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ADVANCED DRUG DISCOVERY
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ADVANCED DRUG DISCOVERY
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Academic year 2021/2022
- Course ID
- BIO0161 Pds 307-DDD
- Teaching staff
- Prof.ssa Giulia Caron
Prof. Giuseppe Ermondi
Prof.ssa Sonja Visentin - Degree course
- [0101M21] Molecular Biotechnology
- Year
- 2nd year
- Teaching period
- To be defined
- Type
- Related or integrative
- Credits/Recognition
- 5
- Course disciplinary sector (SSD)
- CHIM/08 - chimica farmaceutica
- Delivery
- Blended
- Language
- English
- Attendance
- Obligatory
- Type of examination
- Oral
- Prerequisites
- Basic knowledge of chemistry and biochemistry. Basic knowledge of computer sciences.
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Sommario del corso
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Course objectives
The main goal of the course is to provide to the students the basic knowledge about adanced Drug Discovery techniques.
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Results of learning outcomes
At the end of the course students will be able to evaluate how to include basic drug discovery techniques in their research work
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Course delivery
The course will be delivered in remote presence according to the guidelines provided by the Department and University.
Students can attend to the lessons using Moodle. The registration is free and mandatory to access to the course material and link to remote lessons.
The 3/4 hour lessons will be held synchronously and will include an introduction to the topic of the day followed by class practice.
A student is required to attain at least 75% of the attendance for lectures, tutorials and practical sessions of the course (in classroom or in remote presence).
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Learning assessment methods
Students are encouraged to participate, ask questions and maintain a direct relationship with the professor during the lesson.
In each lesson, they are involved in practical exercitation based on online or free tools that they can perform on their notebooks.
Finally, for each topic, students must submit a report that will be evaluated.
The final examination is oral and includes a discussion of the reports.
Exams will be conducted 'face-to-face' or online according to university guidelines
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Support activities
Classroom practice
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Program
Getting structures
Tools to obtain a reliable and informative 3D structure
Structural databases
Main sources of experimental 3D structures (e.g. PDB, CSD)
Molecular properties in drug discovery
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.).
In silico molecular descriptors and drug-likeness
Multi-Parameter Optimisation (MPO) process. Druglikeness concept. Lipophilicity-based metrics. Lipinski rule (Ro5).
Pharmacodynamics 1: Drug response curve
Protein-ligand (receptor-neurotransmitter, receptor-drug) interaction. Measure drug-target interactions. Monitoring dose-effect. Dose-response curve, and curve-fitting procedure. Ligand efficiency metric.
Pharmacodynamics 2: Molecular docking
Molecular docking concepts and calculation.
ADME-Tox predictors
Barriers to drug exposure. In-vivo Pharmacokinetics. Metabolism. In-vitro ADMET. Experimental techniques used in ADMET.
QSAR/QSPR
Basic concepts. Molecular descriptors. Most important algorithms.
Suggested readings and bibliography
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Readings and bibliography will be suggested during the lessons
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Note
Le modalità di svolgimento dell'attività didattica potranno subire variazioni in base alle limitazioni imposte dalla crisi sanitaria in corso. In ogni caso è assicurata la modalità a distanza per tutto l'anno accademico
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