Biochemistry and Molecular Biology, as a discipline that reveals life phenomena at the molecular level, is a core foundational course in medical education. However, its complicated content and highly abstract concepts have posed a dual challenge for traditional teaching models: "inefficient teaching and insufficient learning outcomes". How to attract students and stimulate their intrinsic motivation within limited classroom time, and how to help students recognize, understand, and develop a passion for biochemistry from the perspective of the discipline's essence, have always been key focuses of curriculum research. This study mainly utilizes the Rain Classroom, a generative Artificial Intelligence (AI)-assisted platform, integrating four dimensions—"teaching, learning, evaluation, and research"—to support education. Taking the chapter of lipid metabolism as an example, it aids teaching through virtual experiments, lesson preparation, knowledge mapping, and assignment design; learning through intelligent study assistant, assignment review, educational resource sharing, and learning path planning; evaluation through grading assignment and tallying up the results, teaching diagnostics and recommendations, and research through data collection and analysis, literature search and summarization. The results of this study indicate that an educational model, instructor-focused instruction, student-focused learning, and generative AI assistance, significantly improves teaching quality, students' independent learning skills, and knowledge mastery. Additionally, ideological education in curriculum with the assistance of Generative AI, focuses on cutting-edge advances in disciplinary and hot topics in medicine, helping establish correct professional values. This study shows the application process of generative AI in assisting biochemistry education and analyzes potential risks in practice to ensure that technological tools consistently serve the core purpose of education.