タイトル

開講年度 開講学部等
2025 大学院創成科学研究科（博士前期）
開講学期 曜日時限 授業形態 AL（アクティブ・ラーニング）ポイント
前期集中 集中   3.0
時間割番号 科目名[英文名] 使用言語 単位数
3272170005 生物機能科学特別講義Ⅰ[Special lecture for Biological Sciences Ⅰ] 日本語 1
担当教員（責任）[ローマ字表記] メディア授業
非常勤 講師 ー
担当教員[ローマ字表記]
非常勤 講師, 今村 博臣
特定科目区分   対象学生   対象年次 1～2
ディプロマ・ポリシーに関わる項目 カリキュラムマップ(授業科目とDPとの対応関係はこちらから閲覧できます)
授業の目的と概要
Since the completion of the Human Genome Project, the life sciences have advanced remarkably. The acceleration and cost reduction of genome analysis have made it possible to obtain genetic information at the individual level, paving the way for personalized medicine. Furthermore, advances in omics technologies and systems biology have established integrated and multilayered approaches to understanding biological information such as genes, proteins, and metabolites.

In recent years, AI technologies—especially the revolutionary protein structure prediction by AlphaFold—have garnered significant attention. These advances have extended to predicting interactions between protein complexes and DNA, RNA, or ligands, thereby accelerating drug discovery and disease research. Enzymes and structural proteins are essential to biological activity, and by interpreting sequence data as a "language," the application of large language models (LLMs) and generative AI is progressing. This trend is deepening our understanding of biological functions and enabling novel molecular design.

In this course, students will learn the fundamentals of enzyme and protein engineering in the post-genomic era. Practical exercises using personal computers will also be included.
授業の到達目標
The aim of this course is to equip students with up-to-date knowledge and critical thinking skills related to modern enzyme and protein engineering.
授業計画
【全体】
Throughout the course, students will be introduced to both the fundamentals and applied examples of enzyme and protein engineering, with concrete case studies provided. Assessment will be based on reports and assignments completed during practical sessions.
項目 内容 授業時間外学習 備考
第1回 Advanced Enzyme and Protein Engineering 1 This lecture provides an overview of life sciences in the post-genomic era, covering genome analysis, omics technologies, systems biology, and the positioning of enzyme and protein engineering within these scientific developments. Approximately two hours of preparation and review are expected for each class session.
第2回 Advanced Enzyme and Protein Engineering 2 An overview of structural biology and protein engineering in the post-genomic era will be provided, with a focus on the application of AI technologies, including AlphaFold and generative AI for sequence and structure prediction. Approximately two hours of preparation and review are expected for each class session.
第3回 Advanced Enzyme and Protein Engineering 3 An overview will be given on AI-driven structure prediction, structure generation, and sequence generation in the post-genomic era, highlighting recent advances and applications of artificial intelligence in protein science. Approximately two hours of preparation and review are expected for each class session.
第4回 Advanced Enzyme and Protein Engineering 4 Structure and function prediction of enzymes and proteins using web-based tools will be introduced. This includes platforms such as BRENDA, Foldseek, ConSurf, AlphaFold, Boltz, and NeuroBind. Approximately two hours of preparation and review are expected for each class session.
第5回 Enzyme and Protein Bioinformatics 1 This module covers computational approaches and algorithms using Python, including graph theory, network theory, and protein structural informatics. The content will be adjusted according to the proficiency level of participating students. Approximately two hours of preparation and review are expected for each class session.
第6回 Enzyme and Protein Bioinformatics 2 This module covers computational approaches and algorithms using Python, including graph theory, network theory, and protein structural informatics. The content will be adjusted according to the proficiency level of participating students. Approximately two hours of preparation and review are expected for each class session.
第7回 Enzyme and Protein Bioinformatics 3 This module covers computational approaches and algorithms using Python, including graph theory, network theory, and protein structural informatics. The content will be adjusted according to the proficiency level of participating students. Approximately two hours of preparation and review are expected for each class session.
第8回 Shaping the Future of Enzymes through Informatics This lecture introduces cutting-edge research in enzyme and protein engineering, with a focus on achievements conducted at Shizuoka Prefectural University. Approximately two hours of preparation and review are expected for each class session.
※AL（アクティブ・ラーニング）欄に関する注
・授業全体で、AL（アクティブ・ラーニング）が占める時間の割合を、それぞれの項目ごとに示しています。
・A〜Dのアルファベットは、以下の学修形態を指しています。
【A：グループワーク】、【B：ディスカッション・ディベート】、【C：フィールドワーク（実験・実習、演習を含む）】、【D：プレゼンテーション】
A: --%　B: --%　C: 30%　D: --%
成績評価法
Grading will be based on reports (50%) and in-class assignments (50%).
教科書にかかわる情報
備考
All necessary materials for the course will be distributed during class sessions.
参考書にかかわる情報
備考
メッセージ
キーワード
持続可能な開発目標（SDGs）

関連科目
履修条件
連絡先
Hiromi Imamura
imamura-h(at)yamaguchi-u.ac.jp
オフィスアワー
Weekday 14~17

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