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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


About SAXSTER server

What is the SAXSTER server?

SAXSTER server is an internet service to couple the raw SAXS data with protein fold-recognition algorithms to improve template-based protein structure predictions.


How does SAXSTER identify the best templates?

The SAXS-assisted MUSTER fold-recognition algorithm, SAXSTER, consists of five steps: threading-based template identification, full-length model construction by I-TASSER, coarse-grained SAXS profile calculation, SAXS data matching, and template re-ranking. The inputs of SAXSTER include the amino acid sequence of the target protein and its respective SAXS data (either intensity profile in reciprocal space or Pair Distance Distribution Function, PDDF, in real space), with the outputs being the Top 10 template structures and the query-template alignments (see Figure 1). The SAXSTER server also provides full-atomic models built by MODELLER from the Top 10 alpha-Carbon trace generated by I-TASSER from the threading alignments.


Figure 1. Flowchart of SAXSTER to combine SAXS data and MUSTER for protein structure prediction.

How to cite SAXSTER

You are requested to cite following article when you use the SAXSTER server:

Contact information

The SAXSTER server is in active development with the goal to provide the reliable structure predictions. Please help us achieve the goal by sending your questions, feedback, and comments to: yangzhanglab@umich.edu.

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