mulecule protein binding affinity prediction
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Updated
Jul 3, 2023 - Python
mulecule protein binding affinity prediction
Group project for Fall 2020 Computational Medicine course.
NeuralMD for protein-ligand binding MD simulation
🤗 Hugging Face space for gnina-torch 🔥
Code for Binding Affinity Prediction with Graph Neural Networks
Package to solve multiple chemical equilibria problems.
Final Project of Deep Learning for Healthcare Spring 2022 - Reproducing DeepDTA
MolPro is a comprehensive python package for small molecule generation using protein active site or/and similar molecules using 3D information of molecules with in-silico validation of molecules by docking , pharmacophore hypothesis. Also off target prediction based on the binding site similarities.
TAG-DTA: Binding Region-Guided Strategy to Predict Drug-Target Affinity Using Transformers
Prediction of Absolute Ligand-Protein Binding Affinity
Predicts the dissociation coefficients between drug-protein (target) pairs using molecular fingerprints and physicochemical protein properties.
Official Implementation of Compass
Repository for the Taba tool
Predict binding affinity of ligand-protein complexes using Graph Neural Networks. The model is implemented using PyTorch Geometric and based on the method in "Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks"
Predicting the effect of mutations on protein stability and protein-protein interaction affinity.
Create customized voxel representations of protein-ligand complexes using GPU.
Predicting the effect of mutations on protein stability and protein binding affinity using pretrained neural networks and a ranking objective function.
Dataset with quantitative binding scores of scFv-format antibodies against SARS-CoV-2 target peptide
PSICHIC (pronounced Psychic) - PhySIcoCHemICal graph neural network for learning protein-ligand interaction fingerprints from sequence data
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