Universitat Internacional de Catalunya

Biomolecular Interaction

Biomolecular Interaction
3
13504
3
Second semester
OB
BASIC HEALTH INFORMATICS TOOLS
Main language of instruction: English

Other languages of instruction: Catalan, Spanish

Teaching staff


Dr. VIAYNA GAZA, Antonio - aviayna@uic.es

Students can request an appointment with the lecturer by email:

Antonio Viayna: aviayna@uic.es

Introduction

All biological system is formed by a large and diverse network of biomolecular interactions. In this course, the student will understand how biomolecules interact, what experimental techniques and in silico tools are available for the analysis of protein-protein and protein-ligand interactions. The student will become familiar with databases and will use available databases and servers to study and analyze biomolecule interactions. They will be introduced in the state-of-the-art of structural bioinformatics for the in-silico simulation and prediction of biomolecular interactions.

The subject Interaction of Biomolecules contributes to the Sustainable Development Goals (SDGs) of the 2030 Agenda, particularly SDGs 3, 4 and 9, by promoting the health and well-being of people, fostering critical thinking and training professionals through quality education and contributing to the development of new technologies, medicines and diagnostic tools.

Pre-course requirements

Structural and functional knowledge of molecules, genetics, cellular biology, and molecular biology.

Objectives

  • Guide students in understanding the physicochemical principles and fundamental mechanisms of biomolecular interactions, and how these interactions are essential for cellular function, biological regulation, and disease development. 
  • Train students to use specialized databases and advanced computational tools to study, model, and predict biomolecular interactions. 
  • Foster in students the ability to analyze and predict the effects of genetic mutations on protein structure and function, using computational modeling and simulation tools, and discuss the implications of these changes in the context of human diseases.

Competences/Learning outcomes of the degree programme

  • CP05 - Apply biological foundations in the search for practical solutions to health problems, following ethical standards and scientific rigour and respecting fundamental equal rights between men and women, and the promotion of human rights and the values inherent in a peaceful society of democratic values that includes inclusive, non-discriminatory language without stereotypes.
  • HB08 - Use basic bioinformatics tools to analyse the structure and interaction of the main biomolecules, as well as the bioinformatics resources of the field of biomedical research.

Learning outcomes of the subject

At the end of the course, students must:

  • Identify and describe the physicochemical foundations and the main interactions between biomolecules, as well as their role in cellular function and disease development.
  • Analyze the impact of genetic mutations on the structure and function of proteins, and how these variants may be related to diseases or healthy states.
  • Use biomolecular interaction databases to identify protein-protein and protein-ligand complexes, and to explore interaction networks related to diseases and metabolic pathways.
  • Characterize protein interactions at the structural and energetic level using experimental techniques and computational tools, such as docking modeling and binding affinity simulations.
  • Predict how mutations in proteins can alter binding affinity in protein-ligand or protein-protein interactions using simulation and computational analysis tools.
  • Use bioinformatics tools for molecular simulation and biomolecular interaction prediction.

  • Apply artificial intelligence–based tools to support the prediction of biomolecular structures or interactions and compare their results with traditional computational methods.

  • Evaluate the use of artificial intelligence models in the prediction of protein structures, protein–protein/protein–ligand interactions, and mutation effects, identifying their advantages, limitations, and potential biomedical applications.

  • Use artificial intelligence models (e.g., structure or affinity predictors) to analyze biomolecular interactions and estimate the impact of mutations on stability or binding affinity in protein–protein or protein–ligand complexes.

Syllabus

Master classes (CM):

  1. Fundamentals of biomolecular interactions
    1. Physicochemical properties
    2. Types of protein interactions
      • Protein-protein
      • Protein-ligand
    3. Genetic variants in health and disease
    4. Impact of mutations on protein structure and function
  2. Prominent databases of biomolecular interactions
    1. Protein-protein/ligand complexes
    2. Protein-protein networks
    3. Disease-related networks
    4. Molecular and metabolic pathway networks
    5. Binding affinity
  3. Characterization of protein interactions
    1. Structural characterization of protein interactions
      1. Experimental techniques
      2. Computational characterization of protein and protein-protein/ligand interfaces
      3. Computational modeling of protein interactions
        • Template-based docking
        • Ab initio docking
      4. Integrative modeling of protein interactions
    2. Energetic characterization of protein interactions
      1. Experimental techniques
      2. Computational tools available
    3. Current limitations

Case Methods (MC):

  1. Analysis of specific protein-protein interaction using interaction databases.
  2. Protein-ligand simulation.
  3. Prediction of binding energy changes upon mutation.

Laboratory:

  1. Databases and servers for the structural characterization of proteins and biomolecular interactions.
  2. Use of computational tools for the simulation and prediction of molecular interactions related with Malaria.

Teaching and learning activities

In person



Fully in-person modality in the classroom

1. Lectures – 20 hours: Presentation of a theoretical topic by the instructor.

2. Case Method (CM) – 6 hours: Presentation of a real or imaginary situation. Students work on the proposed questions in small groups or through active interaction with the instructor, and the responses are discussed. The instructor actively participates and provides new knowledge.

3. Practical classes – 4 hours: Conducted in small groups. The instructor presents a problem and guides the search for a solution, while students develop the methodology implemented by the instructor.

