Subject

Biomolecular Interaction

  • code 13504
  • course 3
  • term Semester 2
  • type OB
  • credits 3

Main language of instruction: Spanish

Other languages of instruction: Catalan, English

Teaching staff

Head instructor

Dr. Jordi VILLÀ - jvilla@uic.es

Office hours

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:

  1. To know the importance of molecular interaction and be able to provide examples of different types of it.
  2. To know the main experimental methodologies used to study protein-protein interactions, as well as their virtues and limitations.
  3. To know and learn to use databases of molecular interactions
  4. To execute and understand simple molecular simulations and molecular docking methodologies

Competencies

General:

  1. Team work and responsibility
  2. Ability to adapt to complex problems and to make informed decisions

 

Specific:

  1. To acquire ability to understand, to develop and to apply computational workflows to solve complex biological problems.
  2. To master data driven research.
  3. To develop skills for science communication in written and oral forms, making simple what is complex.

Learning outcomes

  1. Advanced knowledge of the use of the existing repertoire of protein interaction databases.
  2. Ability to develop computational tools in Python and R for the analysis of biomolecule interaction data.
  3. Ability to work in a team to produce and communicate scientific research.

Syllabus

The subject is divided into three modules:

Lectures:

  1. Biomolecule interaction:
    1. physicochemical fundamentals
    2. experimental techniques
  2. Molecular interaction databases
  3. Dynamics of molecular interactions

Laboratory:

  1. Molecular interaction databases
  2. The use of simulations in the study of molecular interactions
  3. Docking

PBL:

  1. Analysis and discussion of real examples of molecular interactions in biomedicine

Teaching and learning activities


In blended

The subject is divided into three main activities:

  1. Background sessions, based on sessions taught by the teacher.
  2. Practical sessions in which the development of computer tools will allow the completion of practical exercises to solve a problem.
  3. Problem-based learning sessions in which student teams will collectively develop a critical study of an issue.

The whole subject is based on a flipped classroom scheme, in which students will have to work to prepare the content for the next sessions and, in some cases, will have to present their learning to classmates in a collaborative and critical thinking project.

Evaluation systems and criteria


In blended

The evaluation will be based on the following items: 

  1. Written exams: 
    1. Partial: 15% of the final grade 
    2. Final (including full course material): 25% of the final grade 
  2. Completion of practical exercises: 30% of the final grade 
  3. Presentation of the PBL group: 30% of the final grade 

To pass the course the student must obtain a minimum grade of 5 in each of the items mentioned (Partial, Final, Practical Exercises and PBL). If the student does not reach the 5 points on items 1a and 1b, he can take a final multiple-choice exam on June 25 to improve his grades. There is no second chance for items 2 and 3.

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 



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