Sequence assignment for low-resolution modelling of protein crystal structures

Acta Crystallographica. Section D, Structural Biology
Grzegorz ChojnowskiVictor S Lamzin

Abstract

The performance of automated model building in crystal structure determination usually decreases with the resolution of the experimental data, and may result in fragmented models and incorrect side-chain assignment. Presented here are new methods for machine-learning-based docking of main-chain fragments to the sequence and for their sequence-independent connection using a dedicated library of protein fragments. The combined use of these new methods noticeably increases sequence coverage and reduces fragmentation of the protein models automatically built with ARP/wARP.

References

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Mar 21, 2007·Acta Crystallographica. Section D, Biological Crystallography·Ronan M Keegan, Martyn D Winn
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Mar 12, 2015·Acta Crystallographica. Section D, Biological Crystallography·Grzegorz ChojnowskiJanusz M Bujnicki
Feb 20, 2016·Acta Crystallographica. Section D, Structural Biology·Przemyslaw Jerzy PorebskiWladek Minor

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Citations

Mar 7, 2020·Acta Crystallographica. Section D, Structural Biology·Adam D CrawshawPaula S Salgado
Mar 7, 2020·Acta Crystallographica. Section D, Structural Biology·Grzegorz ChojnowskiVictor S Lamzin
Feb 10, 2021·Acta Crystallographica. Section D, Structural Biology·Grzegorz ChojnowskiVictor S Lamzin
Jun 27, 2021·Science Advances·Katherine S H BeckhamMatthias Wilmanns

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Methods Mentioned

BETA
X-ray

Software Mentioned

LIBSVM
scikit
wARP
REDO
MORDA
MrBUMP
seqqy
ARP
BALBES
MOLREP

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