt):
P12616
Name::
Fimbrial subunit type 2
Experimental Method:
Predicted structure
Sequence source:
ACTINOMYCES NAESLUNDII

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 P12616 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P12616|FM2_ACTNA Fimbrial subunit type 2 OS=Actinomyces naeslundii OX=1655 PE=3 SV=1 MKYNTSTLGRRAAAAAGVLTLAVLGLAPMAQAENANHGDINTEALGSLTIHKHLNGDGNPIGAPDGTASNDDGKGAPVSGVQFTAYEINGIDLKTSEGWAKVNALTNTGAIPDNACANPGQPTLPNYTFRSSRVSGDTDRDGEAKIESLPVKAYLVCETKTPGNIVQKAKPFVVTIPHPNTAAKADGTWLYDVHVYPKNEKIEVAKTIEDQRNNGYIVGSKVRFPVSSTLPKLDDNSYYKYYQFKDTLDNRLKQVTATDVTLGGTRLDEGTDYTLGTDGQTVTVTFNQNGLSKLKGNPGQKLQAVFEGVVSEVGDGSINNTAQLISDTTYAEQPPAPETPPANPDNPPTTEQVTSKWGDLTIKKVDGNDRSGDKDGLKGAEFQIYKAKDAYADTCSPEADGQPLTINGESTFTTGEGGTINFKALFVSDSVQDTGRDNRVDAPHRCYVLVETKAPAGYVLPADASRAITVEPGAGVTQQVVIDNVKQSVPGLPLTGANGMLILTASGAALLMIAVGSVLVARYRERKRNRDLAA

P12616 AF NFT

MOLNFT AF v1

NFT data

MOLNFT P12616 research and analysis (ICN3D with VR)

FASTA sequences

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