Research Poster and Report from a breast cancer research study for which I contributed to as part of an internship at BMCC.
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Updated
Sep 20, 2024
Research Poster and Report from a breast cancer research study for which I contributed to as part of an internship at BMCC.
Official Implementation of CompassDock
PSICHIC (pronounced Psychic) - PhySIcoCHemICal graph neural network for learning protein-ligand interaction fingerprints from sequence data
Create customized voxel representations of protein-ligand complexes using GPU.
Predict the binding affinity of protein-protein complexes from structural data
NeuralMD for protein-ligand binding MD simulation
Repository for the Taba tool
Package to solve multiple chemical equilibria problems.
TAG-DTA: Binding Region-Guided Strategy to Predict Drug-Target Affinity Using Transformers
mulecule protein binding affinity prediction
Predicts the dissociation coefficients between drug-protein (target) pairs using molecular fingerprints and physicochemical protein properties.
Dataset with quantitative binding scores of scFv-format antibodies against SARS-CoV-2 target peptide
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"
🤗 Hugging Face space for gnina-torch 🔥
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.
Prediction of Absolute Ligand-Protein Binding Affinity
Code for Binding Affinity Prediction with Graph Neural Networks
Predicting the effect of mutations on protein stability and protein-protein interaction affinity.
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