Dr. Sherman works closely with researchers using Schrödinger software for molecular modeling and drug design projects. All of the scripts discussed here can be downloaded free of charge from the Schrödinger Script Center, or by using 'Update...' from the Scripts menu in Maestro.
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Q. I have been using metadynamics within Desmond and am happy with the calculations. However, the analysis takes some time and freezes Maestro while running. Is there a way to run the analysis in the background?
A. We just posted an updated metadynamics analysis GUI (desmond_metadynamics_analysis_gui_2011.py) that addresses these needs. The updated script is not only faster than the last version, it also runs analysis jobs in the background so that you can keep working in Maestro. The analysis returns a free energy surface (FES) for 1 or 2 collective variables of interest.
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Q. I have a few hundred docked ligands and would like to explore the properties of the different ligands simultaneously. For example, it is difficult to browse a list of poses in the Project Table and keep track of the relationship between the 3D interactions, 2D fingerprint similarity, and other molecular descriptors. Do you have any suggestions to make this easier?
A. The new Pose Explorer script (pose_explorer.py) should help with your work. The Glide Pose Explorer can automatically compute 3D interaction fingerprints, 2D ligand fingerprints, and other molecular descriptors from a Glide poseviewer file. You can then cluster the molecules based on these different properties and view the results in multiple interactive self-organizing maps. As you might expect, the self-organizing maps are interactive – you can view the contents of individual cells in the Workspace, or select them in the Project Table.
We expect that this script should prove useful for almost any researcher who uses Glide to select lead compounds. For example, this script allows users to identify docked compounds that make the same interaction patterns with the receptor, are diverse in 2D fingerprint space, and have specific properties of interest.
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Q. I have two conformations of the same protein and would like to compute the RMSD for each residue. How can I do this?
A. You can calculate per-residue RMSDs using a recently released script designed for that exact task (rmsd_by_residue.py). Keep in mind that the input has to be 2 conformations of a protein with identical connectivity – for example, if you have a missing loop in one conformation, the script will not work properly. The output is a csv file with the RMSD for each residue.
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Q. Lately I’ve been identifying lead compounds by screening for ligands that match a Phase pharmacophore hypothesis. However, I don’t always need to use all of the options in the various Phase interfaces. Is there a simplified interface I can use? If so, when should someone use the simplified interface?
A. Yes, we have a new graphical user interface (phase_simple_hypo_gui.py) that includes only the most essential settings in Phase. This simplified GUI is designed to get you screening a database in as little time as reasonably possible.
The full-featured Phase interfaces contain a variety of options that are useful in a specific subset of cases – for example, when newly discovered information can be used to customize a pharmacophore model, or when a later-stage discovery project requires that database screens be run with specific matching criteria.
However, there are many times when a straightforward pharmacophore model can be screened against an existing database using default search criteria. If you’re unsure of whether you need to exploit the options that are only present in the full-featured interface, try running with the simplified interface. If you already know how to use the full-featured Phase interfaces, you’ll have no problem getting started with the simplified interfaces. If you haven’t yet used Phase, you’re still in luck – the interface is very easy to get started with, and contains everything you need to create a pharmacophore model and screen a database for matching ligands.
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Q. I remember seeing a paper about a way to compute changes in solvent accessible surface area (SASA) upon ligand binding and decomposing the SASA into contributions from different residue types. Do you have a script that can do this?
A. Yes, it sounds like you’re referring to the paper, “Assessment of a Novel Scoring Method Based on Solvent Accessible Surface Area Descriptors” by Nunez et al. (J. Chem. Inf. Model., 2010, 50 (4), 480–486). We wrote a script to compute the SASA descriptors used in that work. The script (binding_sasa.py) computes the total change in SASA as well as the change in SASA for different types of residues.
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