Molecular-replacement phasing using predicted protein structures from AWSEM-Suite

Abstract

The phase problem in X-ray crystallography arises from the fact that only the intensities, and not the phases, of the diffracting electromagnetic waves are measured directly. Molecular replacement can often estimate the relative phases of reflections starting with those derived from a template structure, which is usually a previously solved structure of a similar protein. The key factor in the success of molecular replacement is finding a good template structure. When no good solved template exists, predicted structures based partially on templates can sometimes be used to generate models for molecular replacement, thereby extending the lower bound of structural and sequence similarity required for successful structure determination. Here, the effectiveness is examined of structures predicted by a state-of-the-art prediction algorithm, the Associative memory, Water-mediated, Structure and Energy Model Suite (AWSEM-Suite), which has been shown to perform well in predicting protein structures in CASP13 when there is no significant sequence similarity to a solved protein or only very low sequence similarity to known templates. The performance of AWSEM-Suite structures in molecular replacement is discussed and the results show that AWSEM-Suite performs well in providing useful phase information, often performing better than I-TASSER-MR and the previous algorithm AWSEM-Template.

Implications of AlphaFold2 for crystallographic phasing by molecular replacement

“…Models from I-TASSER, generated by full-length iterative structural fragment reassembly, have been incorporated in the I-TASSER-MR server, which uses progressive sequence truncation to edit the models for molecular replacement (Wang et al, 2017). AWSEM-Suite combines both homology model templates and coevolutionary information with the physico-chemical energy terms of AWSEM (Jin et al, 2020). In our own collaborations, the phenix.mr_rosetta pipeline (Terwilliger et al, 2012) can use Rosetta to rebuild template structures prior to attempting molecular replacement.…”

Possible Implications of AlphaFold2 for Crystallographic Phasing by Molecular Replacement

“…Models from I-TASSER, generated by full-length iterative structural fragment reassembly, have been incorporated in the I-TASSER-MR server, which uses progressive sequence truncation to edit the models for molecular replacement (Wang et al ., 2017). AWSEM-Suite combines both homology model templates and coevolutionary information with the physico-chemical energy terms of AWSEM (Jin et al ., 2020). In our own collaborations, the phenix.mr_rosetta (Terwilliger et al ., 2012) pipeline can use Rosetta to rebuild template structures prior to attempting molecular replacement.…”

Unleashing the potential of noncanonical amino acid biosynthesis to create cells with precision tyrosine sulfation

“…To explore the contribution of this highly variable region to substrate binding, the structure of Nn SULT1C1 was predicted via Alphafold 2. Alphafold 2 is a machine learning approach that has been shown to predict protein structure with a high degree of accuracy 53 – 56 . More than 90% of the residues in the predicted Nn SULT1C1 structure show Local Distance Difference Test values over 90, indicating they have a significant likelihood of predicting structure with a very high accuracy.…”