Rational design and structural characterization of bioactive molecules
A.A. 2023/2024
Obiettivi formativi
This course is intended to provide the student with a theoretical, analytical and applied background in the fields of rational drug design and of target-oriented chemical optimization of bioactive compounds. In particular, modern chemical-physics methods for the investigation of the molecular target-ligand interaction will be discussed in the context of the expanded role of chemistry through the process of the design and optimization of pharmacologically active molecules; and modern, chemistry-directed approaches to assist the identification of novel molecular targets (chemical tools and probes, chemical genetics) will be described.
The course is ideally linked to those dealing with structural biology, bioinformatics, nanotechnologies, protein engineering and molecular enzymology.
The course is ideally linked to those dealing with structural biology, bioinformatics, nanotechnologies, protein engineering and molecular enzymology.
Risultati apprendimento attesi
At the end of the class, the students will be able to:
1. illustrate the basic concepts of equilibrium thermodynamics including internal energy, en-thalpy, entropy, and Gibbs free energy;
2. create suitable mathematical models for an accurate description of the covalent and non-covalent interactions involved in biological phenomena such as protein folding, allostery, and substrate binding;
3. describe the main characteristics of Force Fields employed in computer simulations of bio-molecular systems;
4. illustrate the workflow and main applications of popular computational chemistry tech-niques, i.e. molecular dynamics and Monte Carlo sampling;
5. link the computational study, performed at the microscopic molecular level, of biological phenomena like protein folding to their macroscopic thermodynamical investigation;
6. have understood how computational methods (structure-based, ligand-based and fragment-based drug discovery) support the fast, effective design and optimization of biologically active, small or-ganic molecules; and
7. have learnt about chemical probes for mechanism of action studies in vitro and in vivo (pho-toaffinity ligands, biotin conjugates, etc.); and about their use in target validation studies (affinity chromatography, photoactivation, etc.).
1. illustrate the basic concepts of equilibrium thermodynamics including internal energy, en-thalpy, entropy, and Gibbs free energy;
2. create suitable mathematical models for an accurate description of the covalent and non-covalent interactions involved in biological phenomena such as protein folding, allostery, and substrate binding;
3. describe the main characteristics of Force Fields employed in computer simulations of bio-molecular systems;
4. illustrate the workflow and main applications of popular computational chemistry tech-niques, i.e. molecular dynamics and Monte Carlo sampling;
5. link the computational study, performed at the microscopic molecular level, of biological phenomena like protein folding to their macroscopic thermodynamical investigation;
6. have understood how computational methods (structure-based, ligand-based and fragment-based drug discovery) support the fast, effective design and optimization of biologically active, small or-ganic molecules; and
7. have learnt about chemical probes for mechanism of action studies in vitro and in vivo (pho-toaffinity ligands, biotin conjugates, etc.); and about their use in target validation studies (affinity chromatography, photoactivation, etc.).
Periodo: Primo semestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento può essere seguito come corso singolo.
Programma e organizzazione didattica
Edizione unica
Responsabile
Periodo
Primo semestre
Programma
The first module of the course (3 CFUs) is focused on Rational design of biologically active molecules (Pierfausto Seneci)
- Refresh of proteins' structure and properties.
- Ligand-protein interactions: enzymes - competitive and non-competitive, allosteric inhibitors; receptors - agonists and antagonists.
- Virtual and tangible drug design: "in silico" protein / target and small molecule models
- Energy minimization, preferred conformations, molecular descriptors.
- Structure-based drug discovery (SBDD): reliable protein models (X-ray, NMR), docking, putative binders' identification and prioritization.
- Ligand-based drug discovery (LBDD): reliable sets of known ligands, pharmacophore generation and validation, similarity searching.
- Fragment-based drug discovery (FBDD): features and advantages of small fragments in drug discovery; X-ray-driven, fast fragment decoration / structural optimization.
- Examples of rational drug design (HSP90 inhibitors - SBDD and LBDD; kinase inhibitors - FBDD).
- Chemical genetics: phenotype screening, chemistry-assisted identification and validation of novel molecular targets in drug discovery.
- Target identification and validation: chemical probes for in vitro experiments (affinity chromatography - biotinylated compounds, SILAC, SPROX, DARTS, etc.).
- Photoaffinity multi-functional probes (azides, diazirines) as covalent markers for proteomics-driven target identification.
- Examples of chemical genetics (zebrafish development screening, uretupamine discovery).
- Examples of chemistry-driven target identification and validation successful studies (bromodomain inhibitors as anti-inflammatory agents, kinesin Eg5 inhibition against cancers).
The second module of the course (3 CFUs) is focused on Chemical Physics Methods and Theories for Investigating Molecular Structure (Chiara Aieta)
- Refresh of basic thermodynamic concepts;
- Theory of non-covalent interactions: short-range repulsions, van der Waals and electrostatic interactions, hydrogen bonds, stacking and hydrophobic interactions.
