Date: 14 April 2026

Time: 15:00 CET

Registration

Abstract

Biological membranes exhibit intricate, large-scale dynamical architectures that are intimately coupled to cellular function, and abnormal membrane organization is implicated in many diseases. These structures arise from collective molecular interactions. Although these interactions can be described using molecular dynamics simulations, the spatiotemporal scales required to capture membrane organization at cellular and subcellular scale remain beyond the practical reach of such approaches. Meanwhile, rapid advances in experimental techniques now provide unprecedented structural and dynamical detail. Three-dimensional electron microscopy enables visualization of membrane ultrastructure at near-molecular resolution, while super-resolution microscopy reveals membrane dynamics and organization in living cells. These developments create a growing need for computational frameworks capable of bridging molecular detail with mesoscale and cellular-scale phenomena. To address this challenge, I propose integrating mesoscale membrane models into a multiscale simulation framework for biomembranes through systematic mapping and backmapping schemes, enabling the transfer of structural and dynamical information across scales.

In this talk, I will first present a few representative cases demonstrating how large-scale membrane morphology and dynamics regulate molecular-scale processes. I will then introduce a mesoscale simulation framework implemented in the FreeDTS software package and describe its integration into a multiscale modeling pipeline through the TS2CG backmapping scheme. Finally, I will present our recent advances in data-driven mesoscale membrane modeling using the Helfrich Monte Carlo Flexible Fitting (HMFF) approach. This method enables the biasing of membrane simulations using high-resolution structural data from three-dimensional electron microscopy, allowing the generation of statistically meaningful ensembles of membrane morphologies. Together, FreeDTS, HMFF, TS2CG, and conventional molecular dynamics engines constitute a unified multiscale framework that enables simulations of biomembranes across scales.

Presenters

Weria Pezeshkian

Weria Pezeshkian has a master’s degree in condensed matter physics and a PhD in molecular biophysics. Currently, he is a group leader at the Niels Bohr Institute, University of Copenhagen. His group develops and applies multiscale computer simulation methods to explore cellular forms.

LinkedIn: @weria-pezeshkian-22015a51

Bluesky: @weria-lab.bsky.social

Date: 31 March 2026

Time: 15:00 CET

Registration

Abstract

Static structural models often fail to capture the dynamic mechanisms of protein interactions. To address this, we introduce DynaPIN, an open-source pipeline for extracting dynamic interface fingerprints from molecular simulations. DynaPIN unifies quality control metrics, interface prediction accuracy assessment, and atomistic interaction analysis into a single automated workflow, accessible at https://github.com/CSB-KaracaLab/DynaPIN. A key feature is our interface-specific analysis centered on a Dynamic Interface definition, which classifies residues based on the persistence of their interaction status over the simulation. We applied DynaPIN to representative rigid, medium, and difficult targets from the DynaBench dataset, an MD simulation resource for Docking Benchmark 5.5. Our results show that interface flexibility diverges from static accuracy classifications established in Docking Benchmark 5.5, as explored before. All in all, by providing standardized, frame-resolved outputs, DynaPIN’s aim is to facilitate mechanistic studies and generate standardized unbiased data for future dynamics-aware artificial intelligence models.

Presenters

Ezgi Karaca

Ezgi Karaca is a computational structural biologist specializing in structural modeling and biomolecular dynamics. She completed her Ph.D. (2013) at Utrecht University under the supervision of Prof. Alexandre Bonvin, where she advanced HADDOCK. She then conducted her postdoctoral research at EMBL Heidelberg (2013–2016) with Prof. Teresa Carlomagno and Prof. Orsolya Barabas, developing M3, a protein complex modeling tool capable of handling 20 molecules using sparse experimental data. In 2017, Dr. Karaca established the Computational Structural Biology Lab at Izmir Biomedicine and Genome Center and joined Dokuz Eylul University. Her lab develops classical and AI-driven approaches to model biomolecular interactions and their dynamics. She received an EMBO Installation Grant (2020). Dr. Karaca was also the first assessor from Türkiye in CASP14 and CASP15 for the assembly prediction rounds. Her lab’s first online tool, PROT-ON, a structure-based web server for designing interfacial mutations, gained significant attention from the scientific community, with 50,000 uses per year worldwide.

