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Structural assembly of two-domain proteins by rigid-body docking

Overview of attention for article published in BMC Bioinformatics, October 2008
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Title
Structural assembly of two-domain proteins by rigid-body docking
Published in
BMC Bioinformatics, October 2008
DOI 10.1186/1471-2105-9-441
Pubmed ID
Authors

Tammy MK Cheng, Tom L Blundell, Juan Fernandez-Recio

Abstract

Modelling proteins with multiple domains is one of the central challenges in Structural Biology. Although homology modelling has successfully been applied for prediction of protein structures, very often domain-domain interactions cannot be inferred from the structures of homologues and their prediction requires ab initio methods. Here we present a new structural prediction approach for modelling two-domain proteins based on rigid-body domain-domain docking. Here we focus on interacting domain pairs that are part of the same peptide chain and thus have an inter-domain peptide region (so called linker). We have developed a method called pyDockTET (tethered-docking), which uses rigid-body docking to generate domain-domain poses that are further scored by binding energy and a pseudo-energy term based on restraints derived from linker end-to-end distances. The method has been benchmarked on a set of 77 non-redundant pairs of domains with available X-ray structure. We have evaluated the docking method ZDOCK, which is able to generate acceptable domain-domain orientations in 51 out of the 77 cases. Among them, our method pyDockTET finds the correct assembly within the top 10 solutions in over 60% of the cases. As a further test, on a subset of 20 pairs where domains were built by homology modelling, ZDOCK generates acceptable orientations in 13 out of the 20 cases, among which the correct assembly is ranked lower than 10 in around 70% of the cases by our pyDockTET method. Our results show that rigid-body docking approach plus energy scoring and linker-based restraints are useful for modelling domain-domain interactions. These positive results will encourage development of new methods for structural prediction of macromolecules with multiple (more than two) domains.

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Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 2%
Germany 1 2%
Indonesia 1 2%
Russia 1 2%
Spain 1 2%
Japan 1 2%
Unknown 37 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 28%
Researcher 7 16%
Student > Master 5 12%
Student > Bachelor 4 9%
Professor 3 7%
Other 6 14%
Unknown 6 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 30%
Agricultural and Biological Sciences 13 30%
Chemistry 5 12%
Computer Science 2 5%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Other 3 7%
Unknown 6 14%