Hello, I think it is perfectly "valid" to run AlphaFold2 / RosettaFold / etc. models through geometry validation servers (aside from reporting their intrinsic quality indicators like TM-score and pLDDT distribution, as mentioned above by Randy Read). Since most experimental structures have a small percent of Ramachandran outlier residues, a good model ought to have some too. I´ve run into crystal structures that display Ramachandran outliers very well supported by the electron density, and that "strain" in the backbone later on turned out to be favorable for the catalytic mechanism, and so on... Therefore, if AF2 or RosettaFold algorithms are as good as they are advertised, they should be able to capture and predict those outliers too... and it would be very interesting to find out if they do! A model with a perfect Ramachandran plot is probably as reliable as a low resolution structure resulting from a heavily restrained geometry refinement. By the way this is true only for the polypeptide backbone conformation, I don't think any algorithm can predict side chain conformations yet (indeed AF2 offers an optional sidechain energy minimisation to tidy up side chains in the final models, a least in ColabFold by Sergey Ovchinnikov). Happy holidays, Javier
On Tue, Dec 21, 2021 at 10:29 AM Reza Khayat <[email protected]> wrote: > Hi, > > > Thank you for the help. I've addressed some of the concerns raised here in > another thread. "Validation" referred to checking geometric parameters; > however, outstanding geometric parameters do not indicate a structure that > is comparable to an experimentally determined structure. The structures > were predicted with the Robetta server and all have, as expected, geometry > better than most experimental structures. > > > Best wishes, > Reza > > > Reza Khayat, PhD > Associate Professor > City College of New York > Department of Chemistry and Biochemistry > New York, NY 10031 > ------------------------------ > *From:* CCP4 bulletin board <[email protected]> on behalf of Krieger, > James M <[email protected]> > *Sent:* Tuesday, December 21, 2021 7:14 AM > *To:* [email protected] > *Subject:* [EXTERNAL] Re: [ccp4bb] Validation of structure prediction > > There are also dedicated homology modelling validation tools such as > ANOLEA (ANOLEA (Atomic Non-Local Environment Assessment) (melolab.org) > <https://urldefense.proofpoint.com/v2/url?u=http-3A__melolab.org_anolea_&d=DwMF-g&c=4NmamNZG3KTnUCoC6InoLJ6KV1tbVKrkZXHRwtIMGmo&r=1DzJFW0v6TgEhkW1gy_-ke-RbtvS1fzEbD5_hcb9Up0&m=wygUyYLV7I0tm87EBKcsmtMhtRx3xWnT36HOD04_BCo&s=Y379nBTcaulXSuY9Y7ZQJsQSkQtJGpI8jj-fuT7THVU&e=> > ). > > Best wishes > James > ------------------------------ > *From:* CCP4 bulletin board <[email protected]> on behalf of Nicholas > Clark <[email protected]> > *Sent:* Tuesday, December 21, 2021 11:57 AM > *To:* [email protected] <[email protected]> > *Subject:* Re: [ccp4bb] Validation of structure prediction > > Reza, > > Thus far, it seems we’ve all assumed this was an AlphaFold or RobettaFold > model. If this is not indeed the case, it may be worthwhile to “validate” > your mode by running your sequence through one of these two and using the > validation from them. > > The AlphaFold DB can be found here, with a number of predicted structures: > > https://alphafold.ebi.ac.uk > <https://urldefense.proofpoint.com/v2/url?u=https-3A__nam12.safelinks.protection.outlook.com_-3Furl-3Dhttps-253A-252F-252Falphafold.ebi.ac.uk-252F-26data-3D04-257C01-257Ckriegerj-2540PITT.EDU-257Ca05aa26f114e4fb7e6c108d9c479140b-257C9ef9f489e0a04eeb87cc3a526112fd0d-257C1-257C0-257C637756847599764985-257CUnknown-257CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0-253D-257C3000-26sdata-3D1szS78fj9859h8AR0Mt5YtgUXeW1JmsB2YU0j5Hhy5U-253D-26reserved-3D0&d=DwMF-g&c=4NmamNZG3KTnUCoC6InoLJ6KV1tbVKrkZXHRwtIMGmo&r=1DzJFW0v6TgEhkW1gy_-ke-RbtvS1fzEbD5_hcb9Up0&m=wygUyYLV7I0tm87EBKcsmtMhtRx3xWnT36HOD04_BCo&s=OM7PDWl19Mz3PGjngC_uwF797ZeTV5gVNCg5RXNrUV8&e=> > > The AlphaFold colab can be found here, although the prediction is not as > good as AlphaFold 2, as it does not use templates: > > > https://colab.research.google.com/github/deepmind/alphafold/blob/main/notebooks/AlphaFold.ipynb > <https://urldefense.proofpoint.com/v2/url?u=https-3A__nam12.safelinks.protection.outlook.com_-3Furl-3Dhttps-253A-252F-252Fcolab.research.google.com-252Fgithub-252Fdeepmind-252Falphafold-252Fblob-252Fmain-252Fnotebooks-252FAlphaFold.ipynb-26data-3D04-257C01-257Ckriegerj-2540PITT.EDU-257Ca05aa26f114e4fb7e6c108d9c479140b-257C9ef9f489e0a04eeb87cc3a526112fd0d-257C1-257C0-257C637756847599764985-257CUnknown-257CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0-253D-257C3000-26sdata-3Dd323My3Ix-252BQwDW3D7ZCe6RTlY7wvMqXl92ZGRiIiMSo-253D-26reserved-3D0&d=DwMF-g&c=4NmamNZG3KTnUCoC6InoLJ6KV1tbVKrkZXHRwtIMGmo&r=1DzJFW0v6TgEhkW1gy_-ke-RbtvS1fzEbD5_hcb9Up0&m=wygUyYLV7I0tm87EBKcsmtMhtRx3xWnT36HOD04_BCo&s=iJvvBod4oNFHS9YMaLMNdy0edv1eh47A2txWBV5IuoQ&e=> > > > RobettaFold can be found here: > https://robetta.bakerlab.org > <https://urldefense.proofpoint.com/v2/url?u=https-3A__nam12.safelinks.protection.outlook.com_-3Furl-3Dhttps-253A-252F-252Frobetta.bakerlab.org-252F-26data-3D04-257C01-257Ckriegerj-2540PITT.EDU-257Ca05aa26f114e4fb7e6c108d9c479140b-257C9ef9f489e0a04eeb87cc3a526112fd0d-257C1-257C0-257C637756847599764985-257CUnknown-257CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0-253D-257C3000-26sdata-3DT3foQ-252FDRiOinSJjqeKwkPkw1UtSXc4PvyJRCTSwtUiI-253D-26reserved-3D0&d=DwMF-g&c=4NmamNZG3KTnUCoC6InoLJ6KV1tbVKrkZXHRwtIMGmo&r=1DzJFW0v6TgEhkW1gy_-ke-RbtvS1fzEbD5_hcb9Up0&m=wygUyYLV7I0tm87EBKcsmtMhtRx3xWnT36HOD04_BCo&s=8b0eA8ZDF8wlvyfoyNxzxxmGN0T58L9WsgHqEaxUoZY&e=> > > Best, > > Nick Clark > > On Tue, Dec 21, 2021 at 6:20 AM Randy John Read <[email protected]> wrote: > > Just to add one point that I don’t think I’ve seen yet. If what the > referee wants is a data-free assessment of the expected quality of the > model, I think that the best assessment at the moment is the one done by > AlphaFold2 (or indeed RoseTTAFold if you’re using one of their models). The > machine-learning algorithm is pretty good at assessing how good of a job it > has done, either overall (predicted TM score) or locally (predicted lDDT > score for AlphaFold2 or predicted RMSD for RoseTTAFold). There are cases of > false positives (poor models that think they’re good) and false negatives > (good models that think they’re bad), but these are in the minority from > what I’ve seen so far. > > Of the tools mentioned earlier, I think ProQ2 is the only one that is > really trained to assess predicted model quality, but I suspect it’s not as > good at assessing the quality of the latest generation of models as the > tools generating those models are. > > Best wishes, > > Randy Read > > > On 21 Dec 2021, at 11:12, Kay Diederichs <[email protected]> > wrote: > > > > Hi Reza, > > > > the term "validation" as used by e.g. crystallographers - namely by > checking geometric parameters of a structure derived from experiment(s) - > is euphemistic since realistic geometry is a required but not sufficient > property of a model - it can be completely wrong even if it has good > geometry. This type of validation should rather be called "checked for > geometric consistency" or similar. > > > > In general, the validation of a prediction should be performed by > experiment(s). Ideally, that would be X-ray structure solution or cryo-EM > or NMR. But it could also be e.g. a set of binding or cross-linking > experiments, with suitable positive and negative controls. > > > > That a computational prediction can be "validated" by another > calculation may be possible if the prediction is based on a set of facts > that is disjoint from that of the "validation calculation". But this is not > the case e.g. for models from AlphaFold or RoseTTaFold; MolProbility or > similar programs could at most indicate that the prediction has failed, but > not that the prediction is correct. Experiments are needed for this - and > even these could be inconclusive. > > > > Best wishes, > > Kay > > > > On Mon, 20 Dec 2021 16:10:02 +0000, Reza Khayat <[email protected]> > wrote: > > > >> ?Hi, > >> > >> Can anyone suggest how to validate a predicted structure? Something > similar to wwPDB validation without the need for refinement statistics. I > realize this is a strange question given that the geometry of the model is > anticipated to be fine if the structure was predicted by a server that > minimizes the geometry to improve its statistics. Nonetheless, the journal > has asked me for such a report. Thanks. > >> > >> Best wishes, > >> > >> Reza > >> > >> > >> Reza Khayat, PhD > >> Associate Professor > >> City College of New York > >> Department of Chemistry and Biochemistry > >> New York, NY 10031 > >> > >> ######################################################################## > >> > >> To unsubscribe from the CCP4BB list, click the following link: > >> https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB&A=1 > 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