Refactor RMSD analyses into MDAnalysis AnaysisBase classes#90
Refactor RMSD analyses into MDAnalysis AnaysisBase classes#90hannahbaumann wants to merge 10 commits intomainfrom
AnaysisBase classes#90Conversation
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@talagayev and @jthorton : This is a first go at the refactor into the individual RMSD classes, based on the MDAnalysis |
hannahbaumann
changed the title
AnaysisBase classes
| class LigandRMSD(AnalysisBase): | ||
| """ | ||
| 1D RMSD time series for a ligand AtomGroup. | ||
| """ | ||
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| def __init__(self, atomgroup, **kwargs): | ||
| super(LigandRMSD, self).__init__(atomgroup.universe.trajectory, **kwargs) | ||
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| self._ag = atomgroup | ||
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| def _prepare(self): | ||
| self.results.rmsd = [] | ||
| self._reference = self._ag.positions | ||
| self._weights = self._ag.masses / np.mean(self._ag.masses) | ||
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| def _single_frame(self): | ||
| rmsd = rms.rmsd( | ||
| self._ag.positions, | ||
| self._reference, | ||
| self._weights, | ||
| center=False, | ||
| superposition=False, | ||
| ) | ||
| self.results.rmsd.append(rmsd) | ||
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| def _conclude(self): | ||
| self.results.rmsd = np.asarray(self.results.rmsd) |
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2 initial thoughts:
- Can we make a more general RMSD class that can be reused for protein and ligand analysis, basically it should work on any atom group and does this not already exist in MDAnalysis?
- Do we not want to switch to use the symmetry RMSD (spyrmsd I think its called)?
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@jthorton : There's a difference between the RMSD class in MDAnalysis in what we've been doing, and I'm not sure yet what we want. In MDAnalysis, by default they are doing a superposition (rotational and translational), while we didn't do that. Now I'm not sure, what are we actually interested in, esp. for the ligand RMSD. Should this be the RMSD of the internal conformation of the ligand, or the RMSD of the ligand in the binding pocket/ligand pose? I think in the solvent we would definitely be more interested in the internal conformation of the ligand. In the binding pocket, I'm not sure. We also calculate the ligand COM displacement as a measure of stability in the pocket, but I'm not sure what we would want for the RMSD. What do you think?
talagayev
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@hannahbaumann I like it, looks very good to me :) also the structure is like for the MDAnalysis AnalysisBase classes, which is I think @IAlibay wanted to have and also adressing it that it takes any atom group adressing @jthorton comment is good.
Overall Looks good to me :)
| prot_rmsd = RMSDAnalysis(prot).run(step=skip) | ||
| output["protein_RMSD"].append(prot_rmsd.results.rmsd) | ||
| # # Using the MDAnalysis RMSD class instead | ||
| # gs = ["protein and name CA", "protein"] |
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Here is an example of how we could do the same analysis using the MDAnalysis RMSD class.
| self, atomgroup, reference=None, mass_weighted=False, superposition=False, **kwargs | ||
| ): | ||
| super(RMSDAnalysis, self).__init__(atomgroup.universe.trajectory, **kwargs) | ||
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_analysis_algorithm_is_parallelizable
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Add tests for mass weighting and superposition. Potentially import test data from MDAnalysis. |
| prot_rmsd2d = Protein2DRMSD(prot).run(step=skip) | ||
| output["protein_2D_RMSD"].append(prot_rmsd2d.results.rmsd2d) | ||
| # # Using the MDAnalysis DistanceMatrix class | ||
| # prot_rmsd2d = diffusionmap.DistanceMatrix(u, select="protein and name CA") |
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This MDA code is much slower, on the test data 10s vs. 0.4s.
| output["protein_RMSD"].append(prot_rmsd.results.rmsd) | ||
| # # Using the MDAnalysis RMSD class instead | ||
| # gs = ["protein and name CA"] | ||
| # prot_rmsd = rms.RMSD( |
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The two RMSD classes are approximately equal in timing (on the test data)
4 participants
Refactor the rmsd analysis using this example: https://docs.mdanalysis.org/2.7.0/documentation_pages/analysis/base.html
gather_rms_datafunction but access the individual analysis classes directly in the openfeProtocolmake_Universefunction go into utils?