B2845 - Medicinal Chemistry Methodologies for the Discovery of New Drugs

Academic Year 2023/2024

  • Docente: Elisa Uliassi
  • Credits: 6
  • SSD: CHIM/08
  • Language: Italian
  • Moduli: Elisa Uliassi (Modulo 1) Matteo Masetti (Modulo 2) Federico Falchi (Modulo 3)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2) Traditional lectures (Modulo 3)
  • Campus: Bologna
  • Corso: Single cycle degree programme (LMCU) in Pharmaceutical Chemistry and Technology (cod. 5986)

Learning outcomes

The course offers the opportunity to develop specific knowledge and skills to be used during the initial stages of research and development of new drugs, including innovative ones. The course, organized in two modules, aims to train industrial pharmacists with a solid and critical knowledge of the medicinal chemistry approaches underlying the rational design of new drugs and emerging modalities, even beyond traditional small molecules. At the end of the course the student will be able to: (i) evaluate the opportunities (in term of pharmacokinetics and pharmacodynamics) offered by the different therapeutic modalities to modulate certain targets and provide the most effective treatment for a given disease, (ii) employ the main current methodologies of chemoinformatics and molecular modeling for the identification and optimization of bioactive molecules.

Course contents


1. Introduction to the drug discovery process. The drug discovery process. Target identification, validation, and characterization. Hit identification. Hit-to-lead stage. Lead optimization.

2. Undruggable targets and new chemical modalities. Concept of druggable and undruggable targets. Introduction to the new chemical modalities.

3. The concept of polypharmacology and network pharmacology in medicinal chemistry. Strategies for the development of multi-target molecules and combinations.

4. Fragment-based drug discovery. Introduction to Fragment-based drug discovery and fragment identification techniques. Fragment-to-lead design and optimization strategies (e.g., Balversa®).

5. RNA/oligonucleotide-based drugs. Introduction to oligonucleotide-based drugs: antisense oligonucleotides (ASOs – e.g., Spinraza®), aptamers (e.g., Macugen), RNA-based drugs (mRNA, e.g., Comirnaty®, RNAi – e.g., Oxlumo®). Modification sites of an oligonucleotide. Conjugation strategies (e.g., Amvuttra®).

6. Macrocycle/cyclopeptide-based drugs. Introduction to macrocycles/cyclopeptides-based drugs (e.g., Vonjo®, Olysio®, Orbactiv®, Lupkynis®). Strategies of macrocyclization and development of cyclic (constrained) peptides.

7. Drug conjugates. Introduction to drug conjugates: antibody-drug conjugates (e.g., Elahere™), small molecule drug conjugates (e.g., Lutathera®), fluorescent drug conjugates (e.g., Cytalux®). Design strategies and (bio)conjugation reactions.

8. Photoactivatable drugs. Introduction to photoactivable drugs: photosensitizers for photodynamic therapy (e.g., Photofrin®, 5ALA), "photoswitchable" drugs (e.g., KIO-301), "photocleavable" drugs. Development of photoactivatable drugs.

9. Degraders in the clinic and in clinical trials. Introduction to degraders: molecular glues (e.g., Thalomid®, Revlimid®), PROTACs (e.g., ARV-110, ARV-471), and other new degraders (RIBOTACs, DUBTACs and LYTACs). Basic concepts on endogenous cellular degradation systems. Design, synthesis, and optimization strategies.


1. Representation of molecular structures. Introduction to molecular graphs. Connectivity tables. Linear notations. Fingerprints.

2. Molecular descriptors and chemical similarity. Examples of molecular descriptors. Topological indices. Distance and similarity measures. Introduction to cluster analysis. Overview of dimensionality reduction. Concept of chemical space and its representation.

3. Structure-activity relationships. Derivation and validation of QSAR models. Examples of simple QSAR models. Introduction to classification methods. Concept of "activity landscape".

4. Virtual Screening. Introduction to Virtual Screening. Selection of target structure in Structure-Based Virtual Screening. Validation of a Virtual Screening protocol. Enrichment metrics.


In-class computer exercises using dedicated software.

1. Introduction to molecular modeling. Force fields. Minimization algorithms. Conformational analysis. Overview of Molecular Dynamics.

2. Pharmaceutical databases of interest (Uniprot and Protein Data Bank), selection of the most suitable target structure.

3. Preparation of the target (hydrogen addition, prediction of ionization states/tautomeric forms, minimization, etc.).

4. Preparation of a molecule database (conversion from 2D to 3D, generation of protonation/tautomerization states, handling of stereoisomers, minimization, and application of filters if necessary).

5. Recognition of molecular interactions between target and ligand and structure-activity relationships.

6. Introduction to molecular docking: search and scoring phases. Validation of the molecular docking protocol. Overview of flexible docking. Reproduction of the binding mode of the drug Imatinib in the Abl protein. Study of the case of the T315I mutation and how this problem was solved.

7. Introduction to pharmacophore models. Application of conformational analysis. Construction of pharmacophore models.

8. Virtual screening simulation through similarity searching, utilization of a pharmacophore model, and molecular docking.

Teaching methods

Lectures and laboratory activities.

Assessment methods

The exam will consist in an oral discussion aimed at assessing students' knowledge of the course objectives.

Teaching tools

The teaching material (slides) presented during classes is available on the Virtuale platform.

Office hours

See the website of Elisa Uliassi

See the website of Matteo Masetti

See the website of Federico Falchi


Good health and well-being Quality education

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.