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 <CCP4BB@JISCMAIL.AC.UK> on behalf of Krieger, James M <krieg...@pitt.edu> Sent: Tuesday, December 21, 2021 7:14 AM To: CCP4BB@JISCMAIL.AC.UK 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 <CCP4BB@JISCMAIL.AC.UK> on behalf of Nicholas Clark <ndcla...@buffalo.edu> Sent: Tuesday, December 21, 2021 11:57 AM To: CCP4BB@JISCMAIL.AC.UK <CCP4BB@JISCMAIL.AC.UK> 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 <rj...@cam.ac.uk<mailto:rj...@cam.ac.uk>> 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 > <kay.diederi...@uni-konstanz.de<mailto:kay.diederi...@uni-konstanz.de>> 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 > <rkha...@ccny.cuny.edu<mailto:rkha...@ccny.cuny.edu>> 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: >> 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