Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen
You raised a very good question: why we are asking this question now? Maybe the answer is somewhere on the fact that Alphafold is a “revolution” in the prediction field (borrow the term from resolution revolution in cryo-EM). Anyway, when reading all these discussions, it made me think how I came to US to learn how to solve a structure. My Master training is more like bioinformatics. My second paper has a component of structural homology modeling after sequencing some Rice genes. The paper was rejected by the reviewers asking how I could proof my structural modeling (prediction) was correct. At that time, I decided to learn how to solve the structure to proof my prediction is correct. Now, it is interesting to see now the question is on the other side. River From: CCP4 bulletin board On Behalf Of Quyen Hoang Sent: Sunday, April 2, 2023 10:20 AM To: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen EXTERNAL EMAIL: This e-mail is from a sender outside of the UTEP system. Do not click any links or open any attachments unless you trust the sender and know the content is safe. Please forward suspicious emails to secur...@utep.edu<mailto:secur...@utep.edu> or call 915.747.6324 Thank you for having this conversion. I have heard this question more than once (why is experimental determination needed when there is Alphafold) at grant study sections. Some came from structural biologists, so hopefully, the discussion here would help them also. Computational modeling had existed for decades before Alphafold, and no one ever questioned then, as far as I am aware, the need for experimental determination of the modeled structures regardless of how accurate the predicted models may have been (for example an MD state of a point mutation using a high-resolution X-ray model as a starting model), so I am confused as to why we are asking this question now. In my view, predicted model, as good as it may be, is still a prediction. Cheers, Quyen Quyen Hoang, PhD Associate Professor Department of Biochemistry and Molecular Biology Adjunct Associate Professor of Neurology Principal Investigator of the Stark Neurosciences Research Institute Indiana University School of Medicine 635 Barnhill Drive Medical Sciences Building, room MS0013C Indianapolis, IN 46202 317-274-4371 On Apr 2, 2023, at 10:52 AM, Eugene Valkov mailto:eugene.val...@gmail.com>> wrote: It depends on the problem under investigation. For example, if you propose to perform drug discovery with membrane proteins in a lipid/detergent environment or study the structural organization of large ribonucleoprotein assemblies, then AlphaFold will be of limited value and you should point this out in the rebuttal. If one of your aims is to study a protein, divide it into pieces, and solve structures of domains, then this is justifiably questioned by reviewers in light of the information provided by structure prediction. Perhaps in the reviewer's opinion, there is no need to use substantial funds and time to solve that structure. A more competitive proposal may then re-focus on requesting resources for using the structural hypotheses to probe the mechanism with more ambitious experimental structural aims or to take a deeper dive into the function. As Darwin said, it is not the strongest or the fastest (or even the most intellectual!) that survives. On Sun, 2 Apr 2023 at 11:28, Srivastava, Dhiraj mailto:dhiraj-srivast...@uiowa.edu>> wrote: That’s the point. All these predictions can not replace experiments and they should be used only in the absence of experimental structures, that too with caution. A biophysicist and structural biologist understand this but most of the non-experts (including the reviewers of the grants from non-structural biology study sections) don’t understand this and think that with alphafold, there is no need for experimentally determined structures. That’s more damaging than helpful. From: CCP4 bulletin board mailto:CCP4BB@JISCMAIL.AC.UK>> on behalf of Eugene Valkov mailto:eugene.val...@gmail.com>> Sent: Sunday, April 2, 2023 10:10 AM To: CCP4BB@JISCMAIL.AC.UK<mailto:CCP4BB@JISCMAIL.AC.UK> mailto:CCP4BB@JISCMAIL.AC.UK>> Subject: Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen Predicted structures lack the precision and accuracy of experimentally-determined structures at high resolution with all the benefits of unbiased co-discovery of solvent molecules, ions, ligands, etc., bound to molecules of interest. It is also true that AI-assisted structure prediction can be stunningly accurate to the level of correctly identifying interfacing residues between interacting proteins and accurately recapitulating the architectures of large, multi-domain complexes. AI-assisted structure prediction is immensely liberating in l
Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen
Thank you for having this conversion. I have heard this question more than once (why is experimental determination needed when there is Alphafold) at grant study sections. Some came from structural biologists, so hopefully, the discussion here would help them also. Computational modeling had existed for decades before Alphafold, and no one ever questioned then, as far as I am aware, the need for experimental determination of the modeled structures regardless of how accurate the predicted models may have been (for example an MD state of a point mutation using a high-resolution X-ray model as a starting model), so I am confused as to why we are asking this question now. In my view, predicted model, as good as it may be, is still a prediction. Cheers,QuyenQuyen Hoang, PhDAssociate Professor Department of Biochemistry and Molecular Biology Adjunct Associate Professor of NeurologyPrincipal Investigator of the Stark Neurosciences Research InstituteIndiana University School of