4. Virtual Education (VE): Online materials available through the intranet.

Evaluation systems and criteria

In person



1)    Students in the first call:  

Partial exam 20%
Final exam: 40%
Case Methods: 20%
Practical sessions: 20%

2)    Students in the second chance:

Only there is chance to repeat the final exam. Computing in the final grade the partial exam, methods of the case and the practical exercises obtained in the first call.

3)    Students who repeat the subject: 

The continuous assessment grade (participation in class, case methods, practical sessions) will be saved, although whenever they wish, students can repeat the class assistance and obtain a new grade. On the other hand, students will be able to choose whether to do the partial and the final, or if they do only the final, which will count 60% of the grade.

General points to bearing in mind about the evaluation system:  

1) To pass the course the student must obtain a minimum grade of 5 in the final exam to get a mean of all grades.

2) The exams will be single-shoice test. The multi-choice test has 4 answer options, count +1 each answer and -0.33 each incorrect answer.

3) Class attendance:

  • The regular attendance is recommended for the theorical sessions.
  • Attending at master classes is not mandatory, but attendees will have to abide by the rules indicated by the teachers. The expulsion of a student from the master class or the case method will negatively affect the continuous evaluations.
  • The attendance to the case methods is mandatory. All case methods will be evaluated. The lack of attendance must be justified (illness, vaccine citation, etc.), on the contrary, the right to be evaluated by the method of the specific case will be lost.
  • The attendance to the practical sessions is mandatory and the student must attend in assigned groups. The expulsion of a student from the practice room will mean the automatic suspension of the subject.  

4) When granting Honours, special consideration will be given to the candidates for their participation and involvement in the subject, as well as respect for the basic rules.

5) The inappropriate use of electronic devices such as mobile phones, tablets or laptops can lead to expulsion from class. Inappropriate use is understood as the recording and dissemination of both students and teachers during the different lessons, as well as the use of these devices for recreational and non-educational purposes.

Bibliography and resources

Protein Structure Prediction. Methods in Molecular Biology, vol 2165 (2020). Humana Press. Edited by Daisuke Kihara. ISBN: 978-1-0716-0710-7. https://link.springer.com/book/10.1007/978-1-0716-0708-4

Protein-Protein Interactions. Methods in Molecular Biology, vol 1278 (2015). Human Press. Edited by Cheryl L. Meyerkord, Haian Fu. ISBN: 978-1-4939-2425-7. https://link.springer.com/book/10.1007/978-1-4939-2425-7

Protein-Protein Interactions and Networks. Methods in Molecular Biology, vol (2008). Humana Press. Edited by Panchenko A, Przytycka T. ISBN: 978-1-84800-125-1 https://link.springer.com/book/10.1007/978-1-84800-125-1

Protein-Ligand Interactions. Methods in Molecular Biology, vol 305 (2005). Humana Press. Edited by G. Ulrich Nienhaus. ISBN: 978-1-61737-525-5. https://link.springer.com/book/10.1385/1592599125

Protein-Protein Interactions in Human Disease. Advances in Protein Chemistry and Structural Biology, vol 110 (2018). Edited by Rossen Donev. ISBN: 978-0-12-814344-5. https://www.sciencedirect.com/bookseries/advances-in-protein-chemistry-and-structural-biology/vol/110/suppl/C

Structural Bioinformatics. Methods in Molecular Biology, vol 2112 (2020). Humana Press. Edited by Zoltán Gáspári. ISBN: 978-1-0716-0272-0. https://link.springer.com/book/10.1007/978-1-0716-0270-6

Lehninger: principles of biochemistry (4th edn) D. L. Nelson and M. C. Cox, W. H. Freeman & Co., New York ISBN 0-7167-4339-6 (2004). https://onlinelibrary.wiley.com/doi/10.1002/cbf.1216

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment. Lensink MF, Brysbaert G, Mauri T, Nadzirin N, Velankar S, Chaleil RAG, Clarence T, et al. (2021), Proteins, 89(12):1800-1823. https://doi.org/10.1002/prot.26222

Structural and Computational Characterization of Disease-Related Mutations Involved in Protein-Protein Interfaces. Navío D, Rosell M, Aguirre J, de la Cruz X, Fernández-Recio J. (2019), Int J Mol Sci, 20(7):1583. https://doi.org/10.3390/ijms20071583

Hot-spot analysis for drug discovery targeting protein-protein interactions. Expert Opin Drug Discov. Rosell M, Fernández-Recio J. (2018), 13(4):327-338. https://doi.org/10.1080/17460441.2018.1430763

Weak protein–ligand interactions studied by small-angle X-ray scattering. Tuukkanen, A.T. and Svergun, D.I. (2014), FEBS J, 281: 1974-1987. https://doi.org/10.1111/febs.12772

First homology model of Plasmodium falciparum glucose-6-phosphate dehydrogenase: Discovery of selective substrate analog-based inhibitors as novel antimalarial agents. Alencar N, Sola I, Linares M, Juárez-Jiménez J, Pont C, Viayna A, Vílchez D, et al. (2018), Eur J Med Chem, 146:108-122. https://doi.org/10.1016/j.ejmech.2018.01.044

Docking-based identification of small-molecule binding sites at protein-protein interfaces. Rosell M, Fernández-Recio J. (2020), Comput Struct Biotechnol J., 18:3750-3761. https://doi.org/10.1016/j.csbj.2020.11.029

Evaluation period

E: exam date | R: revision date | 1: first session | 2: second session:
  • E1 22/05/2026 A08 14:00h
  • E2 30/06/2026 I3 16:00h
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