Students can request an appointment with the lecturer by email: jvilla@uic.cat
Introduction
In the event that the health authorities announce a new period of confinement due to the evolution of
the health crisis caused by COVID-19, the teaching staff will promptly communicate how this may effect
the teaching methodologies and activities as well as the assessment.
Knowing how biomolecules interact opens the door for us to understand biological mechanisms of increasing complexity. In this course, after a brief introduction to the different experimental techniques of the study of interactions, we will use a purely bioinformatics approach to analyze the particularities of interactions of biomolecules, the study of existing databases and will end with the use of molecular simulations and docking to understand in more detail the biochemical and structural basis of these interactions.
Pre-course requirements
You need to have a good foundation in biochemistry and the ability to understand, develop and execute bioinformatics analysis tools based on Python and R.
Objectives
The central objective of this subject is to develop a holistic knowledge of the characteristics of the interactions between molecules of biological interest (proteins, nucleic acids, metabolites). In particular, in this course, we will seek:
To know the importance of molecular interaction and be able to provide examples of different types of it.
To know the main experimental methodologies used to study protein-protein interactions, as well as their virtues and limitations.
To know and learn to use databases of molecular interactions
To execute and understand simple molecular simulations and molecular docking methodologies
Competencies
General:
Team work and responsibility
Ability to adapt to complex problems and to make informed decisions
Specific:
To acquire ability to understand, to develop and to apply computational workflows to solve complex biological problems.
To master data driven research.
To develop skills for science communication in written and oral forms, making simple what is complex.
Learning outcomes
Advanced knowledge of the use of the existing repertoire of protein interaction databases.
Ability to develop computational tools in Python and R for the analysis of biomolecule interaction data.
Ability to work in a team to produce and communicate scientific research.
Syllabus
The subject is divided into three modules:
Lectures:
Biomolecule interaction:
physicochemical fundamentals
experimental techniques
Molecular interaction databases
Dynamics of molecular interactions
Laboratory:
Molecular interaction databases
The use of simulations in the study of molecular interactions
Docking
PBL:
Analysis and discussion of real examples of molecular interactions in biomedicine
Teaching and learning activities
Evaluation systems and criteria
Bibliography and resources
Structural Bioinformatics 2nd Edition Jenny Gu; Philip E. Bourne ISBN-10: 0470181052
Molecular Driving Forces: Statistical Thermodynamics in Biology, Chemistry, Physics, and Nanoscience, 2nd Edition; Ken A. Dill ISBN-10: 9780815344308