AI for Chemistry & Drug Discovery
Machine learning applications in molecular generation, drug design, and cheminformatics
Explore the revolutionary intersection of artificial intelligence and chemistry, from molecular generation to drug-target prediction. These posts dive deep into computational approaches transforming pharmaceutical research and chemical discovery.
AI Agents in Biomedicine
The future of AI in biomedical research
Comprehensive exploration of autonomous AI agents revolutionizing drug discovery, clinical research, and personalized medicine approaches.
BioNumPy: Efficient Chemical Computing
High-performance cheminformatics with Python
Deep dive into BioNumPy’s applications for molecular data analysis and computational chemistry workflows, including molecular descriptors and chemical space exploration.
Statistical Methods in Cheminformatics
Essential statistics for chemical data analysis
Comprehensive overview of statistical methods used in cheminformatics and drug discovery, including QSAR modeling, activity prediction, and molecular property analysis.
Coming Soon: Molecular Generation with AI
Deep learning approaches to drug design
Explore cutting-edge generative models for molecular design, including VAEs, GANs, and transformer-based approaches for novel compound generation.
Research Areas
Molecular Generation
AI-driven design of novel chemical compounds
Drug-Target Prediction
Machine learning for therapeutic target identification
Protein-Protein Interactions
Computational approaches to molecular interactions
QSAR Modeling
Quantitative structure-activity relationships
Upcoming Topics
- Generative Models for Drug Discovery: VAEs, GANs, and flow-based models for molecular design
- Protein Folding Prediction: AI approaches to understanding protein structure
- Chemical Reaction Prediction: Machine learning for synthetic chemistry
- Drug Repurposing: AI-driven approaches to finding new uses for existing drugs
- Molecular Property Prediction: Deep learning for ADMET properties
- Multi-Modal Drug Discovery: Integrating chemical, biological, and clinical data
Technology Stack
Python Libraries
RDKit, DeepChem, PyTorch Geometric
Deep Learning
Graph Neural Networks, Transformers, VAEs
Cheminformatics
Molecular descriptors, fingerprints, similarity
Accelerating chemical discovery through the power of artificial intelligence and computational innovation.