Homology-based loop modeling yields more complete crystallographic protein structures.

Bart Van Beusekom,Maarten L Hekkelman,Anastassis Perrakis,Robbie P Joosten,Krista Joosten

doi:10.1107/s2052252518010552

Bart Van Beusekom, Maarten L Hekkelman + Show 3 more

Open Access

https://doi.org/10.1107/s2052252518010552

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Abstract

Inherent protein flexibility, poor or low-resolution diffraction data or poorly defined electron-density maps often inhibit the building of complete structural models during X-ray structure determination. However, recent advances in crystallographic refinement and model building often allow completion of previously missing parts. This paper presents algorithms that identify regions missing in a certain model but present in homologous structures in the Protein Data Bank (PDB), and 'graft' these regions of interest. These new regions are refined and validated in a fully automated procedure. Including these developments in the PDB-REDO pipeline has enabled the building of 24 962 missing loops in the PDB. The models and the automated procedures are publicly available through the PDB-REDO databank and webserver. More complete protein structure models enable a higher quality public archive but also a better understanding of protein function, better comparison between homologous structures and more complete data mining in structural bioinformatics projects.

Highlights

Protein structure models give direct and detailed insights into biochemistry (Lamb et al, 2015) and are highly relevant to many areas of biology and biotechnology (Terwilliger & Bricogne, 2014)
Crystallography has been the leading technique in determining protein structure models (Berman et al, 2014) and to date, over 120 000 crystallographic structure models are available from the Protein Data Bank (PDB; Burley et al, 2017)
When Loopwhole was applied to the PDB-REDO databank, we observed an increase of 11% in the number of built loops

Summary

Introduction

Protein structure models give direct and detailed insights into biochemistry (Lamb et al, 2015) and are highly relevant to many areas of biology and biotechnology (Terwilliger & Bricogne, 2014). It is important to realize that all structures are interpretations of the underlying experimental data (Lamb et al, 2015; Wlodawer et al, 2013) and the quality of a structure model should be scrutinized by validation (Read et al, 2011; Richardson et al, 2013). Owing to numerous improvements in refinement and validation methods, the quality of protein structure models is continuously increasing (Read et al, 2011); the completeness of models is decreasing (Fig. 1).

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