Crystallographic modelling of protein loops and their heterogeneity with Rappertk

TL;DR

This paper presents Rappertk, a tool for automated, accurate protein loop modeling and heterogeneity estimation, improving refinement processes and capturing structural variability in crystallography.

Contribution

It introduces efficient loop sampling procedures in Rappertk and demonstrates its effectiveness in both single conformer modeling and heterogeneity analysis.

Findings

Rappertk produces better Rfree scores than CNS alone.

Loop modeling is accurate with few restraints.

The method estimates structural heterogeneity effectively.

Abstract

Background. All-atom crystallographic refinement of proteins is a laborious manually driven procedure, as a result of which, alternative and multiconformer interpretations are not routinely investigated. Results. We describe efficient loop sampling procedures in Rappertk and demonstrate that single loops in proteins can be automatically and accurately modelled with few positional restraints. Loops constructed with a composite CNS/Rappertk protocol consistently have better Rfree than those with CNS alone. This approach is extended to a more realistic scenario where there are often large positional uncertainties in loops along with small imperfections in the secondary structural framework. Both ensemble and collection methods are used to estimate the structural heterogeneity of loop regions. Conclusion. Apart from benchmarking Rappertk for the all-atom protein refinement task, this work also demonstrates its utility in both aspects of loop modelling - building a single conformer and estimating structural heterogeneity the loops can exhibit.