Dear all, I feel the need to respond following last week’s critique of the use of Coot’s map blurring tool for providing diagnostic insight and aiding ligand identification…
> On 24 Nov 2020, at 16:02, Dale Tronrud <de...@daletronrud.com > <mailto:de...@daletronrud.com>> wrote: > > To me, this sounds like a very dangerous way to use this tool decide if a > ligand has bound. I would be very reluctant to modify my map with a range of > arbitrary parameters until it looked like what I wanted to see. The > sharpening and blurring of this tool is not guided or limited by theory or > data. I disagree with this, subject to the important qualification that care is needed with interpretation. Blurring isn't a crime - it merely involves adjusting the weighting given to lower versus higher resolution reflections, and thus allows relaxation of the choice of high-resolution limit, and facilitates local investigation of regions that exhibit a poor signal-to-noise ratio. This is particularly pertinent to liganded compounds, which are typically present with sub-unitary occupancies. Coot's blurring merely involves convolution of the whole map with an isotropic 3D Gaussian, with a parameter (B-factor) to control the standard deviation of the Gaussian. This corresponds to reweighting the structure factors in order to give higher weight to lower-resolution reflections. This approach is guided by a very simple theory: higher resolution structure factors (SFs) are typically noisier, with a worse signal-to-noise ratio than lower resolution SFs (due to increased errors in both observed higher-resolution reflections and calculated phases). Consequently, increasing the blurring B-factor reduces the effect of the noisier higher-resolution SFs. This results in a map that should be more reliable, but at the expense of reduced structural detail due to artificially reducing the effective resolution. It should be noted that this does assume that lower resolution reflections are more reliable than higher resolution ones. So, good low-resolution data quality and completeness is important. Unfortunately, determination of an optimal B-factor parameter is not presently automated. Consequently, users are currently expected to trial different values in the Coot slider tool in order to maximise information and gain, for want of a better word, intuition. Furthermore, due to the spatially heterogeneous nature of atomic positional uncertainty in macromolecular complexes, it can be that different B-factor parameters are of optimal usefulness in different local regions of the map that exhibit different signal-to-noise ratios. Such issues are on-going areas of research. The main problem is that interpretation is subjective. In difficult cases, it is necessary to obtain as much information and insight as possible in order to gain a good intuition. If you can't see a ligand in the "standard" maps, but you can see evidence for a ligand in blurred density (or difference density) maps of the various types, then it means that careful exploration of those avenues is required. Any "evidence" from viewing such maps and map types should serve to guide intuition, and should be digested along with all other available information. Such complementary maps should be seen as diagnostics to gain intuition, rather than something that can be used as an unequivocal argument for ligand binding. Ultimately, the presence of significant density in a blurred map means that there is something substantial present. Or in a blurred difference density that there is something missing from the current model. This could be a missing ligand, or it could be a mismodelled region of the macromolecule, or it could be mismodelled solvent (in which case re-evaluating any solvent mask may be worthwhile). Ultimately it is down to the practitioner to explore all potential explanations for any such behaviour, in order to maximise intuition and convince themselves of the crystal's structural composition. In some cases the presence of density in a blurred map might be sufficient to convince the practitioner that it is worth pursing investigation of binding. This may take various forms: hypothesising an approximate pose for the ligand; the nature of interactions in the structural environment of the macromolecule; re-evaluation after modelling and refinement; or simply stating that there may be evidence of binding. In many cases, the latter is the appropriate action, and, as Robbie quite rightly pointed out: "in a scientific setting this digging is not to come to a strong conclusion, but only to see if you should pursue the project and do additional experiments". > On 24 Nov 2020, at 16:02, Dale Tronrud <de...@daletronrud.com > <mailto:de...@daletronrud.com>> wrote: > [...] to avoid bias in the interpretation of the results, all of the > statistical procedures are decided upon BEFORE the study is even began. This > protocol is written down and peer reviewed at the start. Then the study is > performed and the protocol is followed exactly. > [...] I would recommend that you decide what sort of map you think is the > best at showing features of your active site, based on the resolution of your > data set and other qualities of your project, before you calculate your first > Fourier transform. If you think a Polder map is the bee's knees then > calculate a Polder map and live with it. If you are convinced of the value > of a FEM, or a Buster map, or a SA omit map, or whatever, calculate that map > instead and live with it. I agree that such an approach would be more scientific, and I certainly find this idea very appealing. Whilst I hesitate to speak against such a philosophy, I feel it is necessary to temper/balance this view by pitching a counterargument in the interests of pragmatism - in general it's just not that practical. And perhaps propositions for revolution of best-practice policies within the field should be distinct from current practical recommendation, in the interests of avoiding potential confusion for the student/user who simply wants a solution that they can apply to today's problems. Whilst it sounds like a nice ideal, in general it is difficult to know which pathologies might be encountered (e.g. ambiguous density in the binding site; twinning; modelling difficulties around a symmetry axis; multiple conformations; semi-disorder; post-translational chemical modifications; radiation damage… the list goes on). It's completely acceptable for someone encountering a problem for the first time to explore what tools are available to guide any decision-making, in the hope of achieving the best model possible. A typical user cannot be expected to outline a strategy for every eventuality a priori - that sounds more like the design of an automated pipeline, not advice that users should be expected follow. In summary, it's unadvisable to put all eggs in one basket (of one type of map, Polder or otherwise). If an experienced user likes a particular tool because it's worked well for them in the past, it doesn't mean that they shouldn't try other tools now (in this case: view other types of maps) the next time they encounter a problem. Especially given that tools in our field are still very much evolving over time. Different approaches may have more value and provide more insight in different circumstances. Best regards, Rob ######################################################################## 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/
