The course prepares students to develop and apply computational and simulative approaches to study chemical and biological systems, with the final goal of rationally designing new molecules with potential interesting activities as chemical tools, new drugs, materials. In general, the course aims to develop the ability of scientists to address problems at the intersection of chemistry and biology by providing the chemical concepts that constitute the foundation for understanding complex biological processes at an atomic level. This knowledge is then exploited for the design of novel active molecules. The main questions in this context entail the study of the structures and folding processes of proteins, the visualizations of biomolecules and complex systems, the analysis and prediction of interactions between biological molecules and ligands (drugs, chemical tools) or between proteins and other biological macromolecules, the study and prediction of the reactivity and functions of enzymes. Specific focus will be given to the use of new methods of machine learning and artificial intelligence in the context of biomolecular chemistry.
Course Prerequisites
The students interested in this course should have a good knowledge of organic chemistry (in particular with regards to the structure and reactivity of the main functional groups), of physical chemistry (with particular focus on the basic principles of molecular statistical thermodynamics and kinetics) and a basic knowledge of the principal concepts of molecular structures for the main classes of biomolecules.
Teaching Methods
Lectures will be given using Power Point presentations. Further demonstrations on the board. The final lectures will entail interactive sessions with dedicated Colab notebooks.
Assessment Methods
Oral examination lasting at least 15 minutes, on at least two of the macroareas covered during the course. The exam will aim to assess the critical ability of students to evaluate/develop computational design processes in bioorganic chemistry.
Texts
Lecture notes, materials and handouts provided by the teacher. "Understanding Molecular Simulation", D. Frenkel, B. Smit "Computer Simulation of Liquids", M. P. Allen, D. J. Tildesley "Molecular Modelling - Principles and Applications", A. R. Leach "Introduction to Computational Chemistry", F. Jensen
Contents
The main subjects are:
• Introduction to computational studies of complex chemical and biochemical systems. • Introduction to statistical thermodynamics for the study of complex systems. • Protein structure and fundamental aspects of the processes of molecular recognition in chemical biology. • Molecular Dynamics: studies of the correlations between structures, motions and activities on different scales. • Enzymatic reactivity and modeling of reactions in complex biological contexts: theoretical and computational methods. • Study, analysis and predictions of protein-protein interactions. • Machine Learning methods in chemistry and biological chemistry. • The design of biologically active small molecules: chemical tools and new drugs.