Medicine635 Barnhill DriveMedical Sciences Building, room MS0013CIndianapolis, IN 46202317-274-4371On Apr 2, 2023, at 10:52 AM, Eugene Valkov wrote:It depends on the problem under investigation. For example, if you propose to perform drug discovery with membrane proteins in a lipid/detergent environment or study the structural organization of large ribonucleoprotein assemblies, then AlphaFold will be of limited value and you should point this out in the rebuttal.If one of your aims is to study a protein, divide it into pieces, and solve structures of domains, then this is justifiably questioned by reviewers in light of the information provided by structure prediction. Perhaps in the reviewer's opinion, there is no need to use substantial funds and time to solve that structure. A more competitive proposal may then re-focus on requesting resources for using the structural hypotheses to probe the mechanism with more ambitious experimental structural aims or to take a deeper dive into the function.As Darwin said, it is not the strongest or the fastest (or even the most intellectual!) that survives.On Sun, 2 Apr 2023 at 11:28, Srivastava, Dhiraj <dhiraj-srivast...@uiowa.edu> wrote: That’s the point. All these predictions can not replace experiments and they should be used only in the absence of experimental structures, that too with caution. A biophysicist and structural biologist understand this but most of the non-experts (including the reviewers of the grants from non-structural biology study sections) don’t understand this and think that with alphafold, there is no need for experimentally determined structures. That’s more damaging than helpful. From: CCP4 bulletin board <CCP4BB@JISCMAIL.AC.UK> on behalf of Eugene Valkov <eugene.val...@gmail.com> Sent: Sunday, April 2, 2023 10:10 AM To: CCP4BB@JISCMAIL.AC.UK <CCP4BB@JISCMAIL.AC.UK> Subject: Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen Predicted structures lack the precision and accuracy of experimentally-determined structures at high resolution with all the benefits of unbiased co-discovery of solvent molecules, ions, ligands, etc., bound to molecules of interest. It is also true that AI-assisted structure prediction can be stunningly accurate to the level of correctly identifying interfacing residues between interacting proteins and accurately recapitulating the architectures of large, multi-domain complexes. AI-assisted structure prediction is immensely liberating in lowering the threshold to generate testable hypotheses for those lacking access to experimental structural biology resources. AlphaFold and related structure prediction tools are here to stay, and no magic incantations in funding proposals will likely make them disappear. So rather than wring our hands as a community and mourning the loss of ‘divide-and-conquer’ structural biology, which was a rich vein to mine over the last decades, we should adapt to structure prediction and normalize its use, with proper controls and caveats, as part of our arsenal of tools and methods to focus on the questions under investigation. With best wishes, Eugene Eugene Valkov, D.Phil. Stadtman Investigator RNA Biology Laboratory Center for Cancer Research National Cancer Institute Frederick MD 21702, USA (301) 846-1823 On Sun, 2 Apr 2023 at 10:44, jacinto.ls <jlopez.sagas...@gmail.com> wrote: I am also not sure whether AlphaFold can address the impact of ions and other cofactors on the fold of many proteins. Best wishes, Jacinto On 2/4/23 16:20, Srivastava, Dhiraj wrote: May be this article is of some help suggesting the need of experimental structures despite excellent alphafold model. https://www.nature.com/articles/s41401-022-00938-y From: CCP4 bulletin board on behalf of Ian Tickle Sent: Sunday, April 2, 2023 8:28 AM To: CCP4BB@JISCMAIL.AC.UK Subject: [External] Re: [ccp4bb] Structure prediction - waiting to happen All, t
Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen
It depends on the problem under investigation. For example, if you propose to perform drug discovery with membrane proteins in a lipid/detergent environment or study the structural organization of large ribonucleoprotein assemblies, then AlphaFold will be of limited value and you should point this out in the rebuttal. If one of your aims is to study a protein, divide it into pieces, and solve structures of domains, then this is justifiably questioned by reviewers in light of the information provided by structure prediction. Perhaps in the reviewer's opinion, there is no need to use substantial funds and time to solve that structure. A more competitive proposal may then re-focus on requesting resources for using the structural hypotheses to probe the mechanism with more ambitious experimental structural aims or to take a deeper dive into the function. As Darwin said, it is not the strongest or the fastest (or even the most intellectual!) that survives. On Sun, 2 Apr 2023 at 11:28, Srivastava, Dhiraj wrote: > That’s the point. All these predictions can not replace experiments and > they should be used only in the absence of experimental structures, that > too with caution. A biophysicist and structural biologist understand this > but most of the non-experts (including the reviewers of the grants from > non-structural biology study sections) don’t understand this and think that > with alphafold, there is no need for experimentally determined structures. > That’s more damaging than helpful. > > > -- > *From:* CCP4 bulletin board on behalf of Eugene > Valkov > *Sent:* Sunday, April 2, 2023 10:10 AM > *To:* CCP4BB@JISCMAIL.AC.UK > *Subject:* Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - > waiting to happen > > > Predicted structures lack the precision and accuracy of > experimentally-determined structures at high resolution with all the > benefits of unbiased