MOTIVATION: Rational design of kinase inhibitors remains a challenge partly because there is no clear delineation of the molecular features that direct the pharmacological impact towards clinically relevant targets. Standard factors governing ligand affinity, such as potential for intermolecular hydrophobic interactions or for intermolecular hydrogen bonding do not provide good markers to assess cross reactivity. Thus, a core question in the informatics of drug design is what type of molecular similarity among targets promotes promiscuity and what type of molecular difference governs specificity. This work answers the question for a sizable screened sample of the human pharmacokinome including targets with unreported structure. RESULTS: We show that drug design aimed at promoting pairwise interactions between ligand and kinase target actually fosters promiscuity because of the high conservation of the partner groups on or around the ATP-binding site of the kinase. Alternatively, we focus on a structural marker that may be reliably determined from sequence and measures dehydration propensities mostly localized on the loopy regions of kinases. Based on this marker, we construct a sequence-based kinase classifier that enables the accurate prediction of pharmacological differences. Our indicator is a microenvironmental descriptor that quantifies the propensity for water exclusion around preformed polar pairs. The results suggest that targeting polar dehydration patterns heralds a new generation of drugs that enable a tighter control of specificity than designs aimed at promoting ligand-kinase pairwise interactions. AVAILABILITY: The predictor of polar hot spots for dehydration propensity, or solvent-accessible hydrogen bonds in soluble proteins, named YAPView, may be freely downloaded from the University of Chicago website http://protlib.uchicago.edu/dloads.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Rational design of kinase inhibitors remains a challenge partly because there is no clear delineation of the molecular features that direct the pharmacological impact towards clinically relevant targets. Standard factors governing ligand affinity, such as potential for intermolecular hydrophobic interactions or for intermolecular hydrogen bonding do not provide good markers to assess cross reactivity. Thus, a core question in the informatics of drug design is what type of molecular similarity among targets promotes promiscuity and what type of molecular difference governs specificity. This work answers the question for a sizable screened sample of the human pharmacokinome including targets with unreported structure. RESULTS: We show that drug design aimed at promoting pairwise interactions between ligand and kinase target actually fosters promiscuity because of the high conservation of the partner groups on or around the ATP-binding site of the kinase. Alternatively, we focus on a structural marker that may be reliably determined from sequence and measures dehydration propensities mostly localized on the loopy regions of kinases. Based on this marker, we construct a sequence-based kinase classifier that enables the accurate prediction of pharmacological differences. Our indicator is a microenvironmental descriptor that quantifies the propensity for water exclusion around preformed polar pairs. The results suggest that targeting polar dehydration patterns heralds a new generation of drugs that enable a tighter control of specificity than designs aimed at promoting ligand-kinase pairwise interactions. AVAILABILITY: The predictor of polar hot spots for dehydration propensity, or solvent-accessible hydrogen bonds in soluble proteins, named YAPView, may be freely downloaded from the University of Chicago website http://protlib.uchicago.edu/dloads.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Richard Bonneau; Charlie E M Strauss; Carol A Rohl; Dylan Chivian; Phillip Bradley; Lars Malmström; Tim Robertson; David Baker Journal: J Mol Biol Date: 2002-09-06 Impact factor: 5.469
Authors: Ariel Fernández; Angela Sanguino; Zhenghong Peng; Eylem Ozturk; Jianping Chen; Alejandro Crespo; Sarah Wulf; Aleksander Shavrin; Chaoping Qin; Jianpeng Ma; Jonathan Trent; Yvonne Lin; Hee-Dong Han; Lingegowda S Mangala; James A Bankson; Juri Gelovani; Allen Samarel; William Bornmann; Anil K Sood; Gabriel Lopez-Berestein Journal: J Clin Invest Date: 2007-12 Impact factor: 14.808