SAMPDI-3D webserver

About SAMPDI-3D

SAMPDI-3D uses a gradient boosting decision tree machine learning algorithm with features as physicochemical properties, structure of mutation site and protein-DNA interactions to predict the change of binding free energy. SAMPDI-3D outperforms all existing state-of-the-art methods in both the Pearson correlation coefficient and root-mean-squared-error parameters for several independent datasets(available here). Users can also download SAMPDI-3D stand alone code (available here) and use it locally.

Cite "Bioinformatics, 2021 Aug 3;btab567. doi: 10.1093/bioinformatics/btab567"

ΔΔG change for protein mutation
ΔΔG change for DNA mutation

Protein's single residue mutation (single mode)

Protein-DNA complex structure

Choose a .pdb file

Protein mutation detail

Chain:

Position:

Wildtype:

Mutated:

Protein's multiple residue(s) mutation (batch mode)

Protein-DNA complex structure

Choose a .pdb file

Protein mutation list file

Upload a plain text file with one mutation per line, click here to view an example for reference

Mutations list (allowed only .txt)

DNA's single basepair mutation (single mode)

Protein-DNA complex structure

Choose a .pdb file

DNA mutation detail

Chain:

Position:

Wildtype:

Mutated:

DNA's multiple basepair(s) mutation (batch mode)

Protein-DNA complex structure

Choose a .pdb file

DNA mutation list file

Upload a plain text file with one mutation per line, click here to view an example for reference

Mutations list (allowed only .txt)

SAMPDI-3D: Predicting protein-DNA binding free energy change upon mutations

Emil Alexov Group