Molecular Dynamics

Join today
  • Instructor:  Serguei Vassiliev
  • Level: Beginner-to-Intermediate
  • Duration: 12 hours
  • Helpers: TBD
  • Date:  June 2, 4, 9 & 11, 2026 | 1:00 - 4:00 pm (Atlantic)
  • Prerequisite: None
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COURSE DESCRIPTION

This beginner-to-intermediate, hands-on workshop is designed for participants with no prior experience in Molecular Dynamics tools. Participants will learn to use AMBER and NAMD for preparing and running biomolecular simulations, VMD for trajectory visualization and PDB manipulation, and Python (PYTRAJ) for analyzing and plotting simulation data within Jupyter notebooks.


Sessions:

Day 1: Practical considerations for Molecular Dynamics.

Day 2: Visualizing Structures with VMD.

Day 3: Molecular Dynamics with AMBER and NAMD.

Day 4: Analyzing Molecular Dynamics Data with PYTRAJ.  


We will be using the online programming environment Jupyter for our teaching. Your browser must be reasonably up-to-date for this to work. You can access Jupyter Hub with current versions of Chrome, Safari, and Firefox. (Some older browsers, such as Internet Explorer 9 and lower, may not be sufficient).


Setup Requirements
  • Day 1: No setup required
  • Day 2: Download data and install required software here.
  • Day 3: Download required data here.
  • Day 4: Download required data here.

Meet our team!

Serguei Vassiliev

Instructor

Research Consultant

Serguei joined ACENET in 2019 as a Research Consultant at UNB. His background is in experimental and computational biophysics. After doctoral and postdoctoral studies in biophysics of photosynthesis, Serguei was Alexander von Humboldt Research Fellowship recipient at the Technical University of Berlin where he studied energy conversion in natural and artificial photosynthetic systems using ultrafast laser spectroscopy. More recently he was working as a research associate at Brock University with Dr. Douglas Bruce, where he was engaged in inter-disciplinary research of photosynthesis, integrating biology, computational chemistry, physics and data science. Working at Brock University, Serguei developed specialized programs for global and target analysis of time-resolved spectroscopic data, and analysis of molecular dynamics trajectories. Serguei’s research interests include molecular modelling, simulations of water and oxygen transport in proteins, and computation of the properties of cofactors in protein complexes.

Tannia Chevez

Host 

Digital Training Specialist
BSc Computational Chemistry, Memorial University

Tannia joined ACENET in 2023 and is based in St. John’s. She has held positions as a research assistant in various departments, with responsibilities ranging from developing algorithms for an online animal sound repository, to crafting chemical composite films. Proficient in Python, Java, and JavaScript, she has focused on spectral data analysis, SEM image-based nanoparticle detection, and software development for data analysis. Tannia contributed significantly to the publication of a research paper by analyzing potential environmental toxicants, generating millions of chemical structure IDs, and conducting data extraction and analysis using Python, R, and JavaScript, as well as enhancing algorithms for simulating potential environmental toxicants’ behavior in water, soil, and air environments. Tannia’s teaching experience includes a Leader Instructor at Brilliant Labs where she taught a range of digital topics, and a Digital Literacy Instructor for the Association for New Canadians.

Sarah Clarke

Host

Digital Training Specialist
MSc Computational Chemistry, Dalhousie University

Sarah, based in Nova Scotia, joined ACENET in 2023. She has a range of teaching experience and held regular teaching assistant positions. Passionate about scientific literacy, Sarah has developed teaching materials and taught programming and robotics to youth in St. John's. She has also led professional development workshops for teachers, focusing on digital skills. For her MSc in Computational Chemistry research, she focused on interfacing crystal structure prediction methods.

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We are an Atlantic Canadian not-for-profit providing access to advanced digital research infrastructure, expertise, support and training to academic, industry and government researchers. Learn more about ACENET

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