co-discovery of solvent molecules, ions, ligands, > etc., bound to molecules of interest. > > It is also true that AI-assisted structure prediction can be stunningly > accurate to the level of correctly identifying interfacing residues between > interacting proteins and accurately recapitulating the architectures of > large, multi-domain complexes. AI-assisted structure prediction is > immensely liberating in lowering the threshold to generate testable > hypotheses for those lacking access to experimental structural biology > resources. > > AlphaFold and related structure prediction tools are here to stay, and no > magic incantations in funding proposals will likely make them disappear. So > rather than wring our hands as a community and mourning the loss of > ‘divide-and-conquer’ structural biology, which was a rich vein to mine over > the last decades, we should adapt to structure prediction and normalize its > use, with proper controls and caveats, as part of our arsenal of tools and > methods to focus on the questions under investigation. > > With best wishes, > > Eugene > > Eugene Valkov, D.Phil. > > Stadtman Investigator > > RNA Biology Laboratory > > Center for Cancer Research > > National Cancer Institute > > Frederick MD 21702, USA > > (301) 846-1823 > > > On Sun, 2 Apr 2023 at 10:44, jacinto.ls wrote: > > I am also not sure whether AlphaFold can address the impact of ions and other > cofactors on the fold of many proteins. > > Best wishes, > Jacinto > > On 2/4/23 16:20, Srivastava, Dhiraj wrote: > > May be this article is of some help suggesting the need of experimental > structures despite excellent alphafold model. > https://www.nature.com/articles/s41401-022-00938-y > > -------------- > *From:* CCP4 bulletin board > on behalf of Ian Tickle > > *Sent:* Sunday, April 2, 2023 8:28 AM > *To:* CCP4BB@JISCMAIL.AC.UK > > *Subject:* [External] Re: [ccp4bb] Structure prediction - waiting to > happen > > > All, the first hurdle will of course be whether the AlphaFold model works > as a MR model, even with the 100% completeness and sequence identity of a > bespoke model. The question is what B factors to use or which disordered > bits to leave out, as that can strongly influence the result (perhaps use > info from a similar structure). If it doesn't work in MR that's a pretty > good indication that it's too far from reality to be useful for looking at > detailed interactions. > > Does anyone know of a systematic investigation of the success rate of > AlphaFold models in MR ? That would be useful ammunition ! > > Cheers > > -- Ian > > > On Sun, 2 Apr 2023 at 11:51, Gerard Bricogne > wrote: > > Dear all, > > I think that quoting general viewpoints and statements, h
Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen
It has been mentioned that predictions might be misleading when it comes
to multi-domain complexes, probably due to the orientation of each
domain relative to the others rather than the fold of each domain
individually.
This is delicate since making a hypothesis based on inaccurate models
can take you to the wrong path, which nobody wants. Going back to the
original post of this thread, then in those cases where the targets are
defined by multi-domain assemblies, experimental determination is
particularly justified.
Jacinto
On 2/4/23 17:10, Eugene Valkov wrote:
Predicted structures lack the precision and accuracy of
experimentally-determined structures at high resolution with all the
benefits of unbiased co-discovery of solvent molecules, ions, ligands,
etc., bound to molecules of interest.
It is also true that AI-assisted structure prediction can be
stunningly accurate to the level of correctly identifying interfacing
residues between interacting proteins and accurately recapitulating
the architectures of large, multi-domain complexes. AI-assisted
structure prediction is immensely liberating in lowering the threshold
to generate testable hypotheses for those lacking access to
experimental structural biology resources.
AlphaFold and related structure prediction tools are here to stay, and
no magic incantations in funding proposals will likely make them
disappear. So rather than wring our hands as a community and mourning
the loss of ‘divide-and-conquer’ structural biology, which was a rich
vein to mine over the last decades, we should adapt to structure
prediction and normalize its use, with proper controls and caveats, as
part of our arsenal of tools and methods to focus on the questions
under investigation.
With best wishes,
Eugene
Eugene Valkov, D.Phil.
Stadtman Investigator
RNA Biology Laboratory
Center for Cancer Research
National Cancer Institute
Frederick MD 21702, USA
(301) 846-1823
On Sun, 2 Apr 2023 at 10:44, jacinto.ls <http://jacinto.ls>
wrote:
I am also not sure whether AlphaFold can address the impact of ions and
other cofactors on the fold of many proteins.
Best wishes,
Jacinto
On 2/4/23 16:20, Srivastava, Dhiraj wrote:
May be this article is of some help suggesting the need of
experimental structures despite excellent alphafold model.
https://www.nature.com/articles/s41401-022-00938-y
*From:* CCP4 bulletin board
<mailto:CCP4BB@JISCMAIL.AC.UK> on behalf of Ian Tickle
<mailto:ianj...@gmail.com>
*Sent:* Sunday, April 2, 2023 8:28 AM
*To:* CCP4BB@JISCMAIL.AC.UK
<mailto:CCP4BB@JISCMAIL.AC.UK>
*Subject:* [External] Re: [ccp4bb] Structure prediction - waiting
to happen
All, the first hurdle will of course be whether the AlphaFold
model works as a MR model, even with the 100% completeness and
sequence identity of a bespoke model. The question is what B
factors to use or which disordered bits to leave out, as that can
strongly influence the result (perhaps use info from a similar
structure). If it doesn't work in MR that's a pretty good
indication that it's too far from reality to be useful for
looking at detailed interactions.
