Welcome to our tutorials and training. Each tutorial listed below is designed to be a self contained learning experience. We endeavour to provide tutorials that are free from bugs/glitches and errors, to this end we test and verify to the best of our ability. However it is inevitable that some problems escape unnoticed, should you encounter a problem, regardless of how trivial please report it to This email address is being protected from spambots. You need JavaScript enabled to view it..

Basic Skills

Python for Biomolecular Modelling

Setting up and Running Molecular Dynamics Simulations: Good Practice and Pitfalls

Software

FESetup1.2

ISAMBARD: A Python-based API for Biomolecular Structure Analysis and Parametric Design of Protein Structures

Introduction to BioSimSpace

Calculating Water Affinities in Protein Binding Sites with Grand Canonical Monte Carlo and ProtoMS

Advanced Topic - Free Energy

Free Energy Analysis

Visualising Binding Free Energies Using Swap-based Methods

Advanced Topic - Multiscale Modelling

QM/MM Modelling of Enzyme Reactions


 

Python for Biomolecular Modelling

Author: Christopher Woods

Prerequisites: basic Python

Description: This workshop will introduce more intermediate features of Python that are useful for biomolecular modellers. This will include the use of Jupyter notebooks, how to write Python functions and classes, and how to properly structure and document code. You will be introduced to data analysis tools such as Pandas, NumPy and MatplotLib.

The training material can be found here <link>.

Setting up and Running Molecular Dynamics Simulations: Good Practice and Pitfalls

 icon md setupAuthor(s): Charlie Laughton

Prerequisites: basic knowledge of the Linux command line

Description: Whether you are a user of Amber, Charmm, Gromacs, NAMD or any other MD package, there are a good number of on-line tutorials that will take you through the mechanics of setting up and running an MD simulation. However in general there is less discussion in these about how to ensure you end up with a good simulation. In this workshop we will explore some of the issues in simulation preparation and analysis that can trip up the unwary, and how to avoid them.

The training material can be found here <link>.

QM/MM Modelling of Enzyme Reactions

 interactions copyAuthor(s): Marc van der Kamp and Sam Johns

Prerequisites: basic knowledge of the Linux command line

Description: 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.

The training material can be found here <link>.

FESetup1.2

 festup1Author(s): Antonia Mey

Prerequisites: basic knowledge of Jupyter notebooks, basic knowledge of the Linux command line

Description: This workshop is designed to introduce you to how to use FESetup to prepare protein and ligand files to create simulation input for simple molecular dynamics simulations. It will also address how to then use Sire SOMD to run either a standard molecular dynamics simulation or alchemical free energy simulation. The workshop will provide a quick overview of what exactly alchemical free energy calculations are.

The training material can be found here <link>.

Isambard for Structural Analysis

 StructureFunctionandAssemblyofBiomolecules copyAuthor(s): Christopher Woods and Chris Wells Wood

Prerequisites: Python

Description: In this workshop we introduce ISAMBARD, an open-source Python package for structural analysis and rational design of biomolecules. ISAMBARD provides a generalised approach for modelling any parametrizable protein fold, as well as methods for optimizing and scoring models. In addition, it contains useful tools for the structural analysis of proteins. The practical workshop comprises three parts:

  1. An introduction to structure representation in ISAMBARD through the AMPAL (Atom, Monomer, Polymer, Assembly, Ligand) framework. This will provide a basic overview of how to work with biomolecules in ISAMBARD, including selection and analysis of structural elements.
  2. Modelling and analysis of coiled-coil structures. This will include parametric analysis of natural coiled coils to extract structural parameters, as well as creating 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.

The training material can be found here <link>.

Introduction to BioSimSpace

Author(s): Lester Hedges and Christopher Woods

Prerequisites: Python

Description: BioSimSpace is the new flagship software being produced in partnership with CCP-BioSim/HEC-BioSim. The software provides an easy-to-use Python environment for manipulating biomolecules, running simulations, and analysing / visualising outputs. BioSimSpace hides the details of using individual simulation and analysis packages behind a common, simple Python interface. This enables you to setup, run and analyse simulations using, e.g. Amber, NAMD or Gromacs, all from the same Python script or Jupyter Python interface.

The training material can be found here <link>.

Calculating Water Affinities in Protein Binding Sites with Grand Canonical Monte Carlo and ProtoMS

Author(s): Chris Cave-Ayland

Prerequisites: basic knowledge of the Linux command line, basic knowledge of Python

Description: Recent years have witnessed the maturation of our understanding of water in biomolecular association, such that present day structure-based drug design efforts often consider the influence of water on the ligand and protein. A typical concern is whether water molecules within binding sites should be targeted for displacement to improve affinity and specificity. The difficulty of this problem is often compounded by the existence of networks of interdependent waters.

This problem can be directly addressed through our recently developed simulation technique called Grand Canonical Integration (GCI). Simulations in the Grand Canonical ensemble are able to change particle number, providing a direct route to vary the number of waters in buried protein binding sites that circumvent sampling problems in conventional calculations. GCI provides a theoretically rigorous result to translate Grand Canonical simulation data into binding free energies, not just for individual waters but also entire networks.

In this workshop we will present the theoretical basis for GCI and demonstrate its practical application to a protein-ligand system. This workshop employs ProtoMS, the user-friendly Monte Carlo package developed by the Essex group at the University of Southampton.

The training material can be found here <link>.

Free Energy Analysis

Author(s): Antonia Mey

Prerequisites: Python, setting up free energy simulations

Description: Here we will explore different methods and best practices that should be employed when analysing alchemical free energy calculations for computing free energies of binding for protein and ligand complexes in an interactive python environment.

The training material can be found here <link>.

Visualising Binding Free Energies Using Swap-based Methods

Author(s): Christopher Woods

Prerequisites: Python

Description: The swap-based methods (WaterSwap, LigandSwap and ProteinSwap) are explicit solvent tools that enable you to calculate absolute and relative protein-ligand binding free energies. They can be used to predict how ligand binding is affected by protein mutations, or to predict selectivity of a ligand to different members of a protein family. In addition, these methods provide an in-built residue-based decomposition of the binding free energy, enabling you to visualise and rationalise predicted changes in binding affinity according to changes in specific protein-ligand interactions. This workshop will introduce the swap-based methods, and will take you through the process of running and analysing WaterSwap, LigandSwap and ProteinSwap simulations.

The training material can be found here <link>.