FlexPose, a framework for AI-based flexible modeling of protein-ligand binding pose.
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Updated
Dec 27, 2023 - Python
FlexPose, a framework for AI-based flexible modeling of protein-ligand binding pose.
Code for "T Cell Receptor Specificity Prediction with Bimodal Attention Networks" (https://doi.org/10.1093/bioinformatics/btab294, ISMB 2021)
Target-aware Variational Auto-encoders for Ligand Generation with Multimodal Protein Representation Learning
drugdesign.org source of truth
SAnDReS (Statistical Analysis of Docking Results and Scoring functions) is a free and open-source computational environment for the development of machine-learning models for the prediction of ligand-binding affinity. We developed SAnDReS using Python programming language, and SciPy, NumPy, scikit-learn, and Matplotlib libraries as a computational
Open-sourced docking for small molecule to protein target. It prioritizes enhanced user-friendliness and accessibility.
R shiny app to analyse microscale thermophoresis (MST) data
Two R shiny apps developed for analyzing differential scanning fluorimetry (DSF) data. One for binding, and one for stability
Performs large-scale ligand identification, curation and extraction from human structures in the Protein Data Bank.
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