Therefore, apart from PyMOL itself, the plugin only requires Docker to be installed and running.
Brief my pymol tutorial software#
Now, we introduce Enlighten2, which includes a Python package for the protocols, a new user-friendly PyMOL plugin and, notably, a Docker image with all the required software that allows seamless running of simulations on Windows, Mac and Linux operating systems without non-trivial software installation. These protocols have already been used to analyze enzyme-substrate interactions and dynamics ( Rice et al., 2019 Wang et al., 2018) as well as for preparation for quantum mechanical/molecular mechanical (QM/MM) simulations of enzyme reactions ( Byrne et al., 2016 Drulyte et al., 2019). There is thus a need for user-friendly, low-barrier access to MD simulation of protein–ligand complexes through a visualization program familiar to most structural biologists.Īs a first attempt to meet this need, we initially developed efficient protocols (implemented as shell-scripts) and a basic PyMOL plugin (for the legacy Tkinter GUI) as Enlighten ( ). Other options, such as the GROMACS Plugin to PyMOL (, Schrödinger, LLC, 2018) and the Molecular Dynamics Simulation option in UCSF Chimera ( Pettersen et al., 2004), still require expert knowledge (for ligand parameterization and MD simulation) and/or the non-trivial installation of MD software. Particularly important for the (re)design of enzymes as biocatalysts is assessment of the effect of mutations, for which static structural modelling alone is of limited use.Īlthough automated MD simulations are available in other visualization programs, such as YASARA Structure ( Land and Humble, 2018), the QwikMD plugin to VMD ( Ribeiro et al., 2016) or commercial program packages such as MOE or Discovery Studio, these still require users to obtain and get used to a new, unfamiliar program and interface. Such simulations offer uniquely detailed insights at high time- and space-resolution into mechanisms, dynamics and processes. Atomically detailed, physics-based MD simulation methods are demonstrating growing impact in areas as diverse as biocatalysis, biomaterials, biotechnology and drug design. Biomolecular simulation, and especially molecular dynamics (MD) simulation, is increasingly used for understanding and designing biological molecules and their interactions ( Huggins et al., 2019).
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