Structural Antibody Tools
Here we compile the list of computational tools you can use to annotate and structurally model antibody sequences. Scroll down the page to browse the tools.
If you find this information useful and you would like to cite it, please refer to:
Tools
Please click on the name of the tool to go to its webpage.
| Tool Type | Tool name | Tool Description |
| Antibody Numbering | ANARCI | Online and offline numbering of antibodies using variety of schemes (North, Chothia, Kabat, IMGT etc.s) |
| Antibody Numbering | Abnum | Online numbering of antibodies. |
| Sequence Analysis | IgBLAST | Nucleotide and amino acid antibody sequence analysis in IMGT and KABAT schemes. |
| Sequence Analysis | IMGT/V-QUEST | Online antibody nucleotide sequence analysis in IMGT numbering scheme. |
| Structure Database | SAbDab | Self-updateable database of antibody structures. |
| Structure/Sequence Database | Abysis | Database of antibody structures and sequences. |
| Sequence Database | DIGIT | Database of antibody sequences |
| Fv Modeling | ABodyBuilder | Very rapid modeling of the entire antibody Fv region (0.5 m per model) |
| Fv Modeling | PIGSPro | Rapid modeling of entire Fv region. |
| Fv Modeling | Kotai Antibody Builder | Rapid modeling of entire Fv region. (90m per model) |
| Fv Modeling | RosettaAntibody | Modeling of entire Fv region (up to several days) |
| Fv Modeling | Accelrys | Hybrid modeling (30m per model) |
| Protein Modeling | MODELLER | General-purpose protein modeling software. |
| Loop Modeling | Sphinx | H3-specific loop modeling. |
| Loop Modeling | FREAD | Generic template-based loop modeling software. |
| Loop Modeling | PLOP | Ab initio loop modeling software. |
| Paratope Prediction | Paratome | Structural consensus to identify additional antigen recognizing regions outside the CDRs |
| Paratope Prediction | Antibody i-Patch | Statistical inference to devise a likelihood for a position to form a potential contact |
| Paratope Prediction | proABC | Sequence-based method that leverages machine learning to predict residues that form interactions |