A0A2K1J5A5 AF NFT

Protein SOSEKI 3

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeib5a3q2hz63rzigwckd7i2c7xcuwaw6npzc2yjekc2szfoxcz7qja/metadata.json
IPFS of structure file: 
bafybeihmdvbldz2lgoj7cicdxj3zpoj3276ckb3jaafjfjugw52zmp6vle/AF-A0A2K1J5A5-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x9e5E98E011361C5888c92e2CDb7652E02Bd5C7Ed
First NFT owner address (bech32): 
genesis1ne0f3cq3xcw93zxf9ckdkajjuq4at3ldwq49kv
Current NFT ID #432655 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
432655
Accession (UniProt):
A0A2K1J5A5
Name::
Protein SOSEKI 3
Experimental Method:
Predicted structure
Sequence source:
PHYSCOMITRIUM PATENS

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 A0A2K1J5A5 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A0A2K1J5A5|SOK3_PHYPA Protein SOSEKI 3 OS=Physcomitrium patens OX=3218 GN=SOK3 PE=1 SV=1 MARGEDSSSVQVLYQLSWDGKLEHPHMIEVHYPPNQGGLRLRDVKKRLTTLRGHGINDSFSWSSKRNYKNEFIWNDLCDDDVIQPLRGSGEYVLRASELFDTFTNKPWEHPSKHSNERMQSSRTMSVDNVTLQQGLINVKLHSGALAREDDQPSGEKLCCSGRRSCINLEDCSSKGVAIDIPKNLQNLSVDQETIDVEKSDFCLSSSDNEVSPRLKTAADCITPVKDVGLVVMTRSTTVHGLHTPAPRSLTSPTEPPFSPGSAKRMWKKEIRKSLFRTSRNSSNVNPVLSGENAALDVDVPPITLSTQEDVSFWRDGRSKSASPSSLNELREVQNEKEKEAEQSTSQLIRLLWARWTGGSSKGKRTPQSTCEDPLPKSPEAKQMPRSRTKTPCKEIRSTNHIAGSLPVTCPSPAVDNKAHSSLDRQEIPPQEECKNRPSPMTLQSCEEITSPVTEIEQDVEIGDIKAIVEEQASNKFPEPEFQQNLRTEQIVLSVQIPDLHIDALDSPTSDTQGSPAEADIPKSATARVKTSNSLPRVKTTTSPKPLPPGFHKGTNDTKPVQIITPRRTPRTSIPLASPPPLVRTFNRVSVRSLSSIAAITLSPENDSAASNLSPENPIVKKRINFRERDEMPLIPGLTTLDWEKALQEAVTDCLPPPNFREILQECSTCGRTFKPDSLQVHMRGCHPPQYARAFSARASPHVVRSRAS