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General information |
Course unit name: Design and Evaluation of Bioactive Molecules
Course unit code: 361584
Academic year: 2020-2021
Coordinator: Eva Estebanez Perpi�a
Department: Department of Biochemistry and Molecular Biomedicine
Credits: 6
Single program: S
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Estimated learning time |
Total number of hours 150 |
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Face-to-face and/or online activities |
42 |
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- Lecture |
Face-to-face |
24 |
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- Group tutorial |
Online |
2 |
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- Problem-solving class |
Online |
8 |
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- IT-based class |
Online |
4 |
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- Student presentation and discussion |
Online |
4 |
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Supervised project |
50 |
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Independent learning |
58 |
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Learning objectives |
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Referring to knowledge — Learn basic and advanced guidelines in academia and the pharmaceutical sector on the selection of drug targets, the design of new drugs and the procedures for real-life drug discovery settings.
Referring to abilities, skills — Become competitive doctoral students and postdoctoral fellows as well as practising scientists in academia and the pharmaceutical sector.
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Teaching blocks |
1. General introduction
1.1. Drug discovery, medicinal chemistry, translational medicine and patient-tailored medicine: relevance and applications in biomedicine
1.2. The evolution of drug discovery; Approaches to drug discovery; Real-world drug discovery; Potential and bottlenecks
2. Can drugs be designed?
2.1. What is rational drug discovery and what is not?
3. General introduction to target identification
3.1. Target discovery process; What is druggable? Is it the same for academic groups and pharmaceutical companies? Implications
4. Biomedical and economic implications of drug discovery
4.1. Are medical needs aligned with the health business? What are the main macromolecular pharmaceutical leads? Why?
5. Structural biology and bioinformatics in drug design
5.1. Opportunities and challenges for target identification and lead discovery: a structural biology view or a chemical view of target druggability
6. From virtuality to reality
6.1. Drugs: from discovery to approval; Hit-to-lead; Target identification, lead identification, lead optimisation steps and techniques
7. Chemical space and development of novel drugs for biomedicine
7.1. Are all chemical compounds potential drugs? Drug-like properties; What are pharmacophores? What compounds are bioavailable? In silico prediction of drug properties; Early-phase drug discovery: cheminformatics and computational techniques in identifying lead series
8. Brief review of the principles of protein and nucleic acid structure
8.1. Secondary, tertiary and quaternary structures relevant to the following topics; What are protein-protein and protein-DNA interactions?
9. Overview of biochemical and biophysical techniques for studying the structure and function of macromolecules
9.1. Relevance in drug discovery; Experimental vs. computational techniques; Why the fusion of the two techniques would yield the best results in drug discovery; Uses and limitations of each technique
10. Introduction to families of macromolecules most commonly targeted by major pharmaceutical companies and key targeted diseases
10.1. Description of GPCRs, nuclear receptors and the kinase family of proteins; Description of major antibiotics and their targets; Description of anti-cancer drugs: applications and drawbacks; Why do we still need novel drugs for major diseases? Side-effects and need for drug-discovery and how to bypass bottlenecks; Strategies for efficient drug discovery
11. Introduction to macromolecular leads not yet pursued as mainstream pharmaceutical targets
11.1. Protein-protein interactions as lead targets; Conformational trapping and targeting macromolecular complexes; Allosteric modulators; Minority diseases and their targets; Orphan drugs
12. Virtual screening in drug discovery
12.1. Overall description of scope and limitations; Current strategies for virtual screening; Development of reliable pharmacophores; Docking, scoring and visual inspection; Virtual screening as a routine tool? Protein plasticity: how to hit a mobile target; Rigid vs. flexible docking; Which computational approaches work best? How do they compare?
13. Compound and hit suitability for virtual screening
13.1. Compound selection and available libraries (open-access vs. proprietary); The role of leads in drug discovery; Compound processing prior to screening; Data mining approaches; Scoring functions and evaluation of binding between molecules and macromolecular targets
14. Fragment-based drug discovery: smaller is better?
14.1. Fragment-based high-throughput docking; Generation of ligand conformations; Binding site search and definition; Role of conserved water molecules
15. Structure-based drug discovery
15.1. Use of X-ray crystallography and NMR; Detection of novel (allosteric) sites; Targeting protein-protein interactions; Use of synchrotrons in drug discovery; High-throughput crystallography for lead discovery in drug design; Limitations and lessons in the use of X-ray structural information in drug design
16. From laptop to benchtop to bedside
16.1. Stages of clinical development of novel drugs; FDA and other regulatory agencies; Security checkpoints; What are clinical trials?
17. Case studies and drug discovery: biomedical applications
17.1.
Evolution of pharmaceutical ligands; Implications for CNS pathologies, metabolic syndrome, auto-immune disease, tumour development, etc.
Examples: GPCRs; Protein kinases; Proteases; Nuclear receptors; Epigenetic targets; Oncology, anti-tumoral drugs; Protein-protein interactions; Allosteric modulators
18. Unless the requirements enforced by health authorities demand a prioritisation or reduction of these contents
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Teaching methods and general organization |
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The methodology includes lectures, talks by guest speakers (leading figures in drug discovery fields in academia and the pharmaceutical sector), field trips to laboratories and pharmaceutical platforms.
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Official assessment of learning outcomes |
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— Regular training and oral presentations (individual and in groups) on topics assigned by the lecturer; preparation of talks on an area of drug discovery chosen by the student (worth 50% of the final grade).�
Examination-based assessment — Regular training and oral presentations (individual and in groups) on topics assigned by the lecturer; preparation of talks on an area of drug discovery chosen by the student (worth 50% of the final grade).�
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Reading and study resources |
Check availability in Cercabib
Article
EGNER, U. (et al.). The target discovery process. Dins: Chembiochem [en línia]. 2005 Mar;6(3):468-79 