Volume 4,Issue 6
Integrating Computer-Aided and AI-Driven Drug Design into Medicinal Chemistry Education: A Computational Course on EGFR L858R/V948R-Targeted Oral Anti-Lung Cancer Agents
The traditional medicinal chemistry education suffers from the high barrier of equipment and the teaching of modern computational methods. To solve this, we designed an AI-assisted computational drug design course, “Design of Oral Anti-Lung Cancer Drugs Targeting EGFR L858R/V948R,” for pharmacy undergraduates. The course focuses mainly on a resistant mutation in NSCLC and employs a structured workflow with several software tools such as Schrödinger, PyMOL, MolSnapper, Pipeline Pilot and GROMACS. Through 16 class hours, students can complete the closed-loop learning experience from target selection to candidate compound confirmation. In summary, this course is helpful for technical barriers, encourages students to form an interdisciplinary thinking consciousness, and provides a transferable model for the modernization of hands-on medicinal chemistry education.
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