Inhibitors of the Hsp90 molecular chaperone are showing considerable promise as potential chemotherapeutic agents for cancer. Here, we describe the structure-based design, synthesis, structure-activity relationships and pharmacokinetics of potent small-molecule inhibitors of Hsp90 based on the 4,5-diarylisoxazole scaffold. Analogues from this series have high affinity for Hsp90, as measured in a fluorescence polarization (FP) competitive binding assay, and are active in cancer cell lines where they inhibit proliferation and exhibit a characteristic profile of depletion of oncogenic proteins and concomitant elevation of Hsp72. Compound 40f (VER-52296/NVP-AUY922) is potent in the Hsp90 FP binding assay (IC50 = 21 nM) and inhibits proliferation of various human cancer cell lines in vitro, with GI50 averaging 9 nM. Compound 40f is retained in tumors in vivo when administered i.p., as evaluated by cassette dosing in tumor-bearing mice. In a human colon cancer xenograft model, 40f inhibits tumor growth by approximately 50%.
