Pavel has listed the papers that describe the underlying maths but unless you have high resolution data (> 1.9A say?) unscrambling results from occupancy plus B factor refinement is problematic to say the least..
Think about residues such as ARG or LYS where the termini are often extremely wobbly - they are certainly in the crystal mix butt assigning a single coordinate to those atoms is a bit of a lie.. However we do just that thinking it is better to give some guidance to the community than to assign OCC=0.0 . It is a bit the same for your ligand problem. I tend to start with both occs fixed to 0.5 and see what happens to be B values - no ideal but it gives some feeling for the problem and you can adjust the occupancies in the light of the first results. As Pavel says - once you are reasonably close the an answer you can try the mathematical approach.. Good luck Eleanor On Thu, 23 Nov 2023 at 00:30, Pavel Afonine <[email protected]> wrote: > Hi Matt, > > Im wondering about occupancy refinements - both what's going on under the >> hood and what are best practices. >> > > since you are quoting Phenix I suggest this bit of reading that is > somewhat relevant to your questions: > > https://phenix-online.org/phenixwebsite_static/mainsite/files/newsletter/CCN_2015_07.pdf#page=12 > This documents 13 typical occupancy refinement scenarios and how they can > be handled in Phenix. > > >> In the example I have, there is a ligand found in two distinct, partially >> overlapping sites that can be modeled is some confidence, but likely there >> are very low occupancy additional poses that blurs the electron density. >> The modeled poses are known from prior work, so even though there is >> smearing we know the ligand is in the modeled conformation. After >> perturbing the crystal these I am trying to decide what the best approach >> is to get some sort of numerical occupancy value to describe the >> distribution. >> > > I apologize in advance for this trivial statement, but refinement + > validation are the tools to answer your question. > If you can model these poses with an atomic model and prove they match the > experimental diffraction data ("The modeled poses are known from prior > work" doesn't count in this regard), then you are all good! Depending on > the size ration ligand:whole structure, R factors may or may not be useful > quantifiers of the modeling choices. So your best bets may be local > quantities, such as refined ligand group occupancy, flatness of Fo-Fc map > (assessed as map values at atom positions), local map-model CC, etc. Try to > challenge your modeling decisions by placing similar to expected answers > but knowingly wrong models and see how that changes the fit/quality > criteria -- that may give you a way to assess uncertainty. > > 1. In Phenix, how is the occupancy number determined? > > > Please refer to the paper I mentioned above, and let me know if you have > additional questions. > > >> Is there a real-space correlation between the experimental density and >> the model(weighted to occ) that is optimized? > > > Yes, but very indirectly through optimization of overall standard ML > target function. > > >> How can this go wrong? > > > It can go wrong in as many ways as the refinement target function has > local minima, that is in many thousands ways! > > >> I fear that the smearing and heterogenous nature will through the >> refinement off (over or underfitting to periphery density rather than >> hyper-localized position of the model) >> > > That is a valid concern that is good to keep in mind but that is not a > show-stopper! > > >> 2. Are there errors associated with the occupancy numbers? >> > > Yes, like with any model refinable parameter. For some discussion please > see: > > https://www.nature.com/articles/s41467-018-06957-w > > >> >> 3. For my own testing, I did 5% increments and manually observed Fo-Fc >> and 2Fo-Fc maps and selected a value that resulted in the lowest amount of >> both positive and negative Fo-Fc peaks. This is how we submitted the work >> to journal but reviewer wants it to be automatically calculated. > > > Above mentioned paper is now more relevant in light of this question! Yes, > you can do manual sampling to get starting values (because the closer they > are to the true values, the better chances refinement is successful), then > do some refinement starting with these values. > > Good luck! > Pavel > > > ------------------------------ > > To unsubscribe from the CCP4BB list, click the following link: > https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB&A=1 > ######################################################################## To unsubscribe from the CCP4BB list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB&A=1 This message was issued to members of www.jiscmail.ac.uk/CCP4BB, a mailing list hosted by www.jiscmail.ac.uk, terms & conditions are available at https://www.jiscmail.ac.uk/policyandsecurity/
