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• W1602137070 abstract "Abstract The comparison of protein binding sites is a prominent task in computational chemistry and has been studied in many different ways. For the automatic detection and comparison of putative binding cavities the Cavbase system has been developed which uses a coarse‐grained set of pseudocenters to represent the physicochemical properties of a binding site and employs a graph‐based procedure to calculate similarities between two binding sites. However, the comparison of two graphs is computationally quite demanding which makes large‐scale studies such as the rapid screening of entire databases hardly feasible. In a recent work, we proposed the method Local Cliques (LC) for the efficient comparison of Cavbase binding sites. It employs a clique heuristic to detect the maximum common subgraph of two binding sites and an extended graph model to additionally compare the shape of individual surface patches. In this study, we present an alternative to further accelerate the LC method by partitioning the binding‐site graphs into disjoint components prior to their comparisons. The pseudocenter sets are split with regard to their assigned phyiscochemical type, which leads to seven much smaller graphs than the original one. Applying this approach on the same test scenarios as in the former comprehensive way results in a significant speed‐up without sacrificing accuracy." @default.
• W1602137070 created "2016-06-24" @default.
• W1602137070 creator A5005420915 @default.
• W1602137070 creator A5073954945 @default.
• W1602137070 date "2015-06-19" @default.
• W1602137070 modified "2023-10-10" @default.
• W1602137070 title "Acceleration of Binding Site Comparisons by Graph Partitioning" @default.
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• W1602137070 doi "https://doi.org/10.1002/minf.201500028" @default.
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