Kegg Pathway: 2-Aminothiazole family

J Med Chem. 2006 Nov 16; 49(23): 6819-32
Das J, Chen P, Norris D, Padmanabha R, Lin J, Moquin RV, Shen Z, Cook LS, Doweyko AM, Pitt S, Pang S, Shen DR, Fang Q, de Fex HF, McIntyre KW, Shuster DJ, Gillooly KM, Behnia K, Schieven GL, Wityak J, Barrish JC

2-Aminothiazole (1) was discovered as a novel Src family kinase inhibitor template through screening of our internal compound collection. Optimization through successive structure-activity relationship iterations identified analogs 2 (Dasatinib, BMS-354825) and 12m as pan-Src inhibitors with nanomolar to subnanomolar potencies in biochemical and cellular assays. Molecular modeling was used to construct a putative binding model for Lck inhibition by this class of compounds. The framework of key hydrogen-bond interactions proposed by this model was in agreement with the subsequent, published crystal structure of 2 bound to structurally similar Abl kinase. The oral efficacy of this class of inhibitors was demonstrated with 12m in inhibiting the proinflammatory cytokine IL-2 ex vivo in mice (ED50 approximately 5 mg/kg) and in reducing TNF levels in an acute murine model of inflammation (90% inhibition in LPS-induced TNFalpha production when dosed orally at 60 mg/kg, 2 h prior to LPS administration). The oral efficacy of 12m was further demonstrated in a chronic model of adjuvant arthritis in rats with established disease when administered orally at 0.3 and 3 mg/kg twice daily. Dasatinib (2) is currently in clinical trials for the treatment of chronic myelogenous leukemia.

J Mol Graph Model. 2002 Jun; 20(6): 491-8
Gillet VJ, Willett P, Fleming PJ, Green DV

When designing a combinatorial library it is usually desirable to optimise multiple properties of the library simultaneously and often the properties are in competition with one another. For example, a library that is designed to be focused around a given target molecule should ideally have minimum cost and also contain molecules that are bioavailable. In this paper, we describe the program MoSELECT for multiobjective library design that is based on a multiobjective genetic algorithm (MOGA). MoSELECT searches the product-space of a virtual combinatorial library to generate a family of equivalent solutions where each solution represents a combinatorial subset of the virtual library optimised over multiple objectives. The family of solutions allows the relationships between the objectives to be explored and thus enables the library designer to make an informed choice on an appropriate compromise solution. Experiments are reported where MoSELECT has been applied to the design of various focused libraries.