Combining all maps from a map series from 3DVA would be equivalent to taking the "consensus" map before 3DVA was applied, I believe (it depends what one means by "combine"). This map is blurry, since it results from aligning images of particles that all have slightly different conformations (and therefore can never align perfectly). So, doing this would cancel all the benefits of running 3DVA. The same applies with cryoDRGN, it would not be useful to average together all the different states it found in a heterogeneous set of particles. And to answer this earlier question: Also.. just curious -- what is "3D variability of this map"? Is this one map that is a composition of several map or an ensemble of maps? The big picture is that 3DVA is a PCA trying to find the major ways in which 2D particle images differ. Once principal components of variability are identified, it can then generate maps that are linear interpolations between observed particles, taken along the principal components. What is most often done in practice is to generate a series of maps traversing the first one or two principal components (or as many as you want until you explain most of the variability in the data). This can often identify hinge motions in a complex, or similar large-scale conformational changes. Now, because these maps are linear interpolations, they can sometimes show unphysical features, so I am not sure refining a model against these maps would work well. But it would with maps from cryoDRGN, since it does no such interpolation and can even generate maps that are guaranteed to be supported by observed data. This is very simplified, I am no expert in computational methods. If you want to understand better what is reasonable to do with these maps, you need to know how they are produced, and the two papers I pointed to in my previous message explain this in detail. I hope this helps, Guillaume On 13 Jan 2022, at 17:40, Pavel Afonine mailto:[email protected]> wrote: Hi, good discussion, thanks! Instead of having a series of maps would it make sense to combine all these maps into one composite map, and then refine one atomic model against this composite map, and model variability using alternative conformations (very much like in crystallography)? If that's a possible route then all is needed is a tool to combine the maps and phenix.real_space_refine can already handle models with alternative conformations (can refine occupancies in real space). Pavel On 1/13/22 08:17, Oliver Clarke wrote: Hi, Just to add my two cents, I agree this would be really useful for a lot of folks. Analysis of continuously distributed variability is very common these days in cryoEM, and having a way to jointly refine an ensemble of models against a series of maps would be very handy. Cryodrgn, 3D-VA in cryosparc, ManifoldEM, multibody refinement in relion - there are many tools now for generating a series of density maps potentially corresponding to conformational modes, so having the capacity in phenix to refine models against each map would be very helpful. Cheers Oli Message: 1 Date: Wed, 12 Jan 2022 10:36:27 +0100 From: vincent Chaptal mailto:[email protected]> To: Guillaume Gaullier mailto:[email protected]>, Pavel Afonine mailto:[email protected]> Cc: PHENIX user mailing list mailto:[email protected]> Subject: Re: [phenixbb] refinement of an ensemble of structures -> cryoEM variability Message-ID: mailto:[email protected]> Content-Type: text/plain; charset="utf-8"; Format="flowed" Hi Guillaume, thanks for the backup. It's exactly my feeling also. Best Vincent Le 12/01/2022 ? 10:09, Guillaume Gaullier a ?crit?: Hi, I am guessing what we are talking about here are the maps generated by cryoSPARC 3D variability analysis. See: Punjani A & Fleet DJ (2021) 3D Variability Analysis: Resolving continuous flexibility and discrete heterogeneity from single particle cryo-EM.?Journal of Structural Biology: 107702 https://doi.org/10.1016/j.jsb.2021.107702 But this is not the only program that generates series of maps to describe continuous heterogeneity from single-particle cryoEM images, see also cryoDRGN:?Zhong ED, Bepler T, Berger B & Davis JH (2021) CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks.?Nature Methods: 1?10 https://doi.org/10.1038/s41592-020-01049-4 Except some ideally rigid particles like apoferritin, pretty much everything shows some degree of flexibility that generates continuous heterogeneity in cryoEM images. So, my feeling is that a user-friendly program to fit a series of models (ideally, auto-generated from a single starting model) to a map series is probably going to be a standard requirement pretty soon for typical single-particle cryoEM projects. Cheers, Guillaume On 11 Jan 2022, at 17:16, Pavel Afonine wrote: Hi Vincent, this looks like a very specialized task that I've never heard of before! We can add a tool to do that if this becomes something that more than one person does more than once. Meanwhile, a simple script in a language of your?preference (python, linux shell, etc) should do the job. I can help with a script if needed, let me know! Also.. just curious -- what is "3D variability of this map"? Is this one map that is a composition of several map or an ensemble of maps? Pavel On 1/11/22 01:48, vincent Chaptal wrote: Hi Phenix-ers, I thought to ask for something that I believe you have already implemented, but I'm not sure of the best tool to use. I have a cryoEM map where I refine my "high resolution" structure. I also have the 3D variability of this map that shows?several maps varying around the consensus high-res map. I want to refine an ensemble (20) of structures, one for every 20?maps around the consensus map. Is there a tool in phenix to do this? I could refine individually the high-res structure into each map incrementally; since every map differs a little from the?original one, Real-space-refinement could move the structure a little at a time. Then I could combine all the PDBs in an?ensemble? A tool to refine variability would be very useful. Input could be a PDB and an ensemble of maps, and output would be all the?PDBs combined? Thank you. All the best Vincent -- Vincent Chaptal, PhD Director of GdR APPICOM Drug Resistance and Membrane Proteins Lab MMSB -UMR5086 7 passage du Vercors 69007 LYON FRANCE +33 4 37 65 29 01 http://www.appicom.cnrs.fr http://mmsb.cnrs.fr/en/ _______________________________________________ phenixbb mailing list [email protected] http://phenix-online.org/mailman/listinfo/phenixbb Unsubscribe: [email protected] _______________________________________________ phenixbb mailing list [email protected] http://phenix-online.org/mailman/listinfo/phenixbb Unsubscribe: [email protected] Page Title N?r du har kontakt med oss p? Uppsala universitet med e-post s? inneb?r det att vi behandlar dina personuppgifter. F?r att l?sa mer om hur vi g?r det kan du l?sa h?r: http://www.uu.se/om-uu/dataskydd-personuppgifter/ E-mailing Uppsala University means that we will process your personal data. For more information on how this is performed, please read here: http://www.uu.se/en/about-uu/data-protection-policy -- Vincent Chaptal, PhD Director of GdR APPICOM Drug Resistance and Membrane Proteins Lab MMSB -UMR5086 7 passage du Vercors 69007 LYON FRANCE +33 4 37 65 29 01 http://www.appicom.cnrs.fr http://mmsb.cnrs.fr/en/

