Dipartimento di Scienze della Vita e dell'Ambiente - Guida degli insegnamenti (Syllabus)
Basic knowledge of Bioinformatics, Chemistry and Physics.
During the course, there will be both theory frontal lessons (4 credits, 32 hours) and practical laboratory exercises (2 credits, 16 hours) which will be carried out individually or in small groups.
Support materials for the preparation of the final exams will be distributed such as the instruction for the practical exercises.
Knowledge At the end of the course, the students must have a full-scale introduction to computational chemistry and molecular modeling, including special topics on computational-aided drug design. More in details, they will have knowledge of the state-of-art techniques for energy and structure calculations ( both for small ligands, drugs and for macromolecules such as proteins and nucleic acids).
Ability to apply the knowledge:
The course goal is to develop a practical understanding of computational methods (strengths, limitations, applicability) and competence in applying these methods to molecular modeling in order to solve and explain biological relevant problems. The students should be also able to use some molecular modeling software to predict the 3D structure of proteins, and the ligand-receptor association.
FRONTAL LESSONS (4 credits, 32 hours):
Introduction to molecular modeling and simulation: problems, challenges, and approaches. Basic protein structure; Introduction to quantum and molecular mechanics. Biomolecular force fields; non bonded computations. Protein folding prediction; Theoretical prediction of Mechanism of Enzymatic reaction. Complete minimization methods; Homology and comparative modeling for 3D protein predicition, new challenges to GPCRs model construction. Conformational search applied to the study of bioactive conformation: Systematic search and Monte Carlo method and Molecular dynamics simulated annealing approach. Full atom molecular dynamics methods: approach and challenges to simulation in membrane bilayers. Molecular docking: methods and application to rational drug design. Computer-Aided Drug Design: peptidomimetics as novel antibiotics (casa studies); the solvation problem: current status and future developments. Dynamics of proteins and peptides in membrane: state of art and applications.
LABORATORY LESSONS (2 credits, 16 hours):
Practical exercises taken to the DISVA informatics laboratory about some arguments discussed in the frontal lessons (such as molecular docking and comparative protein modeling).
Methods for assessing learning outcomes:
The student will send the written lab reports by e-mail in PDF or doc version. The exam consists of an oral on topics covered in class or, alternatively, in a written assignment to multiple choice questions (n. 10, 1 pt /question) and of 5 open questions (4 pt /question). For the final grade the reports of the exercises will be evaluated, and they are awarded up to a maximum of two points. The exam is passed when the final grade is greater than or equal to 18.
Criteria for assessing learning outcomes:
In the written test, the student must demonstrate knowledge of principles and methods (theory and practice) of molecular modeling methodologies and to have acquired basic knowledge on methods for the prediction of protein structure and drug-receptor interactions. In the lab reports, the students must demonstrate that they have achieved the ability to apply the knowledge acquired during the training, to enforce a simple laboratory computational experiment and the ability to critically draw, independently and / or in a group, a report test.
Criteria for measuring learning outcomes:
The final mark is awarded out of thirty. The exam is passed when the grade is greater than or equal to 18. It is expected to be awarded the highest marks with honors (30 cum laude).
Criteria for conferring final mark:
The final grade is given by summing the evaluation of the oral or written test with the score assigned to the laboratory report, the latter up to a maximum of two points. “30 cum laude” is attributed when the score obtained from the previous sum exceeds the value 30 while the student has demonstrated full mastery of the subject.
Materials distributed during lessons (papers and diapositives)
A.R. Leach, Molecular Modeling - Principles and applications, Longman, second edition, 2001.
C.J.Cramer, Essentials of Computational Chemistry: Theories and Models, John Wiley & Sons, 2004.
T. Schlick, Molecular Modeling. An Interdisciplinary Guide, Second Edition, Springer Verlag, New York ,2010.
D. C. Rapaport, The Art of Molecular Dynamics Simulation, 2004, ISBN 0-521-82568-7
Jan H. Jensen, Molecular Modeling Basics, CRC Press, 2010