Important notice
The course guide is provisional.
The PDF version of the course guide may take a few days to become available in the DDD.
Structure and Function of Proteins and Drug Design
Code: 42398Credits: 12
| Degree programme | Type | Course |
|---|---|---|
| Bioinformatics | OP | 1 |
Contact lecturer
- Name :
- Xavier Daura Ribera
- Email :
- xavier.daura@uab.cat
Teaching staff
- Natalia Sánchez Groot
- Berta Carrasco Martinez
- Ester Boix Borras
- Leonardo Pardo Carrasco
- Jean-Didier Pierre Marechal
- Angel Gonzalez Wong
- Laura Masgrau Fontanet
- Alex Peralvarez Marin
- Oscar Conchillo Solé
- Xavier Daura Ribera
- Marc Ciruela Jardí
Group languages
You can consult this information at the end of the document.
Prerequisites
To take this module it is necessary to have previously passed both compulsory modules I and II (Programming in Bioinformatics and Core Bioinformatics). Basic notions of Chemistry and/or Biochemistry are also needed.
Objectives
Proteins are the subject of intensive research across diverse fields, ranging from targeted drug design to the engineering of novel enzymes for sustainable industrial biocatalysis. In these areas, molecular modeling has become an essential tool, central to research conducted in both academia and industry. This module provides students with the fundamental theoretical and practical knowledge required to become skilled scientists in the field.
Specifically, the module aims to introduce students to:
- The physical principles underlying various molecular modeling techniques
- The foundational and state-of-the-art methods applied in the field
- The primary areas of application, with a particular emphasis on drug design
Learning outcomes
- CA08 (Propose bioinformatics solutions to molecular interaction problems based on structural modelling.) Propose bioinformatics solutions to molecular interaction problems based on structural modelling.
- CA09 (Work collaboratively in the analysis and interpretation of structural data in bioinformatics projects.) Work collaboratively in the analysis and interpretation of structural data in bioinformatics projects.
- CA10 (Critically evaluate molecular models by applying them in drug design studies.) Critically evaluate molecular models by applying them in drug design studies.
- KA10 (Explain the fundamentals of the experimental and computational techniques used in the structural and functional analysis of proteins, including the comparative study of protein families.) Explain the fundamentals of the experimental and computational techniques used in the structural and functional analysis of proteins, including the comparative study of protein families.
- KA11 (Explain the design and usefulness of molecular databases, such as the PDB or AlphaFold Protein Structure Database, in the study of protein-ligand interactions.) Explain the design and usefulness of molecular databases, such as the PDB or AlphaFold Protein Structure Database, in the study of protein-ligand interactions.
- KA12 (Describe structure-activity relationships and chemoinformatics and molecular modelling methods applied to drug design and evaluation.) Describe structure-activity relationships and chemoinformatics and molecular modelling methods applied to drug design and evaluation.
- SA11 (Apply tools such as Gaussian, AlphaFold, Modeller, LigandScout and Amber in the modelling and analysis of protein structures and their interactions.) Apply tools such as Gaussian, AlphaFold, Modeller, LigandScout and Amber in the modelling and analysis of protein structures and their interactions.
- SA12 (Analyse three-dimensional structures and biomolecular interactions for the investigation of structure-function relationships.) Analyse three-dimensional structures and biomolecular interactions for the investigation of structure-function relationships.
- SA13 (Relate structural and functional data in the design of computational strategies for virtual screening and drug development.) Relate structural and functional data in the design of computational strategies for virtual screening and drug development.
Contents
MODULE 4: Structure and Function of Proteins and Drug Design
Part I: Molecular Modeling
Basic Concepts
Introduction
Energy calculation (PES, QM, force fields, hybrid QM/MM)
Conformational Exploration (other than MD: MC, GA, NMA)
Part II: Structure Determination and Modeling
Methods to Determine Protein Structure
X-ray crystallography
NMR
Cryo-electron microscopy
Structural Modeling
Homology modeling
AlphaFold
Part III: Molecular Dynamics (MD)
Molecular Dynamics: An Essential Technique
Basics
MD in water
MD in a membrane environment
Coarse graining
Scripting & analysis
Enhanced sampling methods (metadynamics, GaMD, etc.)
