More updates to the superb MayaChemTools. A new command line script named PyMOLExtractSelection.py to extract an arbitrary PyMOL selection from a macromolecule and write it out to a file. In addition, the Psi4CalculateEnergy.py and Psi4PerformMinimization.py scripts have been updated to perform these calculations in solution using domain-decomposition-based continuum solvation models. These scripts rely on Psi4 interface to the DDX module to perform the calculations. Two solvation models are supported: COnductor-like Screening MOdel (COSMO) and Polarizable Continuum Model (PCM). A number of enhancements have been made to the PyMOLVisualizeMacromolecules.py script including identification of arbitrary distance contacts between heavy atoms in pocket residues and docked poses, visualization of solvents and inorganics in the pocket around docked poses, and visualization of B factor values for chains.

 

Manish Sud the creator of MayaChemTools has created a PyMOL session file for visualising the COVID-19 spike protein. On it he has mapped the mutations for alpha, beta, gamma, delta, and omicron spike variants on a full-length model of glycosylated spike protein in open state conformation.

Manish has made the PyMOL session freely available to download. (32MB) here

SARS-CoV-2-Spike-Protein-Open-Complex-Model-And-Variants.pse.zip.

 

This looks really interesting, Ammolite enables the transfer of structure related objects from Biotite to PyMOL for visualization, via PyMOL’s Python API:

• mport AtomArray and AtomArrayStack objects into PyMOL - without intermediate structure files
• Convert PyMOL objects into AtomArray and AtomArrayStack instances.
• Use Biotite’s boolean masks for atom selection in PyMOL.
• Display images rendered with PyMOL in Jupyter notebooks.

To install

conda install -c conda-forge ammolite

Biotite package bundles popular tasks in computational molecular biology into a uniform Python library.

 

Just a couple of notes for software installs prior to the event for those attending the free online Workshop on Open-Source Tools for Chemistry 9-13 November 2020.

Monday 13-30 to 15-30 Cheminformatics and Data Analysis using DataWarrior (Isabelle Giraud)

DataWarrior can be downloaded from here http://www.openmolecules.org/datawarrior/download.html

The training files can all be downloaded from here

Monday 16 - 00 to 18-00 Molecular visualisation using Pymol (Garrett Morris)

Software to install:

PyMOL via Conda:
Conda: https://www.anaconda.com/distribution/ or Miniconda: https://docs.conda.io/en/latest/miniconda.html
https://anaconda.org/psi4/pymol or https://omicx.cc/2019/05/26/install-pymol-windows/

PyMOL via MacPorts:
http://www.ub.edu/cbdd/?q=content/installing-pymol-macports
% sudo port install tcl -corefoundation
% sudo port install tk -quartz
% sudo port install pymol

PyMOL from GitHub: https://github.com/schrodinger/pymol-open-source

Tuesday 11 to 13-00 Chemistry in the cloud: leveraging Google Colab for quantum chemistry (Jan Jensen)

Participants should download Chrome and have a Google account
Participants should make sure they can access this page: https://bit.ly/37fIYbp.
Some basic degree of Python proficiency is required for the course

It would be great if participants could fill out this survey https://forms.gle/pjwsnJTb4X6QpiHK9 early enough to help me design the course

Wednesday 13-30 to 15-30 Accessing biological and chemical data in ChEMBL (Anna Gaulton)

Requires a modern web-browser (with javascript not blocked) such as Chrome/Safari

Thursday 16-00 to 18-00 Fragment based screening, XChem at Diamond (Rachel Skyner)

Requires Chrome web browser, if there is time Rachel would like to give an introduction to the new Python API, we can go through the installation at the workshop but you must have Anaconda installed.

Friday 11-00 to 13-00 An introduction to KNIME workflows (Greg Landrum)

Knime can be downloaded here https://www.knime.com/downloads

Registration This event will be free to attend but registration is required.

More details and registration can be found here https://www.rsc.org/events/detail/43180/workshop-on-open-source-tools-for-chemistry.

Last Updated 28 October 2020

 

All scientists working in chemistry need software tools for accessing, handling and storing chemical information, or performing molecular modelling and computational chemistry. There is now a wealth of open-source tools to help in these activities; however, many are not as well-known as commercial offerings. This workshop offers a unique opportunity for attendees to try out a range of open-source software packages for themselves with expert tuition in different aspects of chemistry.

