Shapespyer 0.2.3

Python toolkit for generation and equilibration of complex soft matter systems

This package includes Python tools and Bash shell scripts for preparation, running and analyses of soft matter simulations.

Shapespyer documentation with examples and tutorials

Key functionality:

• Main toolkit: Python package for generation of ordered molecular aggregates and pre-assembled composite structures to seed molecular dynamics (MD) simulations aimed at studying equilibration (relaxation) processes in soft matter and biomolecular systems.

• Bash scripts for automated workflows for preparation and running simulations using Gromacs, NAMD, DL_POLY or DL_MESO MD engines (MC via DL_MONTE to be added).

• Scripts (Python and Bash) for semi-automated analyses of cluster formation and evolution, including cluster number and size distributions, but also radii of gyration and principal moments of inertia.

• Parsing SMILES strings (from 'smiles.sml') and generating 3D chemical structures

From the outset, the Shapespyer project has been kindly supported by the Ada Lovelace Centre for expertise in scientific software, research software engineering and data management.

Partners

International:

Hanna Barriga, KTH, Sweden (nanoscale structure and dynamics in biological processes)

Margaret Holme, Chalmers, Sweden (self assembled lipid structures for biomedical applications)

Karen Edler, Lund University, Sweden (functional hierarchically structured materials)

SasView & SASSIE teams (SAS calculations based on MD trajectories)

National (UK):

Jian Lu, Biological Physics, Manchester University (bio- and soft matter physics, self-assembly, interfaces)

Lorna Dougan, School of Physics and Astronomy, University of Leeds (hierarchical biomechanics, extreme biophysics)

Valeria Losasso, Computational Biology group, SCD, DL, STFC (lipid bilayers, multi-lamellae)

Tom Headen, ISIS, RAL (coarse-grained SAS calculations based on molecular dynamics simulations)

SAS and Reflectometry beamlines, ISIS, RAL (SAS and Reflectometry experiments)

Project description

Started in April 2020, the Shapespyer project is a thriving collaboration between SCD, ISIS and Diamond, funded by and developed under the umbrella of the Ada Lovelace Centre (ALC), aiming to support and facilitate interdisciplinary research by bridging between theoretical analysis, computer simulation and experimental studies.

The primary goal of the project is to equip Small Angle Scattering (SAS) experimentalists at ISIS and Diamond facilities in RAL with a set of simulation and analytical protocols allowing for the verification of hypotheses and theoretical models of complex molecular nanoaggregates via direct correlation of SAS experiments to detailed computer simulations.

In turn, it is anticipated that this would facilitate the automation of common, routine, tasks associated with the creation, simulation and analysis of complex multicomponent aggregates, which would both simplify and standardise the use of simulations in analyses of SAS experiments. With this in mind, the Shapespyer software package has been developed as an experimentalist-oriented Python framework providing a straightforward workflow to facilitate the analysis of self-assembled nanostructures, ubiquitous in soft condensed matter, and specifically those with biomolecular applications.

Background

In the domain of functional soft matter and biomolecular simulation, the task of preparing complex molecular structures of interest is both challenging and tedious. The naive approach using an initial configuration with randomised positions of solute molecules is most often fruitless due to the complexity of the (unknown) pathways that lead to self-assembly of any particular shape of a molecular aggregate. Unfortunately, pre-equilibration into and further relaxation of a specific molecular complex can easily require simulation times way beyond what is reachable in a practical simulation scenario. Therefore, it is vital to have efficient tools facilitating the generation and initial equilibration of pre-assembled molecular complexes with predetermined composition and structure.

Concept

Taking a number of sample (template) molecules as inputs, automatically generate a predefined larger, possibly multicomponent, structure that could be used as input for molecular dynamics (MD) or Monte Carlo (MC) simulations carried out on virtually any computing platform. The results from these calculations include equilibrated structures and trajectories that can be analysed and compared with results from small angle scattering (SAS) experiments.​

Illustrations

Diagrams