87609 - Advanced Methodologies in Medicinal Chemistry (8 CFU)

Academic Year 2023/2024

  • Docente: Marina Naldi
  • Credits:: 8
  • SSD: CHIM/08
  • Language: Italian
  • Moduli: Marina Naldi (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 Chemistry and Pharmaceutical Technologies (cod. 8412)

Learning outcomes

At the end of the course, which also includes laboratory exercises, the student knows some analytical and bio-analytical methodologies useful for characterizing the target protein and the drug-protein complex and knows the main methods of molecular modeling and simulation making use of that information to design new drugs. In particular, the student: i) will be able to determine the thermodynamic constants and the kinetic constants that regulate the formation of ligand-protein complexes; ii) will be able to plan investigations on molecular recognition mechanisms aimed at the design and development of new drugs; iii) will know how to use some open source molecular modeling software available on the Internet; iv) will be able to build computer models of small organic molecules; v) will be able to interpret a 3D model of a ligand-protein complex and use it to suggest simple molecular modifications of the ligand.

Course contents

  • Module 1:

Analytical methodologies in pharmaceutical chemistry

  1. Bioreactors. Development of a bioreactor: support choices, approaches for the immobilization of the target enzyme, optimization of the conditions of use of the bioreactor, development of functional assays, validation of the bioreactor. The use of bioreactors in the drug discovery process: screening, identification and optimization of active compounds.

  2. Biochromatography. Immobilization of proteins / receptors on chromatographic support. Development of column with the target immobilized: choice of support, approaches for immobilization, validation, optimization of use conditions. Applications of biochromatography in the drug discovery process.

  3. Techniques coupled to detection by mass spectrometry. Fishing of ligands, characterization of ligand-target covalent bonds; characterization of reversible interactions and modulation of protein/protein interactions, screening of enzymatic inhibitors.

  4. Surface plasmon resonance optical biosensors. Instrumentation; molecular recognition processes; isolation of new target proteins; screening of new compounds for their binding affinity to the target protein; study of the kinetics of the molecular recognition process.

  5. Spectroscopy with polarized light. Instrumentation; determination of the secondary structure of peptides and proteins; molecular recognition mechanisms; functional conformational transitions; determination of drug/protein binding parameters; stereochemical characterization of the drug bound to the target protein.

Laboratory of analytical methodologies in pharmaceutical chemistry

Exercises in the computer room with dedicated software.

  1. Use of mass spectrometry for the identification and characterization of proteins, for the characterization of structural changes in proteins, for the monitoring of enzymatic activity.
  1. Use of the optical biosensor and circular dichroism to study molecular recognition phenomena.
  • Module 2: Computational methodologies in pharmaceutical chemistry
  1. Introduction to computational methods in pharmaceutical chemistry. The drug discovery process. Identification, validation, and characterization of the target. Hit identification of hits. Hit-to-lead phase. Lead optimization.

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

  3. Molecular descriptors and chemical similarity. Examples of molecular descriptors. Topological indices. Distance and similarity measurements. Outline of cluster analysis. Outline of dimensionality reduction. Notion of chemical space and its representation.

  4. Structure-activity relationships. Derivation and validation of QSAR models. Examples of simple QSAR models. Outline of classification methods. Concept of "activity landscape".

  5. Molecular modeling. Introduction to force fields. The concept of potential energy surface. Minimization algorithms. Conformational analysis. Outline of Molecular Dynamics.

  6. Pharmacophore and 3D-QSAR models. Application of conformational analysis. Construction of pharmacophore models. Construction of 3D-QSAR models.

  7. Molecular docking. Introduction to molecular docking. The molecular docking protocol: research and scoring phase. Validation of the molecular docking protocol. Molecular recognition models. Including receptor flexibility in molecular docking.

  8. Virtual Screening. Introduction to Virtual Screening. Choice of target structure in Structure-Based Virtual Screening. Validation of a Virtual Screening protocol. Enrichment metrics.
  • Module 3: Laboratori of computational methodologies in pharmaceutical chemistry

Exercises in the computer room with dedicated software.

  1. Databases of pharmaceutical interest (Uniprot and Protein Data Bank), choice of the most suitable structure.

  2. Preparation of the selected structure (adding hydrogens, prediction of ionization/tautomerization states, minimization, etc).

  3. Preparation of a database of molecules (conversion from 2D to 3D, generation of protonation/tautomerization states, treatment of stereoisomers, minimization and usage of filters).

  4. Protein-ligand interactions and structure/activity relationships.

  5. Molecular docking. Reproducing the binding mode of the drug Imatinib with the Abl protein. The case of the T315I mutation and how to tackle this problem.

  6. Simulation of a Virtual Screening campaign through: similarity search, use of a pharmacophore model, and molecular docking.

Readings/Bibliography

Useful texts for consulatation only:

  • V. Cavrini, V. Andrisano. Principi Analisi farmaceutica. Società editrice Esculapio ed. 2013.
  • A. R. Leach, V. J. Gillet. An Introduction to Chemoinformatics. Springer. 2007.

Teaching methods

Frontal lectures and laboratories in the computer room.

In consideration of the type of activity and the teaching methods adopted, the attendance of this training activity requires the prior attendance of all students to the training Modules 1 and 2 on safety in the study places [https://elearning-sicurezza.unibo.it/], in e-learning mode.

Assessment methods

The learning assessment test consists of oral interviews on the topics covered during the course.

Teaching tools

Slides, scientific publications and other teaching material made available through the Virtual Learning Environment [https://virtuale.unibo.it/] platform.

Office hours

See the website of Marina Naldi

See the website of Matteo Masetti

See the website of Federico Falchi