Abstract
Introduction: Tyrosine threonine kinase (TTK1) is a key regulator of chromosome segregation. Recently, TTK targeting came into focus for the enhancement of possible anticancer therapies.
Objective: In this regard, we employed our well-known method of QSAR-guided selection of the best crystallographic pharmacophore(s) to discover considerable binding interactions that transfer inhibitors into TTK1 binding site.
Methods: Sixty-one TTK1 crystallographic complexes were used to extract 315 pharmacophore hypotheses. QSAR modeling was subsequently used to choose a single crystallographic pharmacophore that, when combined with other physicochemical descriptors, elucidates discrepancy in bioactivity of 55 miscellaneous inhibitors.
Results: The best QSAR model was robust and predictive (r2(55) = 0.75, r2LOO = 0.72 , r2press against external testing list of 12 compounds = 0.67), Standard error of estimate (training set) (S)= 0.63 , Standard error of estimate (testing set)(Stest) = 0.62. The resulting pharmacophore and QSAR models were used to scan the National Cancer Institute (NCI) database for new TTK1 inhibitors.
Conclusion: Five hits confirmed significant TTK1 inhibitory profiles with IC50 values ranging between 11.7 and 76.6 mM.
Keywords: Structure-based drug design, checkpoint kinase TTK, QSAR analysis, molecular modeling, IC50.
Graphical Abstract
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