- Molecular mechanics: Force field, modelling of bonding and non-bonding interactions, structure optimization.
- Molecular dynamics. Understanding the rationale beyond molecular dynamics. Ingredients of molecular dynamics (boundary conditions, integrators, structural model, Force Field). Set up of reliable molecular dynamics simulations: problems of solvation, cut-offs, electrostatic interactions and the use of computational barostats and thermostats. Link between molecular dynamics and thermodynamics. Ergodicity.
- A different approach: The Monte Carlo method;
- A short introduction to the construction of ab initio Potential Energy Surfaces;
- Applications. Non-equilibrium (transient) phenomena and related molecular dynamics descriptors. Application of classical simulation methods: structure fluctuations, structure prediction, allostery and molecular docking.
- Refresh of proteins' structure and properties.
- Ligand-protein interactions: enzymes - competitive and non-competitive, allosteric inhibitors; receptors - agonists and antagonists.
- Virtual and tangible drug design: "in silico" protein / target and small molecule models
- Energy minimization, preferred conformations, molecular descriptors.
- Structure-based drug discovery (SBDD): reliable protein models (X-ray, NMR), docking, putative binders' identification and prioritization.
- Ligand-based drug discovery (LBDD): reliable sets of known ligands, pharmacophore generation and validation, similarity searching.
- Fragment-based drug discovery (FBDD): features and advantages of small fragments in drug discovery; X-ray-driven, fast fragment decoration / structural optimization.
- Examples of rational drug design (HSP90 inhibitors - SBDD and LBDD; kinase inhibitors - FBDD).
- Chemical genetics: phenotype screening, chemistry-assisted identification and validation of novel molecular targets in drug discovery.
- Target identification and validation: chemical probes for in vitro experiments (affinity chromatography - biotinylated compounds, SILAC, SPROX, DARTS, etc.).
- Photoaffinity multi-functional probes (azides, diazirines) as covalent markers for proteomics-driven target identification.
- Examples of chemical genetics (zebrafish development screening, uretupamine discovery).
- Examples of chemistry-driven target identification and validation successful studies (bromodomain inhibitors as anti-inflammatory agents, kinesin Eg5 inhibition against cancers).
The second module of the course (3 CFUs) is focused on Chemical Physics Methods and Theories for Investigating Molecular Structure (Chiara Aieta)
- Refresh of basic thermodynamic concepts;
- Theory of non-covalent interactions: short-range repulsions, van der Waals and electrostatic interactions, hydrogen bonds, stacking and hydrophobic interactions.
- Molecular mechanics: Force field, modelling of bonding and non-bonding interactions, structure optimization.
- Molecular dynamics. Understanding the rationale beyond molecular dynamics. Ingredients of molecular dynamics (boundary conditions, integrators, structural model, Force Field). Set up of reliable molecular dynamics simulations: problems of solvation, cut-offs, electrostatic interactions and the use of computational barostats and thermostats. Link between molecular dynamics and thermodynamics. Ergodicity.
- A different approach: The Monte Carlo method;
- A short introduction to the construction of ab initio Potential Energy Surfaces;
- Applications. Non-equilibrium (transient) phenomena and related molecular dynamics descriptors. Application of classical simulation methods: structure fluctuations, structure prediction, allostery and molecular docking.
Prerequisiti
Knowledge of the topics covered by the basic chemistry and physics classes included in the bachelor curriculum before attending the course is recommended. No further prerequisites are required other than those specified in the learning manifesto.
Metodi didattici
Teaching Mode: Classroom lectures supported by projected material and provided lecture material - pdf files and, when needed, mp4 recordings on the Ariel Website. The attendance is highly recommended.
Materiale di riferimento
· A. R. Leach. Molecular Modelling. Principles and Applications. Addison Wesley Longman, Essex, England, 1996
· P. Seneci. Chemical Sciences in Early Drug Discovery: Medicinal Chemistry 2.0. Elsevier, Amsterdam, 2018.
· P. Seneci. Chemical Sciences in Early Drug Discovery: Medicinal Chemistry 2.0. Elsevier, Amsterdam, 2018.
Modalità di verifica dell’apprendimento e criteri di valutazione
The final examination consists in a written test (2 hrs long, 1 hour each for the two modules). Students will be prompted to answer to both open questions and questions with a multiple answer choice, in both cases on any topic treated during both the modules. The written exam allows the teachers to evaluate not only the technical competence of the student, but also his/her ability to organize a short dissertation on scientific topics. The final grade will be the joint evaluation of each candidate by the two instructors.
CHIM/02 - CHIMICA FISICA
CHIM/06 - CHIMICA ORGANICA
CHIM/06 - CHIMICA ORGANICA
Lectures: 48 ore
Docenti:
Conte Riccardo, Seneci Pierfausto
Siti didattici
Docente/i
Ricevimento:
Appuntamento via email
Dipartimento di Chimica, primo piano, corpo A, stanza 131