Abstract
BackgroundModelling 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.ResultsHere 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.ConclusionOur 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.
Highlights
Modelling proteins with multiple domains is one of the central challenges in Structural Biology
We began by compiling inter-domain linkers from multi-domain structures in PDB (Protein Data Bank), with the following requisites: i) The linkers were identified as those polypeptide parts placed between domains defined by Pfam [12] ( Pfam may not always defines domains with clear structural boundaries as those defined in SCOP [13], it is more realistic for identifying domains from protein sequences that have unsolved structures); ii) Only structures with a resolution ≤ 2.5Å were used, in order to obtain atomic positions of linkers with greater certainty; and iii) Only linkers joining domains that are in contact were included
Since our goal was to evaluate the success of our scoring function in the identification of the correct domain-domain assemblies within a docking set, we considered only those cases that had at least one acceptable docking solution within the 2,000 docking poses generated by ZDOCK
Summary
Modelling proteins with multiple domains is one of the central challenges in Structural Biology. 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. Crystallography of multi-domain proteins that have flexible linkers is more problematic. For multi-domain proteins with no structural information, their domain orientations may be predicted through homology modelling. Even if a homologous template exists, its domains might not interact in the same way as the protein to model (see the review of Aloy and Russell [3]). To minimize the chance of inferring wrong interaction data from the templates, Aloy and Russell tried to model putative interactions by assessing residue contacts in the interfaces of known three-dimensional protein structures [4]. Wollacott and co-workers [5] modelled domain-domain assemblies by placing the domains at the N- and C-terminal of the linker structure, whose conformation is sampled during the procedure Their approach successfully identified nearnative assemblies in 50% of the studied cases
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