The software packages will be presented over six two-hour sessions as follows:

09 November: 13.30 - 15.30 Cheminformatics and data analysis using Data Warrior (Isabelle Giraud) 09 November: 16.00 - 18.00 Molecular visualization using PyMOL (Garrett M Morris)

10 November: 11.00 - 13.00  Chemistry in the cloud: leveraging Google Colab for quantum chemistry  (Jan Jensen)

11 November: 13.30 - 15.30  Accessing biological and chemical data in ChEMBL (Anna Gaulton)

12 November: 16.00 - 18.00  Fragment-based screening, XChem at Diamond (Rachael Skyner)

13 November: 11.00 - 13.00  Interactive and automated chemical data analysis with KNIME (Greg Landrum)

Registration This event will be free to attend but registration is required.

More details and registration can be found here https://www.rsc.org/events/detail/43180/workshop-on-open-source-tools-for-chemistry.

 

PyMOL 2.4 has been released. Download ready-to-use bundles from https://pymol.org/ or update your installation with

conda install -c schrodinger pymol

Highlights:

• Incentive PyMOL only:

  • Support for https://lookingglassfactory.com/schrodinger
  • Pi-Pi and Pi-Cation interactions (A > find > pi-interactions)
  • WaterMap result presets (A > preset > WaterMap ...)
  • APBS Plugin improvements (multi-state assemblies, propka pH calculation)

• Open-Source and Incentive PyMOL:

  • Distinguish .mrc and .ccp4 formats (origin interpretation)
  • Trajectory handling improvements
  • Improved error handling in Python API with exceptions
  • ... many bug fixes

This will be the last release with support for Python 2.7.

Full release notes https://pymol.org/dokuwiki/?id=media:new24

 

Just a reminder that support for Python 2.7 will end on Jan 31 2020 (there will be no 2.8), all major scientific packages now support Python 3.x and there will be no further updates the Python 2.x versions.

An increasing number of projects have pledged to drop support for Python 2.7 no later than 2020, these include pandas, RDKit, iPython, Matplotlib, NumPy, SciPy, BioPython, Psi4, scikit-learn, Tensorflow, Jupyter notebook and many more.

Time to update those old scripts and Jupyter notebooks.

 

Just got this message

We are happy to announce the release of PyMOL 2.3. Download ready-to-use bundles from https://pymol.org/2/ or update your installation with "conda install -c schrodinger pymol". New features include: - Atom-level cartoon transparency - Fast MMTF export - Sequence viewer gaps display

This is the first time there are PyMOL bundles with Python 3. If you use custom or third-party Python 2 scripts, they might stop working until you convert them.

Full release notes are here https://pymol.org/dokuwiki/?id=media:new23 and

 

A new release of MayaChemTools is now available, these comprise a fantastic collection of Perl and Python scripts, modules, and classes to support a variety of day-to-day computational discovery needs.

The core set of command line Perl scripts available in the current release of MayaChemTools has no external dependencies and provide functionality for the following tasks:

• Manipulation and analysis of data in SD, CSV/TSV, sequence/alignments, and PDB files
• Listing information about data in SD, CSV/TSV, Sequence/Alignments, PDB, and fingerprints files
• Calculation of a key set of physicochemical properties, such as molecular weight, hydrogen bond donors and acceptors, logP, and topological polar surface area
• Generation of 2D fingerprints corresponding to atom neighborhoods, atom types, E-state indices, extended connectivity, MACCS keys, path lengths, topological atom pairs, topological atom triplets, topological atom torsions, topological pharmacophore atom pairs, and topological pharmacophore atom triplets
• Generation of 2D fingerprints with atom types corresponding to atomic invariants, DREIDING, E-state, functional class, MMFF94, SLogP, SYBYL, TPSA and UFF
• Similarity searching and calculation of similarity matrices using available 2D fingerprints
• Listing properties of elements in the periodic table, amino acids, and nucleic acids
• Exporting data from relational database tables into text files

The command line Python scripts based on RDKit provide functionality for the following tasks:

