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. Structural biologists have much to offer in the longer-term resolution of the crisis, by providing a molecular-level understanding that can inform the development of new therapies such as drugs or vaccines, as well as a deeper understanding of the biology of the virus and its pathogenic mechanisms.
COVID-19 Open Structures has been set up to coordinate an open science initiative to accelerate progress in this structural understanding of COVID-19. Taking a completely open science approach will ensure that there are no unnecessary delays in the determination of structures related to COVID-19, whether they're from the SARS-CoV-2 virus, interacting host proteins, or complexes. When determining a structure turns out to be difficult, help can come from people with specialised skills in your own field or with other areas of expertise, such as molecular modelling or another method for structure determination.
The CASP (Critical Assessment of Structure Prediction) organisers have launched an initiative to mobilise the structure prediction community to predict and refine 3D structures of COVID-19-related proteins and relevant complexes that either have unknown structure or are non-trivial modelling targets, described at the CASP Commons site. Note that the models are being refined iteratively and 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. The CASP initiative has been taken up with great enthusiasm by the prediction community.
The related CAPRI (Critical Assessment of PRedicted Interactions) community is offering to help in predicting the 3D structures and interaction interfaces of protein complexes and large assemblies (homo- or hetero-complexes), starting from predicted structures of the individual components or structures determined experimentally by X-ray diffraction or cryo-EM (see the CAPRI site ). The community has also developed a wide range of tools, for analysing potential binding interfaces and identifying biologically meaningful association modes.
Solving the phase problem can still be a real bottleneck, when there are no good molecular replacement models and no good sources of experimental phasing. An open science approach will help to escape these bottlenecks in a number of ways. 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. Experts in data analysis may well be able to improve the quality and resolution of diffraction data, starting from the same raw images. Similarly, experts in phasing may have tricks or advanced algorithms allowing them to solve the phase problem from data that were insufficient for routine structure solution. 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.
In spite of the fantastic "resolution revolution" in cryo-EM, some samples are still recalcitrant and fail to yield high-resolution reconstructions. These reconstructions can still be of great value if shared openly with the rest of the scientific community. For instance, reconstructions at 5-10 Å resolution have been used successfully by crystallographers to obtain initial phases for crystals that diffract to higher resolution, allowing bootstrapping to a final atomic model. Such reconstructions could also benefit from interaction with the modelling community: predicted structures could be docked into a reconstruction, providing biological insight into complexes, and structure prediction could be improved by being informed by the constraint of fitting into a reconstruction.
Microsoft Teams has been chosen as the platform to coordinate the effort. It was chosen because it is available, it possesses a sufficient set of features, and we have some familiarity with it. A new Team, UOC_Covid-19 Open Structures , has been established, and the site is ready for new targets. For each new target, a new channel will be created to share insights and results as they emerge.
The most important thing in the current circumstances is to make relevant structural information available as quickly as possible. Eventually, of course, structures that are solved with the participation of people in this open science initiative will be published. It seems sensible to expect that the group that provided the project and the original experimental data would lead any publication, but also that anyone who made an important contribution would be appropriately recognised, most likely as one of the authors. In the spirit of this initiative, it would be great if any manuscripts arising would be made accessible immediately through a preprint server such as bioRxiv.