| Course name |
Pharmacy |
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| Study-unit Code |
A005441 |
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| Curriculum |
Comune a tutti i curricula |
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| Lecturer |
Maria Letizia Barreca |
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| Lecturers |
|
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| Hours |
- 28 ore - Maria Letizia Barreca
|
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| CFU |
4 |
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| Course Regulation |
Coorte 2022 |
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| Supplied |
2025/26 |
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| Learning activities |
Affine/integrativa |
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| Area |
Attività formative affini o integrative |
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| Sector |
CHIM/08 |
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| Type of study-unit |
Opzionale (Optional) |
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| Type of learning activities |
Attività formativa monodisciplinare |
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| Language of instruction |
Italian |
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| Contents |
Introduction to current challenges in drug discovery. Fragment-Based Drug Discovery (FBDD). Targeted Protein Degradation (TPD). Chemical probes. Artificial Intelligence in Drug Discovery. Specialized databases and online resources. |
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| Reference texts |
G. Costantino, G. Sbardella - CHIMICA FARMACEUTICA (EdiSES), 2024 (I Ed.) |
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| Educational objectives |
The course aims to provide a solid conceptual understanding of the latest frontiers in drug discovery. Key knowledge acquired will include: - The fundamental principles and advantages of the technologies presented (FBDD, databases and web resources, chemical probes, Artificial Intelligence, Targeted Protein Degradation); - The role and potential of Artificial Intelligence in supporting the rational discovery of new drugs; - The theoretical criteria for combining different methodologies into a coherent, innovative research workflow. Key skills (i.e., the ability to apply the acquired knowledge) will include: - Critically evaluating the scientific literature related to the topics covered; - Efficiently navigating and querying the main databases and online resources dedicated to pharmaceutical chemistry; - Theoretically integrating the knowledge gained into research workflows in order to propose innovative drug-discovery strategies. |
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| Prerequisites |
The student enrolling in this course is expected to have a solid background in medicinal chemistry and pharmacology. |
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| Teaching methods |
Lectures in the classroom covering all course topics, supported by slides that will be made available to students in electronic format during the course. |
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| Learning verification modality |
The exam consists of a final oral test, involving a discussion of the topics covered during the course and listed in the syllabus. The aim is to assess the student’s knowledge and understanding of the subject matter, as well as their ability to analyze, summarize, and critically elaborate on the content. Communication skills and the appropriate use of scientific language will also be evaluated. |
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| Extended program |
-Fragment-Based Drug Discovery (FBDD): Introduction to FBDD; Fragment Identification; Fragment Optimization; Applications and Case Studies. -Targeted Protein Degradation (TPD): Introduction to TPD; PROTACs and Bifunctional Molecules; Alternative TPD Strategies; Applications and Case Studies. -Chemical Probes: Introduction to Chemical Probes; Design and Selection of Chemical Probes; Applications and Case Studies. -Artificial Intelligence (AI) in Drug Discovery: Introduction to AI; Ligand-Based and Structure-Based Approaches; Applications and Case Studies; Limitations, Challenges, and Future Perspectives. -Databases and Online Resources in Drug Discovery: The Role of Databases in Pharmaceutical Research; Chemical and Bioactivity Databases; Structural and Target Databases; Patents and Literature Sources; Integrated Platforms and Tools for Drug Discovery. |
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| Obiettivi Agenda 2030 per lo sviluppo sostenibile |
3. Good Health and Well-being; 4. Quality Education |
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