Learning objectives
The course has a practical formulation. The practical exercises in the lab will be performed personally by the students, to provide them with advanced techniques and methodologies in the field of computational biophysics, in particular for the determination, prediction and analysis of the structure and the dynamics of protein systems.
Knowledge and understanding
The students should have learnt and understood the main features of proteic structures and the fundamental physical and biological principles which underlie the methodologies and techniques explained. They should also be able to consult and understand scientific literature.
Applying knowledge and understanding
The students should be able to analyze a protein structure with the learnt techniques and methodologies, and to collect all the data that could be useful to understand the fundamental properties of the system under study, relating them to its biological function.
Making judgements
The students should be able to choose the better approach for the study of a specific problem regarding a proteic system, and to verify its efficacy and usefulness, searching solutions by themselves and developing their knowledge in depth.
Communication skills
The students should be able to communicate the results of their analyses and studies in a clear and incisive manner. Such ability will be exerted particularly during the course, in which the drawing up of a written report of each practice performed in the lab will be required.
Learning skills
The students should be able to go into the learned techniques thoroughly and to use their knowledge to aquire the most recent research results, and to extend and improve them.
Prerequisites
None.
Course unit content
Protein structure. Covalent and not-covalent interactions that are present in a biomolecular structure. Theoretical and experimental methods for determining secondary and tertiary protein structure. Topological representation. Supersecondary structures. Ramachandran plot. Fold classification.
Search engines in biological databases.
Protein and nucleic acid sequence analysis: similarity and sequence alignment tools (pairwise and multiple). Patterns and conserved motifs recognition. Protein physico-chemical profiles. Secondary structure prediction from the protein sequence.
Analysis of structural and functional features of proteins and protein complexes by means of molecular graphics softwares and web servers.
Computational techniques for the study of protein structure and dynamics:
Comparative modeling and fold recognition methods.
Molecular mechanics and force fields; energy minimization; molecular dynamics simulations.
Molecular recognition. Molecular interaction simulations: docking and drug design.
Practices in the lab during the course.
Full programme
Protein structure. Covalent and not-covalent interactions that are present in a biomolecular structure. Theoretical and experimental methods for determining secondary and tertiary protein structure. Topological representation. Supersecondary structures. Ramachandran plot. Fold classification.
Search engines in biological databases.
Protein and nucleic acid sequence analysis: similarity and sequence alignment tools (pairwise and multiple). Patterns and conserved motifs recognition. Protein physico-chemical profiles. Secondary structure prediction from the protein sequence.
Analysis of structural and functional features of proteins and protein complexes by means of molecular graphics softwares and web servers.
Computational techniques for the study of protein structure and dynamics:
Comparative modeling and fold recognition methods.
Molecular mechanics and force fields; energy minimization; molecular dynamics simulations.
Molecular recognition. Molecular interaction simulations: docking and drug design.
Practices in the lab during the course.
Bibliography
A.M. Lesk, "Introduction to protein science", Oxford Univeristy Press.
A.M. Lesk, "Introduzione alla Bioinformatica", McGraw-Hill Ed.
G. Valle, M. Helmer Citterich, M. Attimonelli, G. Pesole, "Introduzione alla Bioinformatica", Zanichelli Ed.
D.E. Krane, M.L. Raymer, "Fondamenti di Bioinformatica", Pearson Education Ed.
Notes on the lessons and review articles will be given.
Teaching methods
Oral lessons and practices in the laboratory.
Assessment methods and criteria
Discussions on the reports of the practices and oral examination on the fundamental concepts of the studied techniques.
Other information
A report on each practical exercise performed in the lab will be required.
