Discussion
This paper describes the solution of four experimental structures using molecular replacement with models submitted to CASP14. We also report improvement of an already solved target using models.
Molecular replacement is a very well established technique, but high accuracy models are needed, and until now that has almost always required the availability of templates based on high levels of sequence identity 64. The three most recent CASPs have seen dramatic improvements in the accuracy of non-homologous models, first from the successful application of 3D contact prediction methods using statistical approaches65 and then from the use of deep learning methods13,66. In CASP14, the Alphafold2 group submitted models for many targets that rival the corresponding experimental structures in accuracy10-13. The difficulties in obtaining experimental structures for seven of the CASP14 targets provided an opportunity to objectively test the ability of new methods in this respect. As the accounts in this paper show, the models are indeed powerful.
A post-CASP analysis by Randy Read and colleagues15 found that all CASP14 targets with available diffraction data could be solved or at least partially solved using molecular replacement with Alphafold2 models. The analysis implies that in future, structure modeling should be a viable means of solving all but the most challenging crystal structures with molecular replacement, providing good data are available.