Dear Ben, The Wilson scaling as given by the mmtbx routines are protein specific and I don't think using it for small molecules is the right way forward. Specifics: 1. The number of protein residues requested at __init__ aids in determining the solvent content, but it also determines which target 'standard' curve to use to scale against. 2. I don't think that the symmetry will matter, but am not sure. The data should be partitioned into bvarious symmetric classes, with epsilon weights, so that shouldn't be an issue. I all honesty, I think you are better off looking at the Wilson scaling class, and generate an idea of what it is you want it to do and reuse those ideas to get something going. The biggest issue is that the class you look at relies on the fact that a protein structure has a very standard Wilson plot. For small molecule data, no such relationship has been established yet. regards Peter On Mon, Jul 23, 2018 at 8:27 AM, [email protected] < [email protected]> wrote:
Hello any and all,
I was looking to make use of the functionality of wilson_scaling (Wilson plot, etc.) from mmtbx.scaling.data_statistics, in the context of small molecule data. I'm new to mmtbx, so here are two (groups of) questions for the enlightened: 1. Designed, as it is, with MX in mind, wilson_scaling's __init__ demands as an argument the number of protein residues, in order to form an estimate of the contents of the asymmetric unit. If this class were to be used in a small molecule context, what would be a sensible value to use? Would spoofing n_residues with an arbitrary small number (1?) be a robust bodge? Is it ever likely to howl? 2. Being crystals of small molecules, the samples in question may have inversion centres, mirror planes. Having been designed as a tool for MX, will wilson_scaling throw a wobbly when it sees my data?
Many thanks, Ben Williams Diamond Light Source
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