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DMFold results for example

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Input Sequence In FASTA Format

example ( 1221 residues )
>example-A
EIMPLTLKVNGKTEQLEVDTRTTLLDTLRENLHLIGTKKGCDHGQCGACTVLVNGRRLNACLTLAVMHQGAEITTIEGLGSPDNLHPMQAAFIKHDGFQCGYCTSGQICSSVAVLKEIQDGIPSHVTVDLVSAPETTADEIRERMSGNICRCGAYANILAAIEDAAGEIKS

>example-B
MKAFTYERVNTPAEAALSAQRVPGAKFIAGGTNLLDLMKLEIETPTHLIDVNGLGLDKIEVTDAGGLRIGALVRNTDLAAHERVRRDYAVLSRALLAGASGQLRNQATTAGNLLQRTRCPYFYDTNQPCNKRLPGSGCAALEGFSRQHAVVGVSEACIATHPSDMAVAMRLLDAVVETITPEGKTRSITLADFYHPPGKTPHIETALLPGELIVAVTLPPPLGGKHIYRKVRDRASYAFALVSVAAIIQPDGSGRVALGGVAHKPWRIEAADAQLSQGAQAVYDTLFASAHPTAENTFKLLLAKRTLASVLAEARAQA

>example-C
MKFDKPAGENPIDQLKVVGRPHDRIDGPLKTTGTARYAYEWHEEAPNAAYGYIVGSAIAKGRLTALDTDAAQKAPGVLAVITASNAGALGKGDKNTARLLGGPTIEHYHQAIALVVAETFEQARAAASLVQAHYRRNKGAYSLADEKQAVNQPPEDTPDKNVGDFDGAFTSAAVKIDATYTTPDQSHMAMEPHASMAVWDGNKLTLWTSNQMIDWCRTDLAKTLKVPVENVRIISPYIGGGFGGKLFLRSDALLAALAARAVKRPVKVMLPRPSIPNNTTHRPATLQHLRIGADQSGKITAISHESWSGNLPGGTPETAVQQSELLYAGANRHTGLRLATLDLPEGNAMRAPGEAPGLMALEIAIDELAEKAGIDPVEFRILNDTQVDPADPTRCFSRRQLIECLRTGADKFGWKQRNATPGQVRDGEWLVGHGVAAGFRNNLLEKSGARVHLEQNGTVTVETDMTDIGTGSYTILAQTAAEMLGVPLEQVAVHLGDSSFPVSAGSGGQWGANTSTSGVYAACMKLREMIASAVGFDPEQSQFADGKITNGTRSATLHEATAGGRLTAEESIEFGTLSKEYQQSTFAGHFVEVGVHSATGEVRVRRMLAVCAAGRILNPKTARSQVIGAMTMGMGAALMEELAVDDRLGYFVNHDMAGYEVPVHADIPKQEVIFLDDTDPISSPMKAKGVGELGLCGVSAAIANAVYNATGIRVRDYPITLDKLLDKLPDVV

  Multiple Sequence Alignments

Alignment depth: Nf=123.769, number of sequences=4849


  • Download multiple sequence alignment in aln format.
  • Download multiple sequence alignment in a3m format.
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     Top 5 Final Models From DMFold

    Click
    to view    		 RankDownload PDBpTM-score
    1 model1.pdb.gz 0.97
    2 model2.pdb.gz 0.97
    3 model3.pdb.gz 0.97
    4 model4.pdb.gz 0.97
    5 model5.pdb.gz 0.97

    Note: If the JSmol model is not visible, please refresh the page or click the radio buttons

    (a) DMFold generates a large set of structural models by different MSAs as inputs. These models are ranked by predicted TM-score (pTM-score for multimer) or predicted LDDT (pLDDT for monomer) and top 5 models are selected with the highest predicted scores.

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    Reference:
  • Wei Zheng, Qiqige Wuyun, Yang Li, Chengxin Zhang, P Lydia Freddolino, Yang Zhang. Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data. Nature Methods, (2024). https://doi.org/10.1038/s41592-023-02130-4.
  • Wei Zheng, Quancheng Liu, Qiqige Wuyun, P. Lydia Freddolino, Yang Zhang. DMFold: A deep learning platform for protein complex structure and function predictions based on DeepMSA2. In preparation.
  • Wei Zheng, Qiqige Wuyun, Peter L Freddolino, Yang Zhang. Integrating deep learning, threading alignments, and a multi-MSA strategy for high-quality protein monomer and complex structure prediction in CASP15. 1-20. Proteins. (2023). doi:10.1002/prot.26585.

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