The use of Bayesian statistics to model both general (multifamily) and specific (single-target) kinase inhibitors is investigated. The approach demonstrates an alternative to current computational methods applied to heterogeneous structure/activity data sets. This approach operates rapidly and is readily modifiable as required. A generalized model generated using inhibitor data from multiple kinase classes shows meaningful enrichment for several specific kinase targets. Such an approach can be used to prioritize compounds for screening or to optimally select compounds from third-party data collections. The observed benefit of the approach is finding compounds that are not structurally related to known actives, or novel targets for which there is not enough information to build a specific kinase model. The general kinase model described was built from a basis of mostly tyrosine kinase inhibitors, with some serine/threonine inhibitors; all the test cases used in prediction were also on tyrosine kinase targets. Confirming the applicability of this technique to other kinase families will be determined once those biological assays become available.
X-ray crystallography studies of racemic 5-[7-[4-(4,5-dihydro-4-methyl-2-oxazolyl)phenoxy]heptyl]- 3-methylisoxazole bound to human rhinovirus-14 (HRV-14) indicate selective binding of the S isomer. This result correlates well with the 10-fold greater activity of the S isomer as compared to the R isomer. The enantiomeric effect on activity is explained by a hydrophobic interaction of the methyl group in the case of 2a, with a pocket formed by Leu106 and Ser107. The 4-ethyl, 4-propyl, and 4-butyloxazolinyl homologues were prepared and tested against HRV-14. All of these compounds exhibited a comparable stereochemical effect. In each case, the S isomer displayed greater levels of activity than the R. The results of energetic considerations of the oxazoline ring in an 8-A pocket bound to the HRV-14 binding site suggest that the twist angle between the oxazoline and phenyl rings resulting from hydrophobic interactions of the alkyl substituents could be one of the determining factors for biological activity.
A series of substituted phenyl analogues of 5-[[4-(4,5-dihydro-2-oxazolyl) phenoxy]alkyl]-3-methylisoxazoles has been synthesized and evaluated in vitro against several human rhinovirus (HRV) serotypes. Substituents in the 2-position greatly enhanced activity when compared to the unsubstituted compound. Many of these compounds exhibited mean MICs (MIC) against five serotypes as low as 0.40 microM. The mean MIC correlated well (r = 0.83) with the MIC80 (the concentration that inhibited 80% of the serotypes tested). A quantitative structure-activity relationship study indicated a strong dependency of MIC on lipophilicity (log P) in combination with inductive effects (sigma m) and bulk factors (MW).
A simple recursive partitioning decision tree may successfully be used to improve cost-effectiveness by reducing the wastage associated with the unnecessary purchase of vendor compounds unsuitable for NMR screening because of insolubility.
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