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News & Updates Official Release PyMOL, AxPyMOL, and JyMOL v1.7.4 have all been released on December 2, 2014. New Plugin PyANM is a new plugin for easier Anisotropic Network Model (ANM) building and visualising in PyMOL. PyMOL Open-Source Fellowship Schrödinger is now accepting applications for the PyMOL Open-Source Fellowship program! Details on http://pymol.org/fellowship Official Release PyMOL, AxPyMOL, and JyMOL v1.7.2 have all been released on August 4, 2014. Official Release PyMOL, AxPyMOL, and JyMOL v1.7 have all been released today, January 14, 2014. New Plugin Bondpack is a collection of PyMOL plugins for easy visualization of atomic bonds. New Plugin MOLE 2.0 is a new plugin for rapid analysis of biomacromolecular channels in PyMOL. 3D using Geforce PyMOL can now be 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. New Plugin GROMACS_Plugin is a new plugin that ties together PyMOL and GROMACS. New Software CMPyMOL is a software that interactively visualizes 2D contact maps of proteins in PyMOL. New Script cgo_arrow draws an arrow between two picked atoms. Tips & Tricks Instructions for generating movie PDFs using .mpg movies from PyMOL. Older News See Older News.

Did you know... Intra xfit Included in psico This command or function is available from psico, which is a PyMOL extension. Module psico.fitting intra_xfit does a weighted superposition of a multi-state object, like an NMR-ensemble. The weights are estimated with maximum likelihood. This typically gives much better looking ensemble-fittings than the built-in intra_fit command, which does not do any outlier rejection or weighting. To superpose two different objects, use xfit. Installation intra_xfit is available from the psico package and requires CSB. All dependencies are available from Anaconda Cloud: conda install -c schrodinger pymol conda install -c schrodinger pymol-psico conda install -c speleo3 csb Usage intra_xfit selection [, load_b [, cycles [, guide [, seed ]]]] Arguments selection = string: atom selection from a single multi-state object load_b = 0 or 1: save -log(weights) into B-factor column {default: 0} cycles = int: number of weight ..→

A Random PyMOL-generated Cover. See Covers.