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Geometric deep learning method to predict protein binding interfaces from a protein structure.
AlphaFold Meets Flow Matching for Generating Protein Ensembles
User friendly and accurate binder design pipeline
Repository used with Google Colab notebooks for our IDR ensemble dimension predictors.
CosolvKit is a versatile tool for cosolvent MD preparation and analysis
Scripts for the creation of CryptoBench, a new dataset of cryptic binding sites
Chai-1, SOTA model for biomolecular structure prediction
Discovering Interpretable Features in Protein Language Models via Sparse Autoencoders
A python package for generating disordered sequences and disorder sequence variants.
MCGLPPI and MCGLPPI++: Integration of molecular coarse-grained model into geometric representation learning framework for protein-protein complex property prediction
A protein pre-trained model-based approach for the identification of the liquid-liquid phase separation (LLPS) proteins
Wrapper for RDKit's RunReactants to improve stereochemistry handling
RXNMapper: Unsupervised attention-guided atom-mapping. Code complementing our Science Advances publication on "Extraction of organic chemistry grammar from unsupervised learning of chemical reactio…
A Machine Learning Model to Predict Phase Separation Driving Residues
The standalone toolkit for generating PSSM-based features for machine learning based protein sequence analysis.
OpenMM implementation of MOFF, MRG-CG, and HPS models.
Next generation sequence parameter library for proteins
Code for downloading and using the TAO dataset: http://taodataset.org/