Quantitative chemical structure and activity relationship

A.A. 2019/2020
Insegnamento per
Crediti massimi
Ore totali
BIO/10 CHIM/08

Struttura insegnamento e programma

Edizione attiva
Moduli o unità didattiche
In Silico Methods in Toxicology
Lectures: 40 ore

Structural Bioinformatics
Laboratory individual activity: 16 ore
Lectures: 32 ore
Docente: Eberini Ivano

Prerequisiti e modalità di esame
The course requires the knowledge of base notions of mathematics, chemistry, biochemistry and molecular biology, which are needed for a proficient comprehension of the lessons. The examination consists of a written test including questions related to all the topics developed during the In silico methods in toxicology module, and of an oral discussion about two different topics of the Structural bioinformatics module.
In Silico Methods in Toxicology
The course is aimed at presenting approaches and tools useful to understand structure-function relationships, and at applying the knowledge both to biopolymers and to small molecules.
The module Structural bioinformatics is aimed at depicting a landscape of the most up-to-date bioinformatics techniques for the study of the biopolymers (nucleic acids and proteins) that are the main targets of xenobiotics. Students will be introduced to the theoretical bases of the most used computational approaches (4 CFU). Bioinformatics laboratories, totalling 16 hours (1 CFU), will be provided together with lectures, and will be carried out by the Molecular Operating Environment (MOE, http://www.chemcomp.com/MOE-Molecular_Operating_Environment.htm) fully integrated drug discovery software package, kindly offered by the Chemical Computing Group (http://www.chemcomp.com/index.htm).
The module In silico methods in toxicology is aimed at providing students with the fundamental concepts of molecular modelling and a collection of representative in silico approaches playing an increasingly important role in toxicology. Advantages deriving from a complementary use of experimental and in silico techniques will be deeply discussed during the course.

1. Complementarity between in vitro, in vivo and in silico approaches in toxicology
2. Potential energy
3. Proteins as complex systems
4. Competitive and non-competitive inhibition
5. Binding affinity and equilibrium dissociation constant (Kd)
6. Introduction to molecular modelling
7. Hints of computational quantum mechanics
8. Molecular mechanics
9. Molecular docking
10. Pharmacodynamics of xenobiotics and evaluation of their toxic effects
11. The target (and off-target) problem
12. Methods to predict target proteins for toxic agents on a proteome-wide scale (Virtual screening of large protein databases)
13. Structure-based versus ligand-based toxicity prediction approaches
14. Species cross-transferability analysis; reduction and optimization of animal testing
Materiale didattico e bibliografia
1. Arthur M. Lesk, Introduction to Bioinformatics, Fourth Edition. Oxford University Press 2014
2. Andrew R. Leach, Molecular Modelling: Principles and Applications. Pearson - Prentice Hall 2001
Structural Bioinformatics
Classroom activity (4 CFU)
1. Introduction to bioinformatics
2. Genome organization and evolution
3. Databases, archives and information retrieval
4. Substitution matrices, pairwise and multiple alignments, database search and phylogenetic trees
5. Protein structure and architecture
6. Protein structure prediction and validation: comparative modelling, threading and ab initio approaches
7. Case studies: chimeric comparative modelling of a receptor/target; distant homology modelling of an enzyme
8. Xenobiotic and novel drug risk assessment and prioritization
9. Case study: evaluation of endocrine active substances through an efficient in silico pipeline
10. Introduction to systems biology

Bioinformatics laboratories (1 CFU)
1. Building small molecules, biopolymers and introducing their PTMs
2. Protein comparative modelling
3. Molecular docking
4. Quantitative structure-activity relationship in practice
Materiale didattico e bibliografia
1. Arthur M. Lesk, Introduction to Bioinformatics, Fourth Edition. Oxford University Press 2014
2. Andrew R. Leach, Molecular Modelling: Principles and Applications. Pearson - Prentice Hall 2001
Primo semestre
Primo semestre
Modalità di valutazione
Giudizio di valutazione
voto verbalizzato in trentesimi
Siti didattici
Su appuntamento
Dipartimento di Scienze Farmacologiche e Biomolecolari, Via Giuseppe Balzaretti, 9 - 20133 Milano