DeepMSA: deep multiple sequence alignment generation

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●I-TASSER ●I-TASSER-MTD ●C-I-TASSER ●CR-I-TASSER ●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

DeepMSA

Deep Multiple Sequence Alignment Generation

DeepMSA is a composite approach to generate high quality multiple sequence alignment with large alignment depth and diverse sequence sources by merging sequences from whole-genome sequence databases (Uniclust30 and UniRef90) and from metagenome database (Metaclust). Large-scale benchmark data show that DeepMSA profiles consistently improves contact prediction, secondary structure prediction, and threading over default HHblits or PSI-BLAST profiles.

Online server (view example output)

Package download:

Download standalone package.
Download benchmark dataset.
Download per target assessment result on DeepMSA dataset, including detail assessment results for DeepMSA-guided contact prediction, threading, and secondary prediction.
Download DeepMSA results for CASP13 targets, including full-length and domain-level DeepMSA alignments, as well as DeepMSA-guided TripletRes and ResTriplet contact maps.

References:

Chengxin Zhang, Wei Zheng, S M Mortuza, Yang Li, Yang Zhang. DeepMSA: constructing deep multiple sequence alignment to improve contact prediction and fold-recognition for distant-homology proteins. Bioinformatics, 36: 2105-2112 (2020). [PDF] [Supporting Information]