Difference between revisions of "Main Page"

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__NOTOC__
 
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! Official Release
 
! Official Release
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| [http://pymol.org PyMOL v1.8.4 has been released] on October 4, 2016.
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| [https://pymol.org PyMOL v2.3 has been released] on February 11, 2019.
 
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! New Script
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! POSF
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| [[dssr_block]] is a wrapper for DSSR (3dna) and creates block-shaped nucleic acid cartoons
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| [https://pymol.org/fellowship New PyMOL fellows announced for 2018-2019]
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! New Plugin
 
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| [[Lisica|LiSiCA]] is a new plugin for 2D and 3D ligand based virtual screening using a fast maximum clique algorithm.
 
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! Official Release
 
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| [http://pymol.org PyMOL v1.8.0 has been released] on Nov 18, 2015.
 
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! PyMOL Open-Source Fellowship
 
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| Schrödinger is now accepting applications for the PyMOL Open-Source Fellowship program! Details on http://pymol.org/fellowship
 
 
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! Official Release
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! Tutorial
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| [http://pymol.org PyMOL, AxPyMOL, and JyMOL v1.7.6 have all been released] on May 4, 2015.
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| [[Plugins Tutorial]] updated for PyQt5
 
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! New Plugin
 
! New Plugin
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| [[PyANM|PyANM]] is a new plugin for easier Anisotropic Network Model (ANM) building and visualising in PyMOL.
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| [[ProBiS_H2O|ProBiS H2O]] is a new plugin for identification of conserved waters in protein structures.
 
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! New Plugin
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! Selection keywords
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| [[Bondpack]] is a collection of PyMOL plugins for easy visualization of atomic bonds.
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| New [[Selection Algebra|polymer.protein and polymer.nucleic]] selection keywords. Thanks everyone who participated in the [https://goo.gl/forms/r0Ck03VTytZQxN4A2 poll]!
 
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! New Plugin
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! Plugin Update
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| [[MOLE 2.0: advanced approach for analysis of biomacromolecular channels|MOLE 2.0]] is a new plugin for rapid analysis of biomacromolecular channels in PyMOL.
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| [[MOLE 2.0: advanced approach for analysis of biomacromolecular channels|MOLE 2.5]] is an updated version of channel analysis software in PyMOL
 
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! 3D using Geforce
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! New Script
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| PyMOL can now be [http://forums.geforce.com/default/topic/571604/3d-vision/3d-vision-working-with-qbs-in-opengl-software-using-geforce/2/ visualized in 3D using Nvidia GeForce video cards] (series 400+) with 120Hz monitors and Nvidia 3D Vision, this was previously only possible with Quadro video cards.
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| [[dssr_block]] is a wrapper for DSSR (3dna) and creates block-shaped nucleic acid cartoons
 
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! Older News
 
! Older News

Revision as of 11:18, 11 February 2019

hosted by SBGridlogo2.jpg
Welcome to the PyMOL Wiki!
The community-run support site for the PyMOL molecular viewer.
To request a new account, email SBGrid at: accounts (@) sbgrid dot org
Quick Links
Tutorials Table of Contents Commands
Script Library Plugins FAQ
Gallery | Covers PyMOL Cheat Sheet (PDF) Getting Help
News & Updates
Official Release PyMOL v2.3 has been released on February 11, 2019.
POSF New PyMOL fellows announced for 2018-2019
Tutorial Plugins Tutorial updated for PyQt5
New Plugin ProBiS H2O is a new plugin for identification of conserved waters in protein structures.
Selection keywords New polymer.protein and polymer.nucleic selection keywords. Thanks everyone who participated in the poll!
Plugin Update MOLE 2.5 is an updated version of channel analysis software in PyMOL
New Script dssr_block is a wrapper for DSSR (3dna) and creates block-shaped nucleic acid cartoons
Older News See Older News.
Did you know...

Cluster mols

Cluster mols py pymol.png

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

It helps the user by automatically clustering input compounds based on their molecular fingerprints [1] and loading them into the PyMOL window. cluster_mols also highlights both good and bad polar interactions between the ligands and a user specified receptor. Additionally there are a number of keyboard controls for selecting and extracting compounds, as well as functionality for searching online to see if there are vendors for a selected compound.

Description

The basic work flow of cluster_mols.py can be broken up into three parts.

  1. Computing a similarity matrix from the input compounds
  2. Performing hierarchical clustering on the results from 1)
  3. Cutting the tree at a user-specified height and creating and sorting clusters

The results of 1 and 2 are saved to python pickle files so you do not have to recompute them in ..→

A Random PyMOL-generated Cover. See Covers.


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