X: @Ezgi_Karaca_

Bluesky: @ezgikaraca.bsky.social

LinkedIn: @ezgi-karaca-ibg

 

Ayşe Berçin Barlas

Ayşe Berçin Barlas is a computational structural biologist specialized in molecular dynamics simulations and biomolecular interface analysis. She completed her Ph.D. at the Izmir Biomedicine and Genome Center (IBG) and Dokuz Eylül University under the supervision of Dr. Ezgi Karaca, where she investigated how biomolecular complexes encode functional specificity through dynamics. During her doctoral research, she developed a Comparative Dynamics Analysis (CDA) framework to dissect molecular basis of sequence-specific DNA recognition by methyltransferases. As a postdoctoral researcher at IBG, Dr. Barlas is currently working on the development of DynaPIN, a Python-based package for time-resolved characterization of protein-protein interfaces. She is also one of the contributors of DynaBench, a large-scale molecular dynamics dataset designed to capture interface dynamics beyond static reference structures.

 

 

 

 

 

 

Date: 24 March 2026

Time: 15:00 CET

Registration

Abstract

The study of the interior of biomolecules is still a challenging task due to the ephemeral character of tunnels, voids and cavities While experimental techniques provide invaluable structural information, they often offer limited access to the dynamic accessibility of internal pathways and molecular transport processes. Therefore, during the workshop we will be presenting a concise overview of several studies conducted over the past few years using solvent tracking software. This will be accompanied by an explanation of the technical background of the tool and practical training. The webinar will provide insight and understanding into the function and evolution of proteins, facilitating enzyme redesign and drug discovery. We will demonstrate how to access to information about protein interior and small molecules flow direction, how to identify regions in enzymes where small molecules are stuck or trapped. We will provide an examples, how the analysis of water behaviour can help with understand the enzymatic reaction mechanism, and how it can help with drug design and discovery.

Presenters

Artur Góra

Artur is a professor at Silesian University of Technology in Gliwce, Poland and head of the Tunneling Group, where AQUA-DUCT a software for small molecules tracking was developed.

 

 

 

Agata Raczyńska

Agata holds a double PhD from the Silesian University of Technology and the University of Toulouse, and is a senior member of the Tunneling Group. She worked on the development and testing of AQUA-DUCT, as well as its implementation in various in silico-experimental studies on different enzymes.

 

 

 

Maria Bzówka

Maria obtained her PhD from the Silesian University of Technology, where she studied molecular aspects of protein regulation with a focus on the role of water molecules as mediators of intermolecular interactions. Currently, she is a postdoctoral researcher in the group of Francesco Luigi Gervasio (University of Geneva).

 

 

 

Group website: http://www.tunnelinggroup.pl/

AQUA-DUCT website: https://www.aquaduct.pl/

 

 

 

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Abstract

Molecular dynamics simulations are computationally intensive, making the efficient use of hardware crucial. In this webinar, we will explore the practical strategies for maximizing GROMACS simulation speed. By demonstrating how to interpret mdrun logs, we will “open the black box” of MD performance so that users can understand what is happening inside GROMACS during a simulation. We will discuss how system setup and properties influence performance, how these factors interact with hardware and software stacks, and how it all can be understood from GROMACS log files. Attendees will learn best practices for configuration and parallelization to ensure their simulations run as efficiently as possible. Additionally, we will also introduce a new benchmark suite for GROMACS, designed to provide a standardized framework for assessing performance across a variety of systems.

Presenters

Andrey Alekseenko

Andrey Alekseenko is a researcher at the KTH Center for Scientific Computing (KCSC) at KTH Royal Institute of Technology in Stockholm. He is a core developer of the GROMACS molecular dynamics engine, where he is working on performance optimizations for various heterogeneous architectures.

 

 

 

Szilárd Páll

Szilárd Páll is a researcher at the KTH Center for Scientific Computing (KCSC) at KTH Royal Institute of Technology in Stockholm. He helped reformulate key parallel algorithms in molecular dynamics for modern processor architectures, and co-authored the first heterogeneous CPU-GPU parallelization of GROMACS. His recent focus is on efficient asynchronous task scheduling and strong scaling MD on exascale heterogeneous architectures.

 

 

 

 

 

 

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Abstract

This webinar gives an overview of the new features and performance improvements that are included in the recently released 2026.0 version of GROMACS. Performance improvements include a complete HIP backend for AMD GPUs and non-bonded free-energy kernels for CUDA GPUs. Particular attention is devoted to new features for neural-network potentials and the inclusion and validation of the newest AMBER force fields.

