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●I-TASSER ●I-TASSER-MTD ●C-I-TASSER ●CR-I-TASSER ●DMFold ●QUARK ●C-QUARK ●LOMETS ●MUSTER ●CEthreader ●SEGMER ●DeepFold ●DeepFoldRNA ●FoldDesign ●COFACTOR ●COACH ●MetaGO ●TripletGO ●IonCom ●FG-MD ●ModRefiner ●REMO ●DEMO ●DEMO-EM ●SPRING ●COTH ●Threpp ●PEPPI ●BSpred ●ANGLOR ●EDock ●BSP-SLIM ●SAXSTER ●FUpred ●ThreaDom ●ThreaDomEx ●EvoDesign ●BindProf ●BindProfX ●SSIPe ●GPCR-I-TASSER ●MAGELLAN ●ResQ ●STRUM ●DAMpred

●TM-score ●TM-align ●US-align ●MM-align ●RNA-align ●NW-align ●LS-align ●EDTSurf ●MVP ●MVP-Fit ●SPICKER ●HAAD ●PSSpred ●3DRobot ●MR-REX ●I-TASSER-MR ●SVMSEQ ●NeBcon ●ResPRE ●TripletRes ●DeepPotential ●WDL-RF ●ATPbind ●DockRMSD ●DeepMSA ●FASPR ●EM-Refiner ●GPU-I-TASSER

●BioLiP ●E. coli ●GLASS ●GPCR-HGmod ●GPCR-RD ●GPCR-EXP ●Tara-3D ●TM-fold ●DECOYS ●POTENTIAL ●RW/RWplus ●EvoEF ●HPSF ●THE-DB ●ADDRESS ●Alpaca-Antibody ●CASP7 ●CASP8 ●CASP9 ●CASP10 ●CASP11 ●CASP12 ●CASP13 ●CASP14

DMFold standalone package is an integrated program of DeepMSA2 and AlphaFold2 for protein monomer and protein complex structure prediction. Please report bugs and questions at Zhang Lab Service System Discussion Board. The DMFold package is free for academic and non-profit researchers.

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DMFold download:

• For academic users, please click here to download the DMFold package.
• If you need DMFold for a commercial use, please contact us through zhanglabzhanggroup.org

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Release Note:

v1.2 (2024/03/22)
1. Fix a MSA combination scoring function issue in MSA_combination.py

v1.1 (2024/02/09)
1. Fix a JGI search bug when dMSA does have enough sequences but qMSA does not
2. Update Install_af2_env.sh with the numpy and tensorflow
3. Add pLDDT score to b-factor for monomer modeling

v1.0 (2024/01/01)
original version of DMFold

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We recommand you use "Download_lib.py" in DMFold package to download all required databases. However you can also manually download all sequence library below:

The third-party genomics and metagenomics sequence databases used in DMFold.

• uniclust30_2017_04: Uniclust30 HHblits style HMM sequence library (for MSA construction).
• uniref90: UniRef90 library (for MSA construction).
• metaclust: Metaclust library (for MSA construction).
• UniRef30_2022_02: UniRef30 HHblits style HMM sequence library (for MSA construction).
• BFD: BFD HHblits style HMM sequence library (for MSA construction).
• MGnify: MGnify library (for MSA construction).

DMFold sequence library, JGIclust, TaraDB and MetaSourceDB metagenome databases with 30% redundancy removed, producted by Zhang Lab (for MSA construction). We recommand you download the DMFold first, then use Download_lib.py download this library.

• JGI list
• DB.fasta.aa
• DB.fasta.aa.ssi
• DB.fasta.ab
• DB.fasta.ab.ssi
• DB.fasta.ac
• DB.fasta.ac.ssi
• DB.fasta.ad
• DB.fasta.ad.ssi

AlphaFold2 library used in DMFold for MSA ranking and pairing:

• AlphaFold2 parameters.
• PDB70 library.
• MMCIF format coordinates.

AlphaFold2-Multimer library used in DMFold for model generation:

• PDB sequences.
• Small BFD sequence database.
• Uniprot sequence database.

How to cite DMFold?

• 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.