Does anyone know of a systematic investigation of the success
rate of AlphaFold models in MR ? That would be useful ammunition !
Cheers
-- Ian
On Sun, 2 Apr 2023 at 11:51, Gerard Bricogne
wrote:
Dear all,
I think that quoting general viewpoints and statements,
however
knowledgeable and respected their authors may be, will only
exacerbate the
climate of clashing prejudices between two camps and is bound
to sustain a
war of opinions rather than lead to a rational acceptance
that something has
changed. The frustration is that one camp (the AlphaFold
believers) can be
viewed as in effect preventing experiments that could prove
it wrong.
One way to deal with this obstruction would be to
provide, in each
particular case, evidence that the AlphaFold results "do not
cut it" as the
sole provider of 3D information within the project at hand.
This means that
every grant proposal requesting resources towards a
crystallographic
structure solution should document the fact that AlphaFold
predictions have
been performed (or, often, looked up in a database of
pre-cooked results)
but do not provide the accuracy required for the proposed
investigation. If
this step of writing up the "Background" section of the grant
actually
delivers a useful result, then everyone will be happy; and if
it doesn't,
then the case f
Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen
That’s the point. All these predictions can not replace experiments and they should be used only in the absence of experimental structures, that too with caution. A biophysicist and structural biologist understand this but most of the non-experts (including the reviewers of the grants from non-structural biology study sections) don’t understand this and think that with alphafold, there is no need for experimentally determined structures. That’s more damaging than helpful. From: CCP4 bulletin board on behalf of Eugene Valkov Sent: Sunday, April 2, 2023 10:10 AM To: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen Predicted structures lack the precision and accuracy of experimentally-determined structures at high resolution with all the benefits of unbiased co-discovery of solvent molecules, ions, ligands, etc., bound to molecules of interest. It is also true that AI-assisted structure prediction can be stunningly accurate to the level of correctly identifying interfacing residues between interacting proteins and accurately recapitulating the architectures of large, multi-domain complexes. AI-assisted structure prediction is immensely liberating in lowering the threshold to generate testable hypotheses for those lacking access to experimental structural biology resources. AlphaFold and related structure prediction tools are here to stay, and no magic incantations in funding proposals will likely make them disappear. So rather than wring our hands as a community and mourning the loss of ‘divide-and-conquer’ structural biology, which was a rich vein to mine over the last decades, we should adapt to structure prediction and normalize its use, with proper controls and caveats, as part of our arsenal of tools and methods to focus on the questions under investigation. With best wishes, Eugene Eugene Valkov, D.Phil. Stadtman Investigator RNA Biology Laboratory Center for Cancer Research National Cancer Institute Frederick MD 21702, USA (301) 846-1823 On Sun, 2 Apr 2023 at 10:44, jacinto.ls<http://jacinto.ls> mailto:jlopez.sagas...@gmail.com>> wrote: I am also not sure whether AlphaFold can address the impact of ions and other cofactors on the fold of many proteins. Best wishes, Jacinto On 2/4/23 16:20, Srivastava, Dhiraj wrote: May be this article is of some help suggesting the need of experimental structures despite excellent alphafold model. https://www.nature.com/articles/s41401-022-00938-y From: CCP4 bulletin board <mailto:CCP4BB@JISCMAIL.AC.UK> on behalf of Ian Tickle <mailto:ianj...@gmail.com> Sent: Sunday, April 2, 2023 8:28 AM To: CCP4BB@JISCMAIL.AC.UK<mailto:CCP4BB@JISCMAIL.AC.UK> <mailto:CCP4BB@JISCMAIL.AC.UK> Subject: [External] Re: [ccp4bb] Structure prediction - waiting to happen All, the first hurdle will of course be whether the AlphaFold model works as a MR model, even with the 100% completeness and sequence identity of a bespoke model. The question is what B factors to use or which disordered bits to leave out, as that can strongly influence the result (perhaps use info from a similar structure). If it doesn't work in MR that's a pretty good indication that it's too far from reality to be useful for looking at detailed interactions. Does anyone know of a systematic investigation of the success rate of AlphaFold models in MR ? That would be useful ammunition ! Cheers -- Ian On Sun, 2 Apr 2023 at 11:51, Gerard Bricogne mailto:g...@globalphasing.com>> wrote: Dear all, I think that quoting general viewpoints and statements, however knowledgeable and respected their authors may be, will only exacerbate the climate of clashing prejudices between two camps and is bound to sustain a war of opinions rather than lead to a rational acceptance that something has changed. The frustration is that one camp (the AlphaFold believers) can be viewed as in effect preventing experiments that could prove it wrong. One way to deal with this obstruction would be to provide, in each particular case, evidence that the AlphaFold results "do not cut it" as the sole provider of 3D information within the project at hand. This means that every grant proposal requesting resources towards a crystallographic structure solution should document the fact that AlphaFold predictions have been performed (or, often, looked up in a database of pre-cooked results) but do not provide the accuracy required for the proposed investigation. If this step of writing up the "Background" section of the grant actually delivers a useful result, then everyone will be happy; and if it doesn't, then the case for the need to allocate resources to solving the structure by crystallography will be unassailable. In this way, AlphaFold will be a game changer (we have known that since July 202
Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen
Predicted structures lack the precision and accuracy of experimentally-determined structures at high resolution with all the benefits of unbiased co-discovery of solvent molecules, ions, ligands, etc., bound to molecules of interest. It is also true that AI-assisted structure prediction can be stunningly accurate to the level of correctly identifying interfacing residues between interacting proteins and accurately recapitulating the architectures of large, multi-domain complexes. AI-assisted structure prediction is immensely liberating in lowering the threshold to generate testable hypotheses for those lacking access to experimental structural biology resources. AlphaFold and related structure prediction tools are here to stay, and no magic incantations in funding proposals will likely make them disappear. So rather than wring our hands as a community and mourning the loss of ‘divide-and-conquer’ structural biology, which was a rich vein to mine over the last decades, we should adapt to structure prediction and normalize its use, with proper controls and caveats, as part of our arsenal of tools and methods to focus on the questions under investigation. With best wishes, Eugene Eugene Valkov, D.Phil. Stadtman Investigator RNA Biology Laboratory Center for Cancer Research National Cancer Institute Frederick MD 21702, USA (301) 846-1823 On Sun, 2 Apr 2023 at 10:44, jacinto.ls wrote: > I am also not sure whether AlphaFold can address the impact of ions and other > cofactors on the fold of many proteins. > > Best wishes, > Jacinto > > On 2/4/23 16:20, Srivastava, Dhiraj wrote: > > May be this article is of some help suggesting the need of experimental > structures despite excellent alphafold model. > https://www.nature.com/articles/s41401-022-00938-y > > -- > *From:* CCP4 bulletin board > on behalf of Ian Tickle > > *Sent:* Sunday, April 2, 2023 8:28 AM > *To:* CCP4BB@JISCMAIL.AC.UK > > *Subject:* [External] Re: [ccp4bb] Structure prediction - waiting to > happen > > > All, the first hurdle will of course be whether the AlphaFold model works > as a MR model, even with the 100% completeness and sequence identity of a > bespoke model. The question is what B factors to use or which disordered > bits to leave out, as that can strongly influence the result (perhaps use > info from a similar structure). If it doesn't work in MR that's a pretty > good indication that it's too far from reality to be useful for looking at > detailed interactions. > > Does anyone know of a systematic investigation of the success rate of > AlphaFold models in MR ? That would be useful ammunition ! > > Cheers > > -- Ian > > > On Sun, 2 Apr 2023 at 11:51, Gerard Bricogne > wrote: > > Dear all, > > I think that quoting general viewpoints and statements, however > knowledgeable and respected their authors may be, will only exacerbate the > climate of clashing prejudices between two camps and is bound to sustain a > war of opinions rather than lead to a rational acceptance that something > has > changed. The frustration is that one camp (the AlphaFold believers) can be > viewed as in effect preventing experiments that could prove it wrong. > > One way to deal with this obstruction would be to provide, in each > particular case, evidence that the AlphaFold results "do not cut it" as the > sole provider of 3D information within the project at hand. This means that > every grant proposal requesting resources towards a crystallographic > structure solution should document the fact that AlphaFold predictions have > been performed (or, often, looked up in a database of pre-cooked results) > but do not provide the accuracy required for the proposed investigation. If > this step of writing up the "Background" section of the grant actually > delivers a useful result, then everyone will be happy; and if it doesn't, > then the case for the need to allocate resources to solving the structure > by > crystallography will be unassailable. In this way, AlphaFold will be a game > changer (we have known that since July 2021) but not a game killer. Savvas > alluded to a similar approach, but it could be made a formal requirement > acceptable to both proposers and reviewers, who would then both be dealing > with the situation in a scientific rather than dogmatic manner. > > > With best wishes, > > Gerard. > > -- > On Sat, Apr 01, 2023 at 06:54:33PM +, Goldman, Adrian wrote: > > I think this is all true - and I’ve been putting things like this into > my (failing) grants - but I get the dispiriting sense that the medics think > (to borrow a line from hamlet) “the applicant doth protest too much > methinks”. > > >
Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen
I am also not sure whether AlphaFold can address the impact of ions and other cofactors on the fold of many proteins. Best wishes, Jacinto On 2/4/23 16:20, Srivastava, Dhiraj wrote: May be this article is of some help suggesting the need of experimental structures despite excellent alphafold model. https://www.nature.com/articles/s41401-022-00938-y *From:* CCP4 bulletin board on behalf of Ian Tickle *Sent:* Sunday, April 2, 2023 8:28 AM *To:* CCP4BB@JISCMAIL.AC.UK *Subject:* [External] Re: [ccp4bb] Structure prediction - waiting to happen All, the first hurdle will of course be whether the AlphaFold model works as a MR model, even with the 100% completeness and sequence identity of a bespoke model. The question is what B factors to use or which disordered bits to leave out, as that can strongly influence the result (perhaps use info from a similar structure). If it doesn't work in MR that's a pretty good indication that it's too far from reality to be useful for looking at detailed interactions. Does anyone know of a systematic investigation of the success rate of AlphaFold models in MR ? That would be useful ammunition ! Cheers -- Ian On Sun, 2 Apr 2023 at 11:51, Gerard Bricogne wrote: Dear all, I think that quoting general viewpoints and statements, however knowledgeable and respected their authors may be, will only exacerbate the climate of clashing prejudices between two camps and is bound to sustain a war of opinions rather than lead to a rational acceptance that something has changed. The frustration is that one camp (the AlphaFold believers) can be viewed as in effect preventing experiments that could prove it wrong. One way to deal with this obstruction would be to provide, in each particular case, evidence that the AlphaFold results "do not cut it" as the sole provider of 3D information within the project at hand. This means that every grant proposal requesting resources towards a crystallographic structure solution should document the fact that AlphaFold predictions have been performed (or, often, looked up in a database of pre-cooked results) but do not provide the accuracy required for the proposed investigation. If this step of writing up the "Background" section of the grant actually delivers a useful result, then everyone will be happy; and if it doesn't, then the case for the need to allocate resources to solving the structure by crystallography will be unassailable. In this way, AlphaFold will be a game changer (we have known that since July 2021) but not a game killer. Savvas alluded to a similar approach, but it could be made a formal requirement acceptable to both proposers and reviewers, who would then both be dealing with the situation in a scientific rather than dogmatic manner. With best wishes, Gerard. -- On Sat, Apr 01, 2023 at 06:54:33PM +, Goldman, Adrian wrote: > I think this is all true - and I’ve been putting things like this into my (failing) grants - but I get the dispiriting sense that the medics think (to borrow a line from hamlet) “the applicant doth protest too much methinks”. > > Well if as per James H today ;), we deposit coordinates to 1sf, alphafold will be just fine. > > Of course the coordinates won’t be of any use to anybody, but the pictures will be nice. > > Adrian > > Sent from my iPhone > > > On 1 Apr 2023, at 21:39, Randy John Read wrote: > > > > There’s also this preprint with Tom Terwilliger as lead author: https://www.biorxiv.org/content/10.1101/2022.11.21.517405v1. The title is “AlphaFold predictions: great hypotheses but no match for experiment”. > > > > Best wishes, > > > > Randy > > > >> On 1 Apr 2023, at 18:18, Savvas Savvides <9d24f7f13e09-dmarc-requ...@jiscmail.ac.uk> wrote: > >> > >> Dear Rams, > >> > >> I salute you for sharing this. > >> > >> Just a week ago, I also received a remark along these lines on a declined grant application. The remark was the only unfavourable point, which suggested that it must have weighed disproportionally towards the negative outcome. This was a two-stage evaluation process and the grant was cut in stage-1 where it was evaluated by a small group of evaluators, none of whom was a structural biologist/biochemist. Stage-2 would have involved peer review by international experts. > >> > >> Despite my initial disbelief about what this remark might
Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen
May be this article is of some help suggesting the need of experimental structures despite excellent alphafold model. https://www.nature.com/articles/s41401-022-00938-y From: CCP4 bulletin board on behalf of Ian Tickle Sent: Sunday, April 2, 2023 8:28 AM To: CCP4BB@JISCMAIL.AC.UK Subject: [External] Re: [ccp4bb] Structure prediction - waiting to happen All, the first hurdle will of course be whether the AlphaFold model works as a MR model, even with the 100% completeness and sequence identity of a bespoke model. The question is what B factors to use or which disordered bits to leave out, as that can strongly influence the result (perhaps use info from a similar structure). If it doesn't work in MR that's a pretty good indication that it's too far from reality to be useful for looking at detailed interactions. Does anyone know of a systematic investigation of the success rate of AlphaFold models in MR ? That would be useful ammunition ! Cheers -- Ian On Sun, 2 Apr 2023 at 11:51, Gerard Bricogne mailto:g...@globalphasing.com>> wrote: Dear all, I think that quoting general viewpoints and statements, however knowledgeable and respected their authors may be, will only exacerbate the climate of clashing prejudices between two camps and is bound to sustain a war of opinions rather than lead to a rational acceptance that something has changed. The frustration is that one camp (the AlphaFold believers) can be viewed as in effect preventing experiments that could prove it wrong. One way to deal with this obstruction would be to provide, in each particular case, evidence that the AlphaFold results "do not cut it" as the sole provider of 3D information within the project at hand. This means that every grant proposal requesting resources towards a crystallographic structure solution should document the fact that AlphaFold predictions have been performed (or, often, looked up in a database of pre-cooked results) but do not provide the accuracy required for the proposed investigation. If this step of writing up the "Background" section of the grant actually delivers a useful result, then everyone will be happy; and if it doesn't, then the case for the need to allocate resources to