Presenters

Berk Hess

Berk Hess is a professor of Theoretical Biophysics at KTH. He has designed algorithms for the GROMACS simulation package for over two decades. His current research focuses on advanced sampling methods, aggregation of molecules and studying wetting of surfaces at the molecular scale.

 

 

 

Lukas Müllender

Lukas completed his Bachelors and Masters degree in physics with a specialisation in condensed matter theory at RWTH Aachen University. For his Master’s thesis he worked on developing machine-learning collective variables for enhanced sampling from massively parallel path sampling simulations under the supervision of Prof. Paolo Carloni at Forschungszentrum Jülich. Since 2023, he is a PhD student within the AQTIVATE MSCA doctoral programme with Prof. Erik Lindahl at KTH Royal Institute of Technology, working on the implementation and application of neural network potentials in GROMACS.

 

Vedran Miletic

Vedran Miletic is an HPC application expert at MPCDF specializing in GROMACS and other biomolecular simulation software. With more than 15 years of experience in scientific software development and supercomputing, he has contributed code to numerous high-profile open-source projects across both application and compiler/toolchain domains. He has also co-authored several publications in in the areas of computational biochemistry and computational biophysics.

 

 

 

 

 

 

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Access our forum and post your questions for Samantha and Ina until the 3 March 2026

Abstract

Reproducible analysis pipelines sound great in theory, but what does that look like in the life of a busy researcher doing biomolecular system analysis with a “quick and dirty” script on their laptop computer? In this webinar, we walk you through how a bit of structure and version control can make everyday work easier to repeat, share, and build on.

Using a simple molecular dynamics (MD) analysis as a case study, we will show how to go from a one-off script to an organized reproducible collaborative project: tracking changes with git, updating the README as the workflow evolves, and handling common situations like “I found a bug, now what?” through issues and pull requests. Along the way, the session will introduce the CodeRefinery project (https://coderefinery.org/) and give a taste of other topics you can learn about in CodeRefinery workshops, such as recording software environments (for example with conda) and automated testing.

If you run command-line tools, write small scripts in any language (for example, simple bash scripts or Python code, perhaps using BioBBs), or maintain workflows and pipelines, for example, for MD analysis, attend and learn how lightweight research software engineering habits can directly support reproducible workflows, results and publications.

Presenters

Samantha Wittke joined CSC – IT Center for Science, Finland, in 2021 from a scientific background in geoecology and geoinformation technology. The majority of her work is around supporting researchers on their journey into scientific computing as well as supercomputing by providing and coordinating user support and training activities. Since 2019, she is part of CodeRefinery where she has been co-teaching “good enough” practices of “findable, accessible, interoperable and reusable” (FAIR) research software development for researchers and co-organising workshops focusing on this topic. Since 2025 she is leading the project. In 2022, she became a board member of the Nordic Research Software Engineer (RSE) association and is an active member of the RSE community. As a side project, Samantha is also working on a Ph.D. at Aalto University and the Finnish Geospatial Research Institute on the topic of applications of remote sensing time series.

 

 

Ina Pöhner holds a Ph.D. with focus on computational drug discovery from Heidelberg University and is currently a research team lead at the University of Eastern Finland. Her work focuses on computer‑aided and AI‑driven drug discovery, combining biomolecular modelling and simulations with data‑intensive automation in daily research practice. She has several years of experience developing large‑scale virtual screening workflows and research software in high‑performance computing environments, and a long‑standing interest in FAIR data and reproducible research. Since 2025, she has contributed to CodeRefinery as a lesson contributor and co‑instructor. In this webinar, she brings the perspective of a domain scientist applying lightweight research software engineering practices to her biomolecular simulation workflows.

 

Bluesky: https://bsky.app/profile/coderefinery.org

LinkedIn: https://www.linkedin.com/company/coderefinery-research-software-development/

 

 

 

 

 

View slides on Zenodo

Access our forum and post your questions for Matthieu until the 10 March 2026

Abstract

Molecular visualization is a critical task usually performed by structural biologists and bioinformaticians to aid three processes that are essential in science and fundamental to understand structural molecular biology: synthesis, analysis and communication.

