AIBasedDrugDiscovery using OpenVINO

Описание: Our application combines multiple AI-driven steps in the drug discovery process, covering essential predictions and synthesis planning. It helps researchers in:
Lipophilicity Prediction: Determining the hydrophobic or hydrophilic properties of a molecule, which influences its pharmacokinetics, such as absorption and distribution.
Binding Affinity Prediction: Predicting the strength of interaction between a drug candidate and its target protein, providing insight into potential efficacy.
Conformer Generation and Scoring: Generating 3D orientations (conformers) of molecules and scoring them for stability and binding potential, ensuring that the most viable molecular structures are prioritized.
Reaction Prediction and Visualization: Predicting potential chemical reactions and visualizing molecular structures, which aids in planning feasible synthesis pathways.
RAG-Enhanced Reaction Prediction: Utilizing retrieval-augmented generation (RAG) to integrate historical reaction data with model-based predictions, improving the accuracy and relevance of synthetic pathway suggestions.
The application serves as an AI-powered assistant, allowing researchers to evaluate drug candidates, generate synthetic pathways, and optimize drug properties, thereby accelerating the entire drug discovery pipeline.
https://github.com/AbhiLegend/AIDrugD...