solving the structure by crystallography will be unassailable. In this way, AlphaFold will be a game changer (we have known that since July 2021) but not a game killer. Savvas alluded to a similar approach, but it could be made a formal requirement acceptable to both proposers and reviewers, who would then both be dealing with the situation in a scientific rather than dogmatic manner. With best wishes, Gerard. -- On Sat, Apr 01, 2023 at 06:54:33PM +, Goldman, Adrian wrote: > I think this is all true - and I’ve been putting things like this into my > (failing) grants - but I get the dispiriting sense that the medics think (to > borrow a line from hamlet) “the applicant doth protest too much methinks”. > > Well if as per James H today ;), we deposit coordinates to 1sf, alphafold > will be just fine. > > Of course the coordinates won’t be of any use to anybody, but the pictures > will be nice. > > Adrian > > Sent from my iPhone > > > On 1 Apr 2023, at 21:39, Randy John Read > > mailto:rj...@cam.ac.uk>> wrote: > > > > There’s also this preprint with Tom Terwilliger as lead author: > > https://www.biorxiv.org/content/10.1101/2022.11.21.517405v1. The title is > > “AlphaFold predictions: great hypotheses but no match for experiment”. > > > > Best wishes, > > > > Randy > > > >> On 1 Apr 2023, at 18:18, Savvas Savvides > >> <9d24f7f13e09-dmarc-requ...@jiscmail.ac.uk<mailto:9d24f7f13e09-dmarc-requ...@jiscmail.ac.uk>> > >> wrote: > >> > >> Dear Rams, > >> > >> I salute you for sharing this. > >> > >> Just a week ago, I also received a remark along these lines on a declined > >> grant application. The remark was the only unfavourable point, which > >> suggested that it must have weighed disproportionally towards the negative > >> outcome. This was a two-stage evaluation process and the grant was cut in > >> stage-1 where it was evaluated by a small group of evaluators, none of > >> whom was a structural biologist/biochemist. Stage-2 would have involved > >> peer review by international experts. > >> > >> Despite my initial disbelief about what this remark might have caused and > >> upon reflection, I realized that it might be time to become proactive in > >> future applications in anticipation of the apparent growing trend towards > >> such remarks and perceptions. > >> > >> I think that a gener
Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen
No offense to anyone but most of these systematic studies are often on small not so flexible, single domain, easy to crystallize proteins with little conformational variability and that’s where alpha fold excel. It fails with (may not be all though) multidomain proteins with conformational variability, and most of the systematic studies often exclude these tricky cases. From: CCP4 bulletin board on behalf of Ian Tickle Sent: Sunday, April 2, 2023 8:28 AM To: CCP4BB@JISCMAIL.AC.UK Subject: [External] Re: [ccp4bb] Structure prediction - waiting to happen All, the first hurdle will of course be whether the AlphaFold model works as a MR model, even with the 100% completeness and sequence identity of a bespoke model. The question is what B factors to use or which disordered bits to leave out, as that can strongly influence the result (perhaps use info from a similar structure). If it doesn't work in MR that's a pretty good indication that it's too far from reality to be useful for looking at detailed interactions. Does anyone know of a systematic investigation of the success rate of AlphaFold models in MR ? That would be useful ammunition ! Cheers -- Ian On Sun, 2 Apr 2023 at 11:51, Gerard Bricogne mailto:g...@globalphasing.com>> wrote: Dear all, I think that quoting general viewpoints and statements, however knowledgeable and respected their authors may be, will only exacerbate the climate of clashing prejudices between two camps and is bound to sustain a war of opinions rather than lead to a rational acceptance that something has changed. The frustration is that one camp (the AlphaFold believers) can be viewed as in effect preventing experiments that could prove it wrong. One way to deal with this obstruction would be to provide, in each particular case, evidence that the AlphaFold results "do not cut it" as the sole provider of 3D information within the project at hand. This means that every grant proposal requesting resources towards a crystallographic structure solution should document the fact that AlphaFold predictions have been performed (or, often, looked up in a database of pre-cooked results) but do not provide the accuracy required for the proposed investigation. If this step of writing up the "Background" section of the grant actually delivers a useful result, then everyone will be happy; and if it doesn't, then the case for the need to allocate resources to solving the structure by crystallography will be unassailable. In this way, AlphaFold will be a game changer (we have known that since July 2021) but not a game killer. Savvas alluded to a similar approach, but it could be made a formal requirement acceptable to both proposers and reviewers, who would then both be dealing with the situation in a scientific rather than dogmatic manner. With best wishes, Gerard. -- On Sat, Apr 01, 2023 at 06:54:33PM +, Goldman, Adrian wrote: > I think this is all true - and I’ve been putting things like this into my > (failing) grants - but I get the dispiriting sense that the medics think (to > borrow a line from hamlet) “the applicant doth protest too much methinks”. > > Well if as per James H today ;), we deposit coordinates to 1sf, alphafold > will be just fine. > > Of course the coordinates won’t be of any use to anybody, but the pictures > will be nice. > > Adrian > > Sent from my iPhone > > > On 1 Apr 2023, at 21:39, Randy John Read > > mailto:rj...