Advanced BioSimSpace

  • Basic python knowldege
  • Basic understanding of molecular simulations
  • Familiarity with free energy perturbation simulations
  • Familiarity with metadynamics
Alchemical free energy calculations can be used to efficiently compute binding free energies between a ligand and a protein or hydration free energies of a small molecule. In the last few years, the use of such methods has gained momentum not only within academia but also within the pharmaceutical industry. In order to run alchemical free energy simulations, a series of molecular dynamics simulations need to be carried out. In the first part of this workshop you will learn how to set up, run, and analyse, binding free energy calculations with BioSimSpace.
Metadynamics is an advanced simulation method that can be used to bypass large free energy barriers allowing the estimation of free energies for processes that would normally be impossible to observe. The method relies on the concept of "collective variables", which are used to describe the pathways between basins on the free energy surface, e.g. the distance between the centre of mass of a ligand and the binding site in a protein. In the second part of this workshop you will lean how to use BioSimSpace to set up metadynamics simulations for simple collective variables that can be run using GROMACS and PLUMED.


Aimed at: Researchers wanting to perform biomolecular structure analysis and/or de novo modelling of parameterizable protein folds such as coiled coils or other repeat proteins.

Requirements: A basic knowledge of Python is required and familiarity with Jupyter Notebooks is useful.

Abstract: ISAMBARD is an open-source Python package for structural analysis and rational design of biomolecules. This workshop will cover an overview of the basic functionality included in ISAMBARD and comprises of three parts:

  1. A basic overview of biomolecules in ISAMBARD: This session will be an introduction to structure representation in ISAMBARD through the AMPAL (Atom, Monomer, Polymer, Assembly, Ligand) framework, and will demonstrate how to perform selection and analysis of structural elements.

  2. Modelling and analysis of coiled-coil structures: We will perform analysis of natural coiled coils to extract structural parameters, as well as create models de novo using ISAMBARD specifications, which can be extended to allow users to create their own parameterisations.

  3. Optimization of the structural parameters of models: We will give a brief introduction to meta-heuristics, basic optimization of parametric models and how to analyse and interpret the results.


ISAMBARD: an open-source computational environment for biomolecular analysis, modelling and design. Bioinformatics 2017. doi: 10.1093/bioinformatics/btx352

CCBuilder 2.0: Powerful and accessible coiled-coil modelling, Protein Science 2017. doi: 10.1002/pro.3279

Advanced Simulation Methods: QM/MM

Aimed at: Anyone interested in starting to use QM/MM simulations for their research, in particular for enzyme reactions.

Requirements: Basic knowledge of the Linux command line.

Abstract: The training workshop will introduce non-specialists to the use of combined quantum mechanics/molecular mechanics (QM/MM) methods for modelling enzyme-catalysed reaction mechanisms. Concepts and techniques of QM/MM reaction modelling will be explained through hands-on exercises. During the tutorial, each participant will generate and analyse a free energy profile and a potential energy profile for the reaction catalysed by chorismate mutase.

Community Meeting

Aimed at: Biomolecular Simulation community

Requirements: None

Abstract: This is an open session to the entire biomolecular community to identify and discuss community needs in training, software, methods and resources. This will be an open forum and ideas are welcome. These discussions will help frame future plans in CCPBioSim

Introduction to Markov State Modelling

Aimed at: All Levels

Requirements: Python, some experience in the running and analysis of simulation trajectories preferred, some background in linear algebra would be beneficial.

Abstract: Markov State Models (MSM) are a set of tools to analyse molecular simulation trajectories in order to obtain estimates of long-timescale dynamics and free energies for the system of study. MSMs have been used in the past to study short term dynamics such as side chain rearrangements, to much longer dynamical properties such as protein folding, allostery, or protein-protein association. This workshop will give an introduction to the theory behind MSMs followed by a hands-on session on building an MSM. Essential steps such as clustering the simulation data, estimation of the MSM and validation of the MSM as well as the MSMs physical interpretations will be covered. We will be using pyEMMA as the software framework throughout the workshop.