Hi Harry, Yes, the problem is indeed overloading a variable that has another meaning! But it’s also hard to wean people off of something they can read and understand, and we’re probably still not quite in a world where every tool reads mmCIF! The AlphaFold database at the EBI does give you a choice to download PDB or mmCIF format — I’d be interested in knowing how many people choose mmCIF! Interestingly, even in the mmCIF case, the atom records with the coordinates have the pLDDT values labelled as B-factors instead of using some other label. On the other hand, they have an extra loop that gives the pLDDT per residue, named appropriately.
Best wishes, Randy From: CCP4 bulletin board <[email protected]> on behalf of Harry Powell <[email protected]> Date: Monday, 26 January 2026 at 11:46 To: [email protected] <[email protected]> Subject: Re: [ccp4bb] pruning & confidence of AlphaFold models for MR Hi Randy (and others who replied privately) First off, thanks for taking the time to reply - much appreciated! This all correlates with what I would have thought. One of the off-board replies mentioned that they remove unstructured/unreliable conformations - I’d guess that these have low confidence or can be pruned out with tools like process_predicted_model and SliceNDice, or even using DSSP to only include elements with identifiable secondary structure. It occurs to me that the problem with misinterpretation of the confidence in the B-factor column could be avoided if there was a field in the mmCIF format to replace “_atom_site.B_iso_or_equiv” with something like “_atom_site.predicted_confidence"; after all, the mmCIF format is ~30 years old so isn’t everyone using it by default (no, don’t bother answering that; learning chemistry in the 1970s I learnt that we should be talking about “ethanal”, “propan-2-ol” etc (“when you work for a chemical company like ICI that’s what you’ll have to call them”), but 50 years later we still buy acetaldehyde and IPA…)? best wishes Harry On 24 Jan 2026, at 17:35, Randy John Read <[email protected]<mailto:[email protected]>> wrote: Hi Harry, Yes, this is easy to answer! There are various papers, some from my group, about the utility of AlphaFold models in MR. For the specific point of how to treat the models, you can look at the paper on process_predicted_model (https://doi.org/10.1107/s2059798322010026), which is available in both Phenix and CCP4. In CCP4, there’s also the SliceNDice tool. The side chains are considerably better than random, so they’re left in for any residues included in the model. But yes, it’s good to prune out low confidence residues, with 70 being the most common cutoff. The trickiest bit is deciding where there might be inter-domain flexibility. Domain parsing can be done in a variety of ways in process_predicted_model and SliceNDice, but the human eye is also very good at the required pattern recognition! There’s something I like to reiterate whenever possible, because we keep seeing people making this mistake. Whatever you do, don’t use the model straight out of AlphaFold! These have the pLDDT in the B-factor column, on a scale of 0-100 where 100 is nearly perfect. If you leave them as B-factors, you will be down weighting the very best parts of the model in the MR calculation! If you process the model, the pLDDT values will be turned into B-factors that are low for high pLDDT and vice versa. Best wishes, Randy From: CCP4 bulletin board <[email protected]<mailto:[email protected]>> on behalf of Harry Powell <[email protected]<mailto:[email protected]>> Date: Saturday, 24 January 2026 at 15:56 To: [email protected]<mailto:[email protected]> <[email protected]<mailto:[email protected]>> Subject: [ccp4bb] pruning & confidence of AlphaFold models for MR Hi folks I’m sure that people have thought about this, done this, and maybe even published on the topic, so this should be an easy one to answer :-) I was wondering how people treat AlphaFold models when using them in molecular replacement? Do they prune them down to poly Ala, do they include all modelled residues or remove those with low confidence (if so, how low - pLDDT 70?)? 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