@cam.ac.uk>> wrote: > > > > There’s also this preprint with Tom Terwilliger as lead author: > > https://www.biorxiv.org/content/10.1101/2022.11.21.517405v1. The title is > > “AlphaFold predictions: great hypotheses but no match for experiment”. > > > > Best wishes, > > > > Randy > > > >> On 1 Apr 2023, at 18:18, Savvas Savvides > >> <9d24f7f13e09-dmarc-requ...@jiscmail.ac.uk<mailto:9d24f7f13e09-dmarc-requ...@jiscmail.ac.uk>> > >> wrote: > >> > >> Dear Rams, > >> > >> I salute you for sharing this. > >> > >> Just a week ago, I also received a remark along these lines on a declined > >> grant application. The remark was the only unfavourable point, which > >> suggested that it must have weighed disproportionally towards the negative > >> outcome. This was a two-stage evaluation process and the grant was cut in > >> stage-1 where it was evaluated by a small group of evaluators, none of > >> whom was a structural biologist/biochemist. Stage-2 would have involved > >> peer review by international experts. > >> > >> Despite my initial disbelief about what this remark might have caused and > >> upon reflection, I realized that it might be t
Re: [ccp4bb] [External] Re: [ccp4bb] Structure prediction - waiting to happen
When I tested alpha fold on some of my proteins, it failed to predict the intramolecular interactions needed for their functions. Alphafold predicts the folds and overall structure of single domain and may be simple multi domain proteins but when conformational changes are needed for protein function, it fails to predict that. At-least it was the situation with some of my proteins. May be if somehow biochemical constraints are applied, it may predict the structure but you can not rely on alphafold to understand molecular mechanism of protein function. It’s too premature to think that alphafold can replace the need for experimental data. Dhiraj From: CCP4 bulletin board on behalf of Ian Tickle Sent: Saturday, April 1, 2023 9:46 AM To: CCP4BB@JISCMAIL.AC.UK Subject: [External] Re: [ccp4bb] Structure prediction - waiting to happen Hi Ramaswamy I assume this is an April Fool's but it's still a serious question because many reviewers who are not crystallographers or electron microscopists may not fully appreciate the difference currently between the precision of structures obtained by experimental and predictive methods, though the latter are certainly catching up. The answer of course lies in the mean co-ordinate precision, related to the map resolution. Quoting https://people.cryst.bbk.ac.uk/~ubcg05m/precgrant.html : "The accuracy and precision required of an experimentally determined model of a macromolecule depends on the biological questions being asked of the structure. Questions involving the overall fold of a protein, or its topological similarity to other proteins, can be answered by structures of fairly low precision such as those obtained from very low resolution X-ray crystal diffraction data [or AlphaFold]. Questions involving reaction mechanisms require much greater accuracy and precision as obtained from well-refined, high-resolution X-ray structures, including proper statistical analyses of the standard uncertainties (s.u.'s) of atomic positions and bond lengths.". According to https://www.nature.com/articles/s41586-021-03819-2 : The accuracy of AlphaFold structures at the time of writing (2021) was around 1.0 Ang. RMSD for main-chain and 1.5 Ang. RMSD for side-chain atoms and probably hasn't changed much since. This is described as "highly accurate"; however this only means that AlphaFold's accuracy is much higher in comparison with other prediction methods, not in comparison with experimental methods. Also note that AlphaFold's accuracy is estimated by comparison with the X-ray structure which remains the "gold standard"; there's no way (AFAIK) of independently assessing AlphaFold's accuracy or precision. Quoting https://scripts.iucr.org/cgi-bin/paper?S0907444998012645 : "Data of 0.94 A resolution for the 237-residue protein concanavalin A are used in unrestrained and restrained full-matrix inversions to provide standard uncertainties sigma(r) for positions and sigma(l) for bond lengths. sigma(r) is as small as 0.01 A for atoms with low Debye B values but increases strongly with B." There's a yawning gap between 1.0 - 1.5 Ang. and 0.01 Ang.! Perhaps AlphaFold structures should be deposited using James Holton's new PDB format (now that is an April Fool's !). One final suggestion for a reference in your grant application: https://www.biorxiv.org/content/10.1101/2022.03.08.483439v2 . Cheers -- Ian On Sat, 1 Apr 2023 at 13:06, Subramanian, Ramaswamy mailto:subra...@purdue.edu>> wrote: Dear All, I am unsure if all other groups will get it - but I am sure this group will understand the frustration. My NIH grant did not get funded. A few genuine comments - they make excellent sense. We will fix that. One major comment is, “Structures can be predicted by alpfafold and other software accurately, so the effort put on the grant to get structures by X-ray crystallography/cryo-EM is not justified.” The problem is when a company with billions of $$s develops a method and blasts it everywhere - the message is so pervasive… Question: Is there a canned consensus paragraph that one can add with references to grants with structural biology (especially if the review group is not a structural biology group) to say why the most modern structure prediction programs are not a substitute for structural work? Thanks. Rams subra...@purdue.edu<mailto:subra...@purdue.edu> To unsubscribe from the CCP4BB list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1 To unsubscribe from the CCP4BB list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1 To unsubscribe from the CCP4BB list, click the following link: https://www.jiscmail.ac.
