Abstract
BackgroundThe development of accurate protein-protein docking programs is making this kind of simulations an effective tool to predict the 3D structure and the surface of interaction between the molecular partners in macromolecular complexes. However, correctly scoring multiple docking solutions is still an open problem. As a consequence, the accurate and tedious screening of many docking models is usually required in the analysis step.MethodsAll the programs under CONS-COCOMAPS have been written in python, taking advantage of python libraries such as SciPy and Matplotlib. CONS-COCOMAPS is freely available as a web tool at the URL:http://www.molnac.unisa.it/BioTools/conscocomaps/.ResultsHere we presented CONS-COCOMAPS, a novel tool to easily measure and visualize the consensus in multiple docking solutions. CONS-COCOMAPS uses the conservation of inter-residue contacts as an estimate of the similarity between different docking solutions. To visualize the conservation, CONS-COCOMAPS uses intermolecular contact maps.ConclusionsThe application of CONS-COCOMAPS to test-cases taken from recent CAPRI rounds has shown that it is very efficient in highlighting even a very weak consensus that often is biologically meaningful.
Highlights
The development of accurate protein-protein docking programs is making this kind of simulations an effective tool to predict the 3D structure and the surface of interaction between the molecular partners in macromolecular complexes [1]
The conservation of inter-residue contacts has been here measured and visualized with CONS-COCOMAPS for a total of 2130 models submitted to CAPRI for seven different targets: T24, T25, T26, T28, T29, T32 and T36 (See Table 1)
Even T24, having no medium/high quality prediction, presents three native contacts among the ten most conserved ones (Additional file 5). These findings indicate that the consensus of many solutions, even incorrect according to the CAPRI definition, may point to the correct inter-residue contacts
Summary
The development of accurate protein-protein docking programs is making this kind of simulations an effective tool to predict the 3D structure and the surface of interaction between the molecular partners in macromolecular complexes. The 3D structure of a significant fraction of biomolecular complexes is difficult to solve experimentally In this scenario, the development of accurate protein-protein docking programs is making this kind of simulations an effective tool to predict the 3D structure and the surface of interaction between the molecular partners in macromolecular complexes [1]. The first step of a docking simulation generates a large number, around 105-106, of 3D models (decoys) Such decoys are clusterized on the basis of RMSD values, usually calculated on the atoms of the smaller molecular partner (or “ligand”) [5,6,7]. Alternative scores have been proposed to evaluate the correctness of a docking prediction, based on the geometric distance between the interfaces, and the residue-residue contact similarity [8]
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