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ADVANCED DRUG DISCOVERY
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ADVANCED DRUG DISCOVERY
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Academic year 2024/2025
- Course ID
- BIO0161 Pds 308-BIDD
- Teachers
- Giulia Caron
Giuseppe Ermondi - Degree course
- [0101M22] Molecular Biotechnology
- Year
- 2nd year
- Teaching period
- First semester
- Type
- Related or integrative
- Credits/Recognition
- 5
- Course disciplinary sector (SSD)
- CHIM/08 - pharmaceutical chemistry
- Delivery
- Formal authority
- Language
- English
- Attendance
- Obligatory
- Type of examination
- Oral
- Type of learning unit
- corso
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Sommario del corso
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Course objectives
The course will contribute to the educational objectives of the Biomedical Imaging and Drug Discovery programme, offered as part of the Molecular Biotechnology course. It will allow students to approach a drug discovery project with appropriate in-silico tools.
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Results of learning outcomes
KNOWLEDGE AND UNDERSTANDING
Learning the use of advanced in-silico techniques used in the drug discovery process
APPLYING KNOWLEDGE AND UNDERSTANDING
Development of the ability to incorporate common in-silico methods and information provided by various internet sources into daily research work
MAKING JUDGEMENTS
Critical evaluation of the information obtained from the use of in-silico techniques
COMMUNICATION SKILLS
Acquisition of oral and written communication of results as well as the ability to use graphical language
LEARNING SKILLS
Acquisition of autonomous learning capacity and self-assessment of its preparation
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Program
Preparation of the reports
- Basic rules
- Use of a template
Structural databases
- Introduction to the use of free molecular modeling software (e.g., Chimera)
- PDB, CSD
- AlphaFold
Molecular docking and ligand-based virtual screening
- Theoretical background
- Use of free webservers (e.g., SwissDock)
Molecular properties in drug discovery
- Analysis of the most important physicochemical molecular properties (e.g. ionization, lipophilicity, polarity, flexibility, solubility, etc) and calculation and measure of related descriptors (e.g. pKa, log P/D, PSA, etc.)
- The druglikeness concept. Lipophilicity-based metrics. Lipinski rule (Ro5).Multi-Parameter Optimisation (MPO) process.
ADME-Tox predictors
- Barriers to drug exposure
- In-vivo Pharmacokinetics
- Metabolism
- In-vitro ADMET
- Experimental techniques used in ADMET. The case of PROTACs
QSAR/QSPR
- Basic concepts and applications.
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Course delivery
The course will be delivered in presence. All the material will be delivered via Moodle. No synchronous/recorded lesson is available
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Learning assessment methods
Students are expected to prepare 4 reports and 4 infographics during the teaching period. All the reports and the infographics will be evaluated and their average value represents one half of the final course grade. An oral exam will provide the second half of the final course grade.
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Support activities
The report preparation will start during the lessons.
Suggested readings and bibliography
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No specific reference is provided. Recent literature papers will be suggested during the lessons and listed on Moodle to familiarize with the topics. Most of the common drug discovery books can be used to contextualize the arguments.
- Enroll
- Open
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