Here we present VTX, a new molecular visualization software [1] that includes a real-time high-performance molecular graphics engine dedicated to the visualization of the structure and dynamics of massive molecular systems [2]. It is capable to process most molecular structures and trajectories file formats. VTX integrates innovative representations, fully customizable and usable interfaces, python bindings, and different tools and interfaces for molecular simulation. VTX constitutes the basis of the next generation integrative molecular modeling platform. VTX  is open-source (source available at https://github.com/VTX-Molecular-Visualization/VTX) and free for non-commercial use (builds available at http://vtx.drugdesign.fr)

[1] Maria M, Guionnière S, Dacquay N, Guillaume V, Plateau-Holleville C, Larroque V, Larde J, Naimi Y, Piquemal JP, Levieux G, Lagarde N, Merillou S, Montes M.VTX: Real time high performance molecular structure and visualization software. Bioinformatics (2025);41(6):btaf295 [2] Maria M, Guillaume V, Guionnière S, Dacquay N, Plateau-Holleville C, Larroque V, Larde J, Naimi Y, Piquemal JP, Levieux G, Lagarde N, Merillou S, Montes M. Interactive Visualization of large molecular systems with VTX: example with a minimal whole-cell model. Front Bioinform (2025);5:1588661

Presenter

Matthieu Montes (PR at CNAM detached to CNRS) is an ERC fellow(2015-21 and 2022-23) and senior member of the IUF (2023-2025) with expertise on Interactive Molecular Visualization and Simulation, Drug Discovery and design and computational geometry. He is the head of the molecular modeling and drug discovery team of the Computational Quantitative and Synthetic Biology unit (CQSB) UMR7238, CNRS/Sorbonne Université. His team developed key benchmarking datasets for nuclear-receptor ligand discovery (NRLiST and NR-DBIND, including negative binding data). He introduced the “predictiveness curves” framework to assess the quality and robustness of in silico screening campaigns, bridging statistical learning with cheminformatics. Prof. Montes is co-creator of the interactive real-time molecular docking software UDock, and the high-performance molecular-visualization and simulation platform VTX, enabling rapid exploration of massive molecular systems (up to billion atoms). He is the co-founder of Qubit Pharmaceuticals SAS. Prof. Montes has co-authored over 65 publications, 8 patents on therapeutic products in inflammation and cancer among which 1 vaccine candidate currently in clinical trials (orcid 0000-0001-5921-460X).

X: @MatthieuMontes

Bluesky: @matthieumontes.bsky.social

LinkedIn: https://www.linkedin.com/in/matthieu-montes-4603aa1a/

 

 

 

 

 

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Access our forum and post your questions for Claudia and Cathrine until the 24 February 2026

Abstract

The Accelerated Weight Histogram method (AWH) is an enhanced sampling technique for molecular dynamics simulations, capable of speeding up expensive computational tasks such as sampling protein conformational changes or computing binding free energies.

Here, we present two new tutorials on how to use AWH within the molecular dynamics engine, GROMACS. In the first tutorial, awh-basic, we will learn the theory behind AWH and how to use it to study the interactions of two small molecules in solution by deriving the potential of mean force. At the end of the tutorial, we will also compare the results to those obtained from another enhanced sampling technique, umbrella sampling. In the second tutorial, awh-advanced, we will expand the theoretical discussion and add multi-dimensional reaction coordinates, modified target distributions, complex pulling coordinates, and finally introduce computational parallelization in the form of multiple walkers. This tutorial will result in complex free energy landscapes describing the conformational space of a small protein.

We hope that these tutorials will demonstrate ways to use AWH to solve real scientific problems, for the novice and advanced user alike.

Presenters

Claudia Alleva earned her Ph.D. in Biophysics in Forschungszentrum Jülich in 2019 and since then has focused on membrane transporters, aiming to characterize conformational changes responsible for the coupling of cotransported species (i.e. sodium and protons).

LinkedIn: @claudia-alleva

 

 

Cathrine Bergh earned her Ph.D. in theoretical biophysics in 2023 and now works as a researcher at the PDC Center for High-Performance Computing in Stockholm, Sweden. Her work has mostly focused on developing computational techniques to understand large conformational changes of proteins and protein-ligand interactions, e.g. through Markov state models, elastic network simulations, or large-scale HPC+AI workflows.

LinkedIn: @cathrine-bergh