The course aims to introduce and use some databases in chemistry, with particular reference to organic chemistry and to provide students with the basic concepts and the general principles of chemoinformatics.
Expected learning outcomes
Students will acquired the ability to: · manage and extract chemical information contained in different databases · read and modify the most common electronic formats of chemical structures (SMILES, SDF, MOL, PDB) · recognize and calculate the most common molecular descriptors · build and evaluate and multivariate models · set up and analyze a conformational analysis calculation · prepare and set up a virtual screening workflow
Lesson period: Second semester
(In case of multiple editions, please check the period, as it may vary)
· Linear, two-dimensional and three-dimensional molecular representation: chemical similarity and conformational analysis aspects · Molecular descriptors and pharmacophores: definition and description of the main multivariate analysis methods used to build structure-activity models · Virtual screening methods: docking, scoring functions and analysis of the results · Hints to machine learning methods applied to chemoinformatics and drug discovery · use of chemical databases (SciFinder, CSD, PDB, Reaxys, PubChem, ChEMBL)
Prerequisites for admission
Fundamental courses of chemistry of a Bachelor of Science in Chemistry or related fields.
Traditional lessons. Traditional teaching activities (36 h) will be integrated with computer lessons on the use of chemical databases (12 h) and seminars on specific topics of the course.
A. Leach and V. Gillet, 'An Introduction to chemoinformatics', Revised Edition Springer 2007 A. Varnek, Tutorials in Chemoinformatics, John Wiley & Sons Ltd 2017
Assessment methods and Criteria
The exam will consist of a written test of 4-5 open questions which aims to verify the preparation of the student on the course contents. A written reports describing the activities performed in the computer laboratory will be also evaluated.