The course prepares students to apply computational approaches to study biological systems, with the final goal of rationally designing new drugs with activity in vitro and in vivo. In general, the course aims to develop the ability of scientists to address problems at the intersection of biology and medicine that constitute the foundation for understanding complex biological processes. This knowledge is then exploited for the design of novel drugs. Attention will be given to new methods of machine learning and artificial intelligence in the context of drug discovery.
Course Prerequisites
The students interested in this course should have a basic knowledge of organic chemistry, biochemistry (in particular molecular structures for the main classes of biomolecules), and high-school level mathematics.
Teaching Methods
Lectures will be given using Power Point presentations
Assessment Methods
Oral examination. The exam will focus on the various subjects studied during the course and will aim to assess the critical ability of students to evaluate/develop computational design processes in biochemical problems.
Texts
Lecture notes, materials and handouts provided by the teacher.
Contents
The main subjects are:
- Introduction to computational studies of biochemical systems. - Molecular Dynamics: studies of the correlations between structures, motions and activities on different scales. - Ligand-protein interactions: methods to predict the interaction free energy. - The design of biologically active small molecules: chemical tools and new drugs; the role of machine learning.
