SIMCOMP uses a variant of the Bron-Kerbosch maximum clique algorithm [49] to identify the maximum common substructure of two compounds.
The developed plugin represents an interface between PyMOL and LiSiCA, an LBVS software based on a graph theoretical maximum clique algorithm (http://insilab.org/maxclique) [13, 14].
This paper describes a new very efficient branch-and-bound exact maximum clique algorithm BBMCSP, designed for large and massive sparse graphs which appear frequently in real life problems from different fields.
As claimed in the previous section, the number vertices in the first layer of the graph is negligible as compared to the size of the graph, and therefore, the maximum clique algorithm applied in that sub-graph requires few computation.
Also a recently developed, freely-available web server, which enables ligand homology modeling, is ProBiS-ligands (Fig. 2) [45], a method that uses a fast maximum clique algorithm [21] to screen the non-redundant PDB database, to find structurally similar target binding sites to user provided input query protein, independent of their sequence or global structural similarity.
ProBiS uses a fast maximum clique algorithm [21] to compare a query protein to members of a database of 3D protein structures and detects with sub-residue precision structurally similar binding sites as patterns of physiochemical properties on the protein surface.
The script applies a maximum clique algorithm.
However, the actual performance of an efficient maximum clique algorithm depends on the structure of the input graph.
Using a fast maximum clique algorithm and a strategy of dividing graphs into subgraphs, enables our approach to the comparison of complete protein surfaces.
The maximal clique algorithm of Bron and Kerbosch, which has previously been used to compare binding sites (Schmitt et al., 2002), significantly differs from our maximum clique algorithm (Konc and Janežič, 2007b).