How is that different from running parallel jobs of n models against n maps?

For this you need to know how to write programs/scripts (I know you do know!). Then make sure programs down the road can handle multi-model files (in Phenix we can read/write them but that's pretty much it). If you have one map and one model (with altlocs) then you can just use phenix.real_space_refine as is. Otherwise yes, you can refine n models against n maps, in parallel or sequentially! Pavel

On 1/13/2022 8:17 AM, Oliver Clarke wrote:

...

Hi,

Just to add my two cents, I agree this would be really useful for a lot of folks. Analysis of continuously distributed variability is very common these days in cryoEM, and having a way to jointly refine an ensemble of models against a series of maps would be very handy. Cryodrgn, 3D-VA in cryosparc, ManifoldEM, multibody refinement in relion - there are many tools now for generating a series of density maps potentially corresponding to conformational modes, so having the capacity in phenix to refine models against each map would be very helpful.

Cheers Oli

...

Message: 1 Date: Wed, 12 Jan 2022 10:36:27 +0100 From: vincent Chaptal To: Guillaume Gaullier ,    Pavel Afonine      Cc: PHENIX user mailing list Subject: Re: [phenixbb] refinement of an ensemble of structures ->     cryoEM variability Message-ID: Content-Type: text/plain; charset="utf-8"; Format="flowed"

Hi Guillaume,

thanks for the backup. It's exactly my feeling also.

Best Vincent

Le 12/01/2022 ? 10:09, Guillaume Gaullier a ?crit?:

...

Hi,

I am guessing what we are talking about here are the maps generated by cryoSPARC 3D variability analysis. See: Punjani A & Fleet DJ (2021) 3D Variability Analysis: Resolving continuous flexibility and discrete heterogeneity from single particle cryo-EM.?Journal of Structural Biology: 107702 https://doi.org/10.1016/j.jsb.2021.107702

But this is not the only program that generates series of maps to describe continuous heterogeneity from single-particle cryoEM images, see also cryoDRGN:?Zhong ED, Bepler T, Berger B & Davis JH (2021) CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks.?Nature Methods: 1?10 https://doi.org/10.1038/s41592-020-01049-4

Except some ideally rigid particles like apoferritin, pretty much everything shows some degree of flexibility that generates continuous heterogeneity in cryoEM images. So, my feeling is that a user-friendly program to fit a series of models (ideally, auto-generated from a single starting model) to a map series is probably going to be a standard requirement pretty soon for typical single-particle cryoEM projects.

Cheers,

Guillaume

...

On 11 Jan 2022, at 17:16, Pavel Afonine wrote:

Hi Vincent,

this looks like a very specialized task that I've never heard of before! We can add a tool to do that if this becomes something that more than one person does more than once. Meanwhile, a simple script in a language of your?preference (python, linux shell, etc) should do the job. I can help with a script if needed, let me know!

Also.. just curious -- what is "3D variability of this map"? Is this one map that is a composition of several map or an ensemble of maps?

Pavel

On 1/11/22 01:48, vincent Chaptal wrote:

...

Hi Phenix-ers,

I thought to ask for something that I believe you have already implemented, but I'm not sure of the best tool to use.

I have a cryoEM map where I refine my "high resolution" structure. I also have the 3D variability of this map that shows?several maps varying around the consensus high-res map. I want to refine an ensemble (20) of structures, one for every 20?maps around the consensus map. Is there a tool in phenix to do this?

I could refine individually the high-res structure into each map incrementally; since every map differs a little from the?original one, Real-space-refinement could move the structure a little at a time. Then I could combine all the PDBs in an?ensemble? A tool to refine variability would be very useful. Input could be a PDB and an ensemble of maps, and output would be all the?PDBs combined?

Thank you.

All the best Vincent

-- Vincent Chaptal, PhD Director of GdR APPICOM Drug Resistance and Membrane Proteins Lab

MMSB -UMR5086 7 passage du Vercors 69007 LYON FRANCE +33 4 37 65 29 01 http://www.appicom.cnrs.fr http://mmsb.cnrs.fr/en/

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E-mailing Uppsala University means that we will process your personal data. For more information on how this is performed, please read here: http://www.uu.se/en/about-uu/data-protection-policy --

Vincent Chaptal, PhD

Director of GdR APPICOM

Drug Resistance and Membrane Proteins Lab

MMSB -UMR5086

7 passage du Vercors

69007 LYON

FRANCE

+33 4 37 65 29 01

http://www.appicom.cnrs.fr

http://mmsb.cnrs.fr/en/