Data structures for compound promiscuity analysis: promiscuity cliffs, pathways and promiscuity hubs formed by inhibitors of the human kinome

Aim: A large collection of promiscuity cliffs (PCs), PC pathways (PCPs) and promiscuity hubs (PHs) formed by inhibitors of human kinases is made freely available. Methodology: Inhibitor PCs were systematically identified and organized in network representations, from which PCPs were extracted. PH compounds were classified and their neighborhoods analyzed. Data & exemplary results: Nearly 16,000 PCs covering the human kinome were identified, which yielded more than 600 PC clusters and 8900 PCPs. Moreover, 520 PHs were obtained. Limitations & next steps: PC and PCP data structures capture structure–promiscuity relationships. Promiscuity assessment is also affected by data sparseness. Given the rapid growth of kinase inhibitor data, the relevance of PC/PCP/PH information for medicinal chemistry and chemical biology applications will further increase.

Identification and analysis of promiscuity cliffs formed by bioactive compounds and experimental implications

For three promiscuity cliffs (enclosed), cliff compounds, their promiscuity degrees (PDs), and color-coded substitution sites are shown. Comparison of these cliffs suggests the design of a new analog to further explore promiscuity.