Date: Wednesday, 26 November 2025
Time:  8AM to 12:45PM
Delivery Mode: In-person 

 

 

  • Workshop #1

Title: Structural Bioinformatics: An Introductory Molecular Dynamics Workshop for Exploring Biomolecule Motion

Instructor:

  • Dr. Katherine Bradley, University of Doha for Science and Technology, Qatar
  • Dr. Asma El-Magboub, University of Doha for Science and Technology, Qatar

Synopsis:

Structural bioinformatics provides a cost effect approach to deepen our understanding of the three-dimensional structure of biological macromolecules. Within this field. molecular dynamics (MD) has become a key computational tool for exploring biomolecule motions and conformational transitions that are not accessible by any other method. This temporal information from MD can reveal new opportunities to target proteins that were once considered “undruggable” and help to uncover novel lead compounds, such as antiviral therapeutics. This is an introductory workshop for people new to molecular dynamics (MD).  The training will provide attendees with the technical skills to set up a simple all-atom (AA) biomolecule simulation using GROMACS. The training is tailored for complete beginners. No prior experience with virtual machines, Linux or MD and trajectory visualization is required.

 

  • Workshop #2

Title: Protein modelling- basics to AI- predictions

Instructor:

  • Dr. Ayesha Fatima, Riphah International University, Pakistan
  • Mr. Mohamed Salah Amine Benouar, University of Doha for Science and Technology, Qatar

Synopsis:

Proteins are the workhorses of the cell, dictating nearly every biological process from enzyme catalysis to signal transduction. When researchers endeavor to design novel drug, whether they are agonists aiming for a synergistic effect, or inhibitors designed specially to prevent the action of disease-causing receptors, access to an accurate three-dimensional model of the target protein is invaluable. Such models provide unparalleled insights into crucial aspects like the topography of binding pockets, the identification of essential residues within these pockets that mediate ligand interaction, and the diverse non-covalent interactions (e.g., hydrogen bonds, hydrophobic interactions, salt bridges) that precisely orient and stabilize a small molecule ligand within the active site. This deeper understanding of the receptor-ligand complex stability is paramount for rational drug design. This workshop will explore with the participants protein modelling techniques from conventional techniques like homology modeling using Swiss-Model to the more modern generative AI models created by Alphafold and RoseTTAFold. We will discuss landmark developments, including the advent of deep learning algorithms and their transformative success in solving the protein folding problem. While covering essential theoretical concepts, the workshop's core focus will remain on practical tools and hands-on applications to accurately predict and evaluate the quality of the predicted protein structures.

 

  • Workshop #3

Title: Becoming an Open and Reproducible Scientist

Instructor: 

  • Dr. Aziz Khan, Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates.

Synopsis:

Science has long faced a reproducibility crisis, and today reproducibility and openness are not optional, but essential for impactful research. With the rapid growth of AI, these challenges are amplified: AI can make reproducibility more problematic, but it also offers options to strengthen it. This workshop will introduce the principles of reproducibility, FAIR (Findable, Accessible, Interoperable, Reusable) data, and open science, while also exploring how AI can both hinder and enhance transparent research practices. Through hands-on examples and discussions, participants will learn practical strategies and tools to make their computational research more open, reproducible, and sustainable. Whether you are a student, early-career researcher, or established scientist looking to strengthen your research practices, this workshop will help you take meaningful steps toward becoming an open and reproducible scientist.

 

  • Workshop #4

Title: Coding for Biology: Harnessing the Power of AI

Instructor:

  • Dr. Seifeddine Bouallegue, University of Doha for Science and Technology, Qatar

Synopsis:

The rise of large language models (LLMs) such as ChatGPT is reshaping how coding is taught and practiced—especially in biology, where programming skills are increasingly essential. Today, you don’t need to be an expert programmer to build useful bioinformatics tools or automate complex biological workflows. With the right guidance and prompts, AI can help write, debug, and adapt code for real-world biological tasks. This workshop introduces participants to the practical use of AI tools to accelerate learning and development in computational biology. Through a series of guided exercises, attendees will learn how to use LLMs to generate scripts, build simple-to-advanced tools, and solve common problems in biological data analysis. Participants will experience how AI can empower them to become productive coders—regardless of prior experience. No coding background is required; just curiosity and a willingness to explore.