DrugHIVE: Structure-based drug design with a deep hierarchical generative model
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Updated
Jul 22, 2024 - Python
DrugHIVE: Structure-based drug design with a deep hierarchical generative model
TAGMol: Target-Aware Gradient-guided Molecule Generation
This package facilitates molecular docking simulations aimed at analyzing interactions between a target biological system and a collection of potential drug molecules. By leveraging computational algorithms, it ranks these molecules based on docking scores and interaction energies, providing insights into their suitability as drug candidates.
Here I am sharing a package containing scripts for SIFt analysis. These tools enable the user to compare the SIFts of docked ligands with a averaged reference SIFt by calculating the Tanimoto coefficients.
Script enables researchers to parse through ChEMBL bioactivity reports in relation to a specific biological target and provides insight into some important for Computer-Aided Drug Design (CADD) features.
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