Hi Jim,
As Elaine says, ChimeraX is using ColabFold, which is an optimized version of AlphaFold. So you should cite ColabFold (and AlphaFold and ChimeraX).
Also your description of the template use is a bit misleading. First of all, AlphaFold only uses at most 4 PDB templates per chain. The templates you saw in the JSON file came from ColabFold. It is confusing, because AlphaFold will find up to 20 templates per chain, but then it only uses the 4 best scoring. I think that is always the first 4 of the 20. These details are from reading the AlphaFold code on GitHub. Unfortunately the actual workings of AlphaFold are poorly described in the AlphaFold publications. For instance, you will also see in the code that any template with more than 95% sequence identity is not used. That seems wrong, since you would of course want to use the best sequence matches, but I think it is a hold-over from the code that trained AlphaFold where they didn't want exact template matches. This is typical of AlphaFold code, it is shoddy work where DeepMind seemed mostly interested in showing off machine learning, with little concern for actually producing the best biology results. One last comment about the AlphaFold use of templates. In almost all cases AlphaFold more or less ignores the templates. In other words, it produces nearly the same structure whether it uses templates or not. From hundreds of runs on different sequences my experience has been that if AlphaFold gives a high confidence prediction (say mostly plddt > 80), then even if it uses an experimental structure as a template that differs, it will always prefer its predicted conformation over the experimental structure template. So only in cases where AlphaFold is not confident of its prediction will templates possibly help. Basically the template just is a starting structure, and if AlphaFold is at all confident in another conformation it converges to that other conformation and that template makes no difference.
Tom
ChimeraX AlphaFold developer
> On May 9, 2023, at 2:06 PM, Elaine Meng via ChimeraX-users <chimerax-users@cgl.ucsf.edu> wrote:
>
> Hi Jim,
> We (ChimeraX developers) are not the AlphaFold developers and I personally haven't looked at the details of any of its output files, nor am I an expert on your particular protein of interest. So although your inference sounds reasonable, I can't say anything authoritative about it.
>
> ....except that you should say that the calculation is actually done with ColabFold, as mentioned in the documentation:
> <https://rbvi.ucsf.edu/chimerax/docs/user/tools/alphafold.html>
>
> Maybe a careful reading of the AlphaFold and ColabFold papers would help to confirm the rest of your description.
>
> Best,
> Elaine
> -----
> Elaine C. Meng, Ph.D.
> UCSF Chimera(X) team
> Department of Pharmaceutical Chemistry
> University of California, San Francisco
>
>
>> On May 9, 2023, at 1:38 PM, James Raymond via ChimeraX-users <chimerax-users@cgl.ucsf.edu> wrote:
>>
>> Hi Elaine,
>> I am writing up some results. Would you please see if I am describing our method correctly?
>> Our protein has 2 domains, one whose structure is well known and for which many PDBs are available, and another that is novel.
>> The PDB IDs below came from your file entitled af512_template_domain_names.json
>>
>> "Protein structure was predicted with AlphaFold2 (Jumper et al., 2021) as implemented by UCSF ChimeraX v. 1.6rc (Pettersen et al., 2021) with the option to use PDB templates. In practice, this meant that the N-terminal DUF3494 domain of the protein was predicted based on several existing PDB structures (7bwy_A, 7bwx_A, 3uyu_A, 6a8k_A, 3wp9_A, 4nu3_A, 4nu3_B, 6bg8_B, 4nu2_A, 3vn3_A, 6eio_A, 4nuh_A, 7dc5_B, 5uyt_A, 5uyt_B, 5uyt_A, 5uyt_B) and the C-terminal domain was predicted de novo by AlphaFold."
>>
>> Is it OK?
>>
>> thank you
>> Jim
>
>
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