Software - Schneidman Lab @ HUJI

Software & Web Servers

Antibodies

Epitope-specific antibody and nanobody generation using language model embeddings.

Modeling antibody heavy chains or nanobodies using deep learning. The output is a 3D structure.

GitHub repository

Rapid modeling of antibody-antigen and nanobody-antigen complexes.

GitHub repository

Docking & Assembly

Predicting structures of large protein assemblies using combinatorial assembly algorithm and AlphaFold.

Molecular docking algorithm based on shape complementarity principles. For proteins, DNA, peptides, and drugs.

Prediction of complexes with Cn symmetry by geometry based docking.

Rhodopsins

Computational prediction of rhodopsin absorption maxima using geometric deep learning.

GitHub repository

Variant Effect Prediction

Calibrated variant effect prediction at the residue level using conditional score distributions.

Domain-Peptide Interactions

Scalable prediction of domain-peptide specificity using contrastive learning.

Modeling with SAXS Profiles

Fast SAXS profile computation with Debye formula.

Multi-state modeling with SAXS profiles for interpretation of data collected for heterogeneous samples.

Macromolecular docking with SAXS Profile of the complex.

Deep-learning modeling of RNA structures and magnesium ion positions using experimental SAXS data.

📂 SAXS tutorial files - Input files for FoXS, MultiFoXS, BilboMD, and FoXSDock.