Systematic computational identification of promiscuity cliff pathways formed by inhibitors of the human kinome

Data Structures for Compound Promiscuity Analysis: Promiscuity cliffs, Pathways and Promiscuity Hubs Formed by Inhibitors of the Human Kinome

“…PCPs are defined as linear subgraphs of PC clusters and consist of compounds with alternating high and low promiscuity [13]. From PC network clusters, PCPs are systematically extracted using an algorithm based on breadth-first search for shortest paths [14]. In breadth-first search, edges between neighboring nodes have equal length.…”

“…These clusters are rich in structure–promiscuity relationship information, but difficult to analyze. Therefore, as an extension of the PC concept, the PC pathway (PCP) data structure was introduced [13,14]. PCPs are formed in PC clusters and consist of sequences of PCs with overlapping compounds.…”

“…PCP compounds have alternating high and low promiscuity (or are highly promiscuous and nonpromiscuous). They can be systematically extracted from PC clusters using a computational search method [14]. Nearly 16,000 PCs formed by inhibitors of human kinases were organized in more than 600 separate network clusters [13] and from these clusters, 8900 PCPs were isolated [14].…”

“…Following network terminology, hubs are densely connected nodes. PHs are highly promiscuous PCP compounds that form large numbers of PCs with weakly or nonpromiscuous structural analogs outside the PCP [14]. PHs also occur in network regions outside PCPs.…”

“…Taken together, PCs, PCPs and PHs provide valuable information for medicinal chemistry or chemical biology projects. This data note details an open access deposition of PCs identified across the human kinome [13], PCPs extracted from their network clusters [14] and PHs formed by individual kinase inhibitors including clinical compounds. These data are made freely available in an organized and easily accessible form.…”