Q7XWP3 AF NFT

Probable protein transport Sec1a

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeieqotgofdflus4cnuqvpf5ymlrvs3nlkogwzho72ajwqx6qqthtoa/metadata.json
IPFS of structure file: 
bafybeiabim43cqlm5mip4ep4ztxwdysqw2kci7twjvl2gtra7arsuihqfe/AF-Q7XWP3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7430138aDC76d97a0F1f6f3F14D160cC0dBf5ae6
First NFT owner address (bech32): 
genesis1wscp8zkuwmvh5rcldul3f5tqesxm7khxppe79d
Current NFT ID #423341 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
423341
Accession (UniProt):
Q7XWP3
Name::
Probable protein transport Sec1a
Experimental Method:
Predicted structure
Sequence source:
ORYZA SATIVA SUBSP. JAPONICA

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 Q7XWP3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q7XWP3|SEC1A_ORYSJ Probable protein transport Sec1a OS=Oryza sativa subsp. japonica OX=39947 GN=Os04g0252400 PE=3 SV=2 MSMDSVISSRSGADYRSFRQITRDRLLFEMLRSTKKSSKSAWKVLIMDKLTVKIMSFSCKMADVMEEGVSLVEDLYMRRQPLPLMDAIYFIQPTKENIRIFMSDMSGKIPLYKKAYVFFSSPVQRELVAQIKKDSNVRARIGALSEMNLEYFAIDSQGFTTDHDKALEELFSENAEGSLKYNSCLNMMATRIATVFASMREFPRVHYRVARTIDASTLTTLRDLAPTKLAAGVWNCLARFKAMIPEFPQTETCELLIVDRSIDQIAPIIHEWTYDAMCHDLLCMDGNKYVQQVPSKSGSGTENKEVLLEDHDPIWLELRHVHIANASERLHEKMTNFVSKNKAAQLHQARNGGDLSTKELQKMVQALPQYSDQIDKLALHVEIAGKLNSTIKEQQLKDVGQLEQDLVFGDAGTKELINFFRTHLDISRENKLRLLMVYAAINPDKTRSDKGAKLMQLAGLSADDMIAVSNMRCLCGHDSKKSSAGGFTLKFDLRKKRHGIRKERIGEESKWMLSRFYPILEELIEKLSKGELPKDEYHYLNDPSPSFRGIPSASTQTSPAHQPAQSMRSRRTGGTWARPRDSDDGYSSDSVLKHTSSNSRKLGQRLFVFVIGGATRSELCAAHKLSSKLKREIILGSSSLDDPPQFITKLKMLSTDDLTLDDLQI