Molecular Modeling for Drug Discovery Lab

4 Credits.

This graduate-level virtual laboratory immerses students in the computational techniques that drive modern drug discovery and target validation. Through a series of hands-on modules, students will learn to design, implement, and interpret computational workflows used across academia, biotech, and pharmaceutical R&D. The course emphasizes practical skill-building in molecular modeling, structure preparation, ligand design, docking, virtual screening, cheminformatics, and ADMET prediction. Students will work with real protein structures, chemical libraries, and biological datasets to evaluate target druggability, identify potential lead compounds, and assess pharmacological properties. Using industry-standard and open-source tools, students will gain experience constructing reproducible computational pipelines that mirror early-stage discovery processes. The course integrates structural biology, medicinal chemistry principles, and data-driven decision-making to provide a comprehensive understanding of how computational methods support and accelerate drug development. By the end of the course, students will be able to independently execute computational experiments, critically analyze results, and communicate findings in formats aligned with professional scientific practice. Prerequisites: 410.751 Drug Design and Chemical Libraries.