The Covid-19 crisis is bringing out the best in the communities we belong to, with many people giving deep thought to how we can use our skills to help. On the crystallography bulletin boards we've seen offers to help in solving Covid-19-related structures that prove difficult, offers to help with improving protein stability, suggestions that the deposition of raw diffraction images would allow the community to help get the best possible version of any relevant structure, and requests to share bioinformatics analyses and predictions of what are the most interesting targets.
We're writing to suggest an additional way that the community can help to accelerate progress in the structural understanding of Covid-19. The CASP (Critical Assessment of Structure Prediction) organisers have recently launched an initiative to mobilise the structure prediction community to predict and refine 3D structures of SARS-2-Covid proteins and relevant complexes that either have unknown structure or are non-trivial modelling targets: http://predictioncenter.org/caspcommons/index.cgi. Note that the models will be refined much more extensively than typically done in a normal CASP round, which should make them even better than the impressive results seen in recent years. We would like to build on this initiative, and the enthusiasm this has revealed in the prediction community, to help to accelerate the determination of structures needed for a molecular-level understanding of Covid-19. Structure prediction has reached a level of maturity where predicted ab initio models and distant homology models can be accurate enough to solve new structures by molecular replacement. The best way to bring the prediction and experimental communities together to exploit these developments and accelerate progress is to embrace an open science approach. To that end, we propose the following: * If you have diffraction data involving a SARS-2-Covid protein, a host protein relevant to pathogenesis or a complex, but you are not immediately able to solve the structure, contact the CASP organisers ([email protected]) with the sequence(s) of the construct(s) that went into the crystallisation drop. If relevant predictions have already been made, any unreleased models will be released at this point (along with predictions of local accuracy). If proteins in your crystals are not already modelling targets, the CASP organisers will consider them as potential new targets for the modelling community. * We all want the fastest possible progress on scientific understanding of Covid-19, and this can best be achieved by completely open science. On a number of occasions at crystallographic computing schools and workshops, we have seen extremely difficult structures yield to the combined expertise of a number of developers and "power users" of the software, none of whom knew how to solve every problem that arose. Even before CASP models are available, some other crystallographer may find a way to solve the structure! So it would be ideal if the sequence information you provide to the CASP organisers was accompanied by a DOI or URL pointing at the diffraction data, preferably in the form of raw images as well as integrated data. Data from different crystal forms or poorly isomorphous crystals can also be incredibly valuable. Openness should go both ways, so people who wish to access these data will be asked to agree to immediately release any positive results, even if these fall short of a full structure solution, so that others can build on them. Best wishes, Randy Read (in cooperation with the CASP organisers) ----- Randy J. Read Department of Haematology, University of Cambridge Cambridge Institute for Medical Research Tel: +44 1223 336500 The Keith Peters Building Fax: +44 1223 336827 Hills Road E-mail: [email protected] Cambridge CB2 0XY, U.K. www-structmed.cimr.cam.ac.uk ######################################################################## To unsubscribe from the CCP4BB list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=CCP4BB&A=1
