Hi Serhat, AlphaFold does not provide docking scores or energy minimization scores as far as I know. AlphaFold estimates pTM (predicted TM) and ipTM (interface predicted TM) scores related to prediction accuracy. You might want to google molecule TM score to learn about those. And googling Alphafold iptm gives as the top hit a paper describing those scores Evaluation of AlphaFold-Multimer prediction on multi-chain protein complexes https://academic.oup.com/bioinformatics/article/39/7/btad424/7219714 ChimeraX does not show you those scores but does have ways of visualizing the pLDDT (predicted local distance difference test) and PAE (predicted aligned error) generated by AlphaFold, described here https://www.rbvi.ucsf.edu/chimerax/data/pae-apr2022/pae.html And you may be interested in ChimeraX videos about visualizing AlphaFold confidence https://youtu.be/oxblwn0_PMM https://youtu.be/TMcjEecFHaI and more ChimeraX AlphaFold videos here https://www.rbvi.ucsf.edu/chimerax/docs/videos/ The .pkl (Python pickle) files contain data such as PAE scores. ChimeraX can read pkl file to show the scores as described in the above links. The alphafold issue #629 you reference about AlphaFold inserting jax data structures into .pkl files was long ago fixed in both AlphaFold and ChimeraX 1.5 as described in the link you sent. The solution is of course to update the version of ChimeraX and AlphaFold you are using. If you are using any ChimeraX version to run AlphaFold it is using a current AlphaFold. But ChimeraX AlphaFold runs don't produce .pkl files so I guess you are running an old AlphaFold in a different. Tom
On Dec 11, 2023, at 4:23 AM, serhat inceer <serhatinceer@yahoo.com> wrote:
Dear Tom Goddard
My name is Serhat Inceer Researcher at the University of Vienna department od Molecular Biology, and I am reaching out to seek assistance regarding the interpretation of docking scores and multimer energy minimization scores in AlphaFold.
Additionally, I have questions about running ".pkl" files to analyze plDDt graphs for the predicted and ranked models that I have already predicted models.
Specifically, I am interested in understanding the methodology and significance of the docking score and multimer energy minimization score provided by AlphaFold. Could you please provide more information on how these scores are calculated and what they signify in the context of protein structure prediction?
Furthermore, I have generated ".pkl" files for my predicted models, and I am interested in running them to obtain plDDt graphs. Could you please guide me on the steps to run the ".pkl" files for this purpose? Any documentation or resources that outline the process would be greatly appreciated.
According my research on GitHub you got also same error and I am wondering about how could you fit it this situation
https://github.com/google-deepmind/alphafold/issues/629
Thank you very much for your time and assistance. I look forward to your response.
Best regards,
Serhat Inceer