• Calculation of molecular descriptors and partial charges
• Comparison of 3D molecules based on RMSD and shape
• Conversion between different molecular file formats
• Enumeration of compound libraries and stereoisomers
• Filtering molecules using SMARTS, PAINS, and names of functional groups
• Generation of graph and atomic molecular frameworks
• Generation of images for molecules
• Performing structure minimization and conformation generation based on distance geometry and forcefields
• Performing R group decomposition
• Picking and clustering molecules based on 2D fingerprints and various clustering methodologies
• Removal of duplicate molecules and salts from molecules

The command line Python scripts based on PyMOL provide functionality for the following tasks:

• Aligning macromolecules
• Splitting macromolecules into chains and ligands
• Listing information about macromolecules
• Calculation of physicochemical properties
• Comparison of marcromolecules based on RMSD
• Conversion between different ligand file formats
• Mutating amino acids and nucleic acids
• Generating Ramachandran plots
• Visualizing X-ray electron density and cryo-EM density
• Visualizing macromolecules in terms of chains, ligands, and ligand binding pockets
• Visualizing cavities and pockets in macromolecules
• Visualizing macromolecular interfaces
• Visualizing surface and buried residues in macromolecules

 

MayaChemTools is a growing collection of Perl and Python scripts, modules, and classes to support a variety of day-to-day computational discovery needs.

The PyMOL command line scripts now have additional functionality:

• Volume objects to visualize X-ray and cryo-EM density for complex, chains, ligands, binding pockets, pocket solvents, pocket inorganics, etc.
• Alignment of macromolecules and densities during visualization of X-ray and cryo-EM densities
• Surface colored by vacuum electrostatics at residue level for chains and pockets
• Surface colored by hydrophobicity along with charge at atom level for chains and pockets
• Aromatic, polar, positively charged, negatively charged, and other residue group objects for chains and pockets

 

MayaChemTools now includes a collection of python scripts for PyMol

The command line Python scripts based on PyMOL provide functionality for the following tasks:

Aligning macromolecules Splitting macromolecules into chains and ligands Listing information about macromolecules Calculation of physicochemical properties Comparison of marcromolecules based on RMSD Conversion between different ligand file formats Visualizing X-ray electron density and cryo-EM density Visualizing macromolecules in terms of chains, ligands, and ligand binding pockets

MayaChemTools is a growing collection of Perl and Python scripts, modules, and classes to support a variety of day-to-day computational discovery needs.

 

cluster_mols is a PyMOL plugin that allows the user to quickly select compounds from a virtual screen to be purchased or synthesized.

The most up to date version (recommended) of clustermols is available through BitBucket at: https://bitbucket.org/mpb21/clustermols_py/overview

This plugin has a number of dependencies that are required. And it is currently only supported on Linux and OSX.

Baumgartner, Matthew (2016) IMPROVING RATIONAL DRUG DESIGN BY INCORPORATING NOVEL BIOPHYSICAL INSIGHT. Doctoral Dissertation, University of Pittsburgh.

 

The popular molecular visualisation application Pymol has been updated to version 2.0. This is a major update and the changes are detailed below.

You can either download a disk image (117 MB) or instal using Anaconda (Python 2.7)

conda install -c schrodinger pymol

Major Changes

• Unified modern interface
• PyQt interface replaces Tcl/Tk and MacPyMOL on all platforms
• Anaconda Python distribution
• Better third-party plugin and custom scripting support
• Open access incentive executables with new licensing mechanism

New Features

• Native retina resolution / 4k display support
• Dock/undock and rearrange certain panels (Builder, Feedback Browser, Volume Editor)
• Support for trackpad gestures (pinch for zoom in/out, z-rotate)
• Dedicated dialogs for opening MAE files, MTZ files, maps and trajectory files
• New APBS Plugin panel
• .pymolrc script editor with syntax highlighting
• Properties editor
• Improved Draw / RayTrace dialog
• MPEG-4 and GIF movie export panel
• Excel exporter plugin (Windows and Mac)
• Open files by dragging from file browser to PyMOL window
• wire and licorice representation aliases for combined lines/nonbonded and sticks/nb_spheres
• New commands: “copy_to” and “uniquify”
• Single-letter code labels (“label oneletter”)
• Label Wizard menus for colors and transparency
• Improved file types registration on Windows (Setting > Register File Extensions)

Settings changes

• Changed default values for several settings:
• opaque_background=off
• cartoongapcutoff=10
• autoshowclassified=1 (=3 for > 500k atoms)
• valence=on
• stickhscale=0.4
• smoothsurfaceedges=on

