![]() ![]() Our approach takes advantage of the hierarchical structure of the data - from the whole ensemble of protein complex configurations to the individual configurations, their contact interfaces, and the interacting amino acids. In this paper, we propose a novel multiscale visual drilldown approach that was designed in tight collaboration with proteomic experts, enabling a systematic exploration of the configuration space. However, it is not feasible to experimentally verify more than only a very small subset of them. ![]() ![]() When studying multi-body protein complexes, biochemists use computational tools that can suggest hundreds or thousands of their possible spatial configurations. Supplementary data are available at Bioinformatics online. It placed correctly most of the subunits of multimolecular complexes of up to 16 subunits and significantly outperformed the CombDock and Haddock multimolecular docking methods. The method was tested on several representative complexes, both in the bound and unbound cases. The optimal assembly of the individual subunits is formulated as an Integer Linear Programming task. The algorithm accepts as input atomic resolution structures of the individual subunits obtained from X-ray, NMR or homology modeling, and interaction data between the subunits obtained from mass spectrometry. We present a novel integrative computational modeling method, which integrates both low and high resolution experimental data. Experimental techniques can provide atomic resolution structures of single proteins and small complexes, or low resolution data of large multimolecular complexes. Atomic resolution modeling of large multimolecular assemblies is a key task in Structural Cell Biology. ![]()
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