The aim of this workshop is to introduce researchers to the field of Chemoinformatics, especially in the areas of Structure-Based Drug Design (SBDD) and Ligand-Based Drug Design (LBDD). Trainees will cover the use of protein, ligand and drug databases, protein modelling, molecular docking and virtual screening for drug discovery applications. Managing and analysing virtual chemical libraries will also be covered, including the application of machine learning algorithms in drug discovery.

The workshop will be instructed by trainers from the University of Antioquia in Colombia, from CINVESTAV Unit for Advanced Genomics (LANGEBIO) in Mexico, as well as local expert researchers from the School of Chemistry at the National Autonomous University of Mexico (UNAM).

Who is this course for?

This workshop is suitable for researchers working in Latin American countries. Early career researchers, including graduate students, postdocs and professors working, or planning to start working in Chemoinformatics, are warmly encouraged to apply.

This workshop will be located in a room with computers however we recommend participants bring their own laptops.

A number of travel fellowships are available for this course - early-stage researchers and researchers from underrepresented groups are especially encouraged to apply for CABANA travel fellowships. You can apply for travel fellowships via the course application form.

Prerequisites: 
Undergraduate-level knowledge of chemical and protein structures are required. Familiarity with basic chemoinformatics concepts and notions of programming (R, Python and/or UNIX) are recommended. Please note this course will be taught in English, however, the trainers are fluent in Spanish and can offer language support where needed.

What will I learn?

Learning outcomes

After this course, you should be able to:

• Visualize proteins and ligands using molecular visualization tools
• Browse and investigate biomolecular structural information using PDBe
• Use molecular docking and virtual screening for hit identification
• Apply homology modelling to the prediction of protein structures
• Apply predictive models (regressions, classifications) to molecules

Course content

During this course you will learn about: 

• Protein Databank in Europe (PDBe) resources
• Molecular visualization tools such as PyMol
• DataWarrior
• Homology modelling using MODELLER, molecular docking and virtual screening
• BIOFACQUIM compound database
• Machine learning algorithms and statistics for drug discovery

Trainers

In order to be considered for a place on this course applicants must complete the online application form.

Incomplete applications will NOT be considered. 

If you have any queries about the registration process please email Guilherme Oliveira and Piv Gopalasingam.

Please note that the registration fee of $800 MXN includes:

• Lunches and refreshment breaks
• Accommodation for 5 nights (14-18 Oct)
• Course materials 
• Course dinner on Thursday, October 17th
• Course certificate