Structural Bioinformatics
A.Y. 2025/2026
Learning objectives
The aim of the course is to provide students a thorough overview of the computational tools, and some of the underlying theory, to study the dynamics of biomolecules by computer simulation techniques. The course covers progresses in the development of atomistic, coarse-grained and quantum mechanical simulations and expand on methods for structure predictions based on statistical and evolutionary data and on hybrid methods that integrate structural biology techniques (Nuclear Magnetic Resonance, Small Angles X-Ray scattering, Cryo-electron microscopy) and computer simulations to increase the accuracy of computer simulations and experiments.
The course is ideally linked to those dealing with protein engineering and structural biology.
The course is ideally linked to those dealing with protein engineering and structural biology.
Expected learning outcomes
After following this course, students will know how computer simulations of biomolecules can be used to investigate biological problems at the molecular level.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
The course focuses on the use of computer simulations to study the structure and dynamics of biomolecules (proteins, nucleic acids, and membranes). Each topic is introduced theoretically and then learned hands-on using state-of-the-art software. Topics include: analysis, visualization and comparison of protein structures and trajectories; protein structure prediction and docking; molecular dynamics simulations (atomistic and coarse-grained); quantum chemistry simulations; free energy methods and protein design approaches. During the course, students will have the opportunity to learn how to use and manage data using Python notebooks.
Prerequisites for admission
None.
Teaching methods
Teaching method: 2/5 classroom lectures supported by projected material; 3/5 practical sessions in the computer lab.
Attendance: highly recommended.
Attendance: highly recommended.
Teaching Resources
Computer Simulations of Fluids (2nd Edition). D.J. Tildesley and M.P. Allen (Oxford)
Statistical Physics of Biomolecules, An Introduction. Zuckermann (CRC Press)
Copies of the slides projected in the classroom and other materials will be made available through the course website on the ARIEL platform of the University of Milan.
This material does not replace the lectures or a textbook. The material is made available only to enrolled students and should not be distributed to others.
Statistical Physics of Biomolecules, An Introduction. Zuckermann (CRC Press)
Copies of the slides projected in the classroom and other materials will be made available through the course website on the ARIEL platform of the University of Milan.
This material does not replace the lectures or a textbook. The material is made available only to enrolled students and should not be distributed to others.
Assessment methods and Criteria
Evaluation of the student's performance will be based on an oral examination as well as during lab activities. During the course students organized in group will guide the class thoruough practical activies. At the exam the student will present a scientific paper in which one or more of the techniques presented in the course have been used to address a biological problem. This exam allows students to test their ability to understand scientific literature based on the techniques learned hand's on during the course and to verify their practical understanding of the topic covered.
FIS/07 - APPLIED PHYSICS - University credits: 6
Practicals: 16 hours
Lectures: 40 hours
Lectures: 40 hours
Professor:
Camilloni Carlo
Professor(s)