MODLAB
The Molecular Design Laboratory (MODLAB) develops and implements new concepts, algorithms, and software for the rapid identification of bioactive molecules and pharmaceutical lead structures.
We envision a future where artificial intelligence (AI)-driven technologies enable sustainable high-quality drug discovery, accelerate the development of safe, effective treatments, optimize therapies, and improve patient outcomes.
Molecular design requires trans-disciplinary thinking. We use a broad range of machine learning methods and bio/cheminformatics techniques for automated hypothesis generation, activity prediction, and validation.
Working closely with chemical synthesis and biochemical activity testing, we assess computer-generated hypotheses and methods for their practical application in medicinal chemistry. Our studies primarily focus on the machine-driven de novo design of small molecules and peptides with specific pharmacological activity.
Our research includes drug repurposing, target profile prediction and drug polypharmacology, analysis of protein structure and modulation of protein-protein interaction, virtual compound screening, the design of natural product analogs and peptides, and the de-orphanizing of drugs and their biological activities.