Menu changes

• “Open Recent” file menu
• File > New Window opens new PyMOL window
• Setting > Register File Extensions
• Plugin > Legacy Plugins
• New > Pseudoatom > Callout
• A > Copy to object
• A > State > Split

Bug fixes

• Fixed slow performance of “extract” command
• Better unicode/UTF-8 handling
• Fixed inconsistent look of labels and connectors on Retina and non-Retina displays
• Fixed labelrelativemode=2 raytracing
• Improved Maestro and MOE format compatibility
• Fixed internal GUI clipping on certain Windows systems with integrated Intel graphics

The new user interface and all core improvements will be pushed to the open source SVN repository early next year.

 

Just heard of a new PYMOL plugin, created by Jared Sampson, called PyMOLProbity which allows a PyMOL user to visualize MolProbity-style structural validation data directly in a PyMOL session. PyMOLProbity is a plugin allows the user to produce MolProbity-style visualization of atomic interactions within a structure (e.g. H-bonds, van der Waals interactions and clashes) directly within a PyMOL session.

The plugin runs local copies of several executable programs from the Richardson Lab at Duke University, authors of the MolProbity software, parses the output, and displays the results in the PyMOL viewport. There are both a graphical user interface (GUI) for general point-and-click use, and a command-line interface (CLI) suitable for scripting.

Chen et al. (2010) MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallographica D66:12-21 DOI.

Full installation instructions are here

The Reduce, Probe, and Prekin executables are only available for Linux and MacOS, PYMOL is available from Schrödinger and also available via Homebrew, you will need to install XQuartz first.

There are detailed instructions on how to install a variety of chemistry/cheminfomatics/biology packages on a Mac here.

 

An interesting post on chemistry and computers, Pymol and very large PDB files. The Zika Cryo-EM structure as a case study. Always good to see people stress testing computational tools.

 

I came across the jupyter-docker-pymol recently and thought I'd give it a mention. It is a Container-based installation of PyMol, with interaction through the browser via ipymol and Jupyter notebook (based on jupyter/notebook).

This project uses PyMol 1.8.2.0 and Python 3

 

When El Capitan first came out I upgraded a machine with an existing installation of a variety of cheminformatics tools installed using Homebrew and PIP as described here. Under this situation Pymol worked without problem. However I have had a few readers email me saying they are having problems so I took a new machine running El Capitan and tried to instal the same cheminformatics tools including Pymol using Homebrew and PIP. All worked fine except Pymol which opened but crashed with the following error.

Username:~ prompt$ pymol
PyMOL(TM) Molecular Graphics System, Version 1.7.6.0.
 Copyright (c) Schrodinger, LLC.
All Rights Reserved.

    Created by Warren L. DeLano, Ph.D. 

    PyMOL is user-supported open-source software.  Although some versions
    are freely available, PyMOL is not in the public domain.

    If PyMOL is helpful in your work or study, then please volunteer 
    support for our ongoing efforts to create open and affordable scientific
    software by purchasing a PyMOL Maintenance and/or Support subscription.

    More information can be found at "http://www.pymol.org".

    Enter "help" for a list of commands.
    Enter "help <command-name>" for information on a specific command.

 Hit ESC anytime to toggle between text and graphics.

 Detected OpenGL version 2.0 or greater. Shaders available.
 Detected GLSL version 1.20.
 OpenGL graphics engine:
  GL_VENDOR:   NVIDIA Corporation
 GL_RENDERER: NVIDIA GeForce 8600M GT OpenGL Engine
  GL_VERSION:  2.1 NVIDIA-10.0.40 310.90.10.05b12
 Detected 2 CPU cores.  Enabled multithreaded rendering.
libpng warning: Application built with libpng-1.6.19 but running with 1.5.23
/usr/local/bin/pymol: line 4:  3628 Segmentation fault: 11  "/usr/local/opt/python/bin/python2.7" "/usr/local/Cellar/pymol/1.7.6.0/libexec/lib/python2.7/site-packages/pymol/__init__.py" "$@&ldquo;

The helpful on the Pymol user list pointed me to this message on the Homebrew-Science issues

First uninstall pymol and libpng

brew uninstall pymol
brew uninstall libpng

then install pymol first.

brew install pymol
brew install libpng

Now when you type pymol in a Terminal window you should see.