Free energy: TI, FEP, MM/PBSA
Part IV: Drug Design
Basics in pharmacology
Hot targets and currently marketed drugs
Kinases, nuclear receptors, G protein-coupled receptors, membrane transport proteins
Molecular descriptors
ADME-Tox
Ligand-based and structure-based pharmacophore modeling
Docking
Ligand-protein docking
Protein-protein docking
Virtual screening
MD applications in drug design
Learning activities and methodology
| Title | Hours | ECTS | Learning outcomes |
|---|---|---|---|
| Regular study | 224 | 8.96 | CA08, CA10, SA11, SA12, SA13 |
| Solving problems in class and work in the computing lab | 40 | 1.6 | CA08, CA09, CA10, SA11, SA12, SA13 |
| Seminars | 2 | 0.08 | CA10, SA13 |
| Theoretical classes | 32 | 1.28 | CA08, CA10, KA10, KA11, KA12, SA13 |
The methodology will combine theoretical classes, solving problems in class, practices in the computers lab, seminars and independent study and delivarable tasks. The virtual platform of the UAB will be used.
Assessment
Continuous assessment activities
| Title | Weight | Hours | ECTS | Learning outcomes |
|---|---|---|---|---|
| Soft skills | 10% | 0 | 0 | CA08, CA09, CA10, SA13 |
| Works done and presented by the student (student's portfolio) | 50% | 0 | 0 | CA08, CA09, CA10, KA10, KA11, KA12, SA11, SA12, SA13 |
| Individual theoretical and practical tests | 40% | 2 | 0.08 | CA08, CA10, KA10, KA11, KA12, SA11, SA12, SA13 |
The evaluation system is organized in three main activities. There will be, in addition, a retake exam. The details of the activities are:
Main evaluation activities
- Soft skills (10%): attendance and participation in class, transversal competences.
- Student's portfolio (50%): works done and presented by the student all along the course. None of the individual assessment activities will account for more than 50% of the final mark.
- Individual theoretical and practical test (40%): a final exam will take place at the end of this module.
Retake exam
To be eligible for the retake process, the student should have been previously evaluated in a set of activities equaling at least two thirds of the final score of the module. The teacher will inform the procedure and deadlines for the retake process.
Not valuable
The student will be graded as \"Not Valuable\" if the weight of the evaluation is less than 67% of the final score.
This subject/module does not implement the single-evaluation system.
Use of AI (restricted use model): For this course, the use of Artificial Intelligence (AI) technologies is permitted exclusively for bioinformatics tasks that require it and for support tasks, such as bibliographic or information searches, text correction, or translations. Regarding its use in support tasks, the student must clearly identify which parts were generated using this technology, specify the tools used, and include a critical reflection on how these tools have influenced the process and the final outcome of the activity. Failure to transparently disclose the use of AI in this graded activity will be considered a breach of academic integrity and may result in a partial or total penalty on the activity’s grade, or more severe sanctions in serious cases.
Committing any irregularity during an assessment activity (academic fraud, plagiarism, or the unauthorized use of AI, unless explicitly permitted in the course guide) that could lead to a significant variation in the grade will result in a score of 0 for that specific activity. If the course guide establishes that obtaining a minimum grade in this specific assessment is an essential prerequisite to pass the course, or if multiple irregularities occur across different assessment activities within the same course, the final grade for the course will be 0. Furthermore, disciplinary proceedings may be initiated against any student who commits any of these irregularities.
Bibliography
Molecular Modeling principles and applications, A. Leach, Ed. Pearson (i.e. second edition ISBN-13: 978-0582382107) (physical document available at the UAB library services)
Essential of Computational Chemistry, C. J. Cramer, (i.e. second Edition, ISBN-13: 978-0470091821) (physical and electronic documents available at the UAB library services)
Introduction to Computational Chemistry. Frank Jensen. JohnWiley § Sons Ltd. (ISBN: 0470011874, 2007) (electronic document available at the UAB library services)
Python, how to think like a computer scientist [http://www.greenteapress.com/thinkpython/] (electronic document available at the UAB library services)
Computational and Visualization techniques for structural bioinformatics using chimera, Forbes J. Burkowski, CRC press (electronic document available at the UAB library services)
Software
On Linux:
| UCSF Chimera |
| UCSF ChimeraX |
| PyMol |
| VMD |
| Rasmol |
| Modeller |
| AlphaFold3 |
| Gaussian |
| Gaussview |
| AMBER |
| AmberTools |
| GROMACS |
| LigandScout |
| DataWarrior |
| Jupyter Notebook |
| Python |
| grace |
|
|
Course groups and languages
The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE
| Type of teaching | Group | Language | Semester | Shift |
|---|---|---|---|---|
| (TEm) Theory (master) | 1 | English | first semester | morning-mixed |
| (PLABm) Practical laboratories (master) | 1 | English | first semester | morning-mixed |
| (SEMm) Seminars (master) | 1 | English | first semester | morning-mixed |