It seems immensely powerful, but my impression is it shows just how much information can be extrapolated from the PDB if a technique that can make use of "deep similarity" can be employed.
Obviously alphafold2 can make use of relationships that arent limited to direct homology, but if there is a fundamental "cellular context-free" relationship between sequence and structure (I'm sceptical about this) then it must be via the sidechains. If the sidechains predictions are worse than the backbone, and loops are also imperfect, then it strongly suggests that the process is still inferring the structure (albeit in a very clever way that can determine and weight similarities that go far beyond those implied by direct homology) rather than "building" it de novo. Obviously sidechain and loop positions are important when we think about the applications of macro molecular structures, but I'm not qualified to say whether there is actually enough data in the PDB to beat the law of diminishing returns and reliably get trustworthy "experimental quality" predictions, and how that will scale with complex proteins which may be very context dependent in their ability to fold. We probably dont need a universal understanding of sequence/structure to get there, but the claim that this is just a matter of time only really follows on from the assumption of a true de-novo method. Without it, the learning set may need to be bigger than all solved (or even solveable) structures. This could have been framed as something really exciting and complementary to experimental structural biology (trivial MR, much better denovo EM etc..) at a time when multi-disciplinary approaches are producing incredible insights, but the press that has been generated, seems misleading, and I fear this is what the public and funders will base their decisions upon. Just my two cents. Matthew. Get Outlook for Android<https://aka.ms/ghei36> ________________________________ From: CCP4 bulletin board <CCP4BB@JISCMAIL.AC.UK> on behalf of Cedric Govaerts <cedric.govae...@ulb.ac.be> Sent: Wednesday, December 9, 2020 9:37:17 AM To: CCP4BB@JISCMAIL.AC.UK <CCP4BB@JISCMAIL.AC.UK> Subject: Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less pipetting (?) Dear All After about 10 (!) years of (very) hard work we solved the structures of our dearest membrane transporter. Dataset at 2.9 And resolution, fairly anisotropic, experimental phasing, and many looooong nights with Coot and Buster to achieve model refinement. The experimental structure had a well defined ligand nicely coordinated but also a lipid embedded inside the binding cavity (a complete surprise but biologically relevant) and two detergent molecules well defined (experimental/crystallisation artefact). As our paper was accepted basically when CASP organisers were calling for targets I offered my baby to the computing Gods. However we only provided the sequence to CASP, no info regarding any ligand or lipid. Less than a month after, the CASP team contacted us and send us the best model. In fact it was 2 half models as the transporter is a pseudo dimer, with the N-lobe and C-lobe moving relative to each other during transport cycle, thus divided as two domains in CASP. The results were breathtaking. 0.7 And RSMD on one half, 0.6 on the other. And yes, group 427 was the superpower (did not know at the time that it was AlphaFold). We had long discussions with the CASP team, as -for us- this almost exact modelling was dream-like (or science fiction) and -at some point- we were even suspecting fraud, as our coordinates had travelled over the internet a few times around when interacting with colleagues. The organisers reassured us that we were not the only target that had been “nailed” so no reason to suspect any wrongdoing. To this day I am still baffled and I would be happy to hear from the community, maybe from some of the CASP participants. The target is T024, the “perfect" models are domain-split version (T024-D1 and T024-D2), as AlphaFold2 did not perform so well on the complete assembly. Deposited PDB is 6T1Z Cedric PS: I should also note that many other groups performed very well, much better than I would have dreamed, including on the full protein but just not as crazy-good. — Prof. Cedric Govaerts, Ph.D. Universite Libre de Bruxelles Campus Plaine. Phone :+32 2 650 53 77 Building BC, Room 1C4 203 Boulevard du Triomphe, Acces 2 1050 Brussels Belgium http://govaertslab.ulb.ac.be/ ________________________________ To unsubscribe from the CCP4BB list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB&A=1 ######################################################################## To unsubscribe from the CCP4BB list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB&A=1 This message was issued to members of www.jiscmail.ac.uk/CCP4BB, a mailing list hosted by www.jiscmail.ac.uk, terms & conditions are available at https://www.jiscmail.ac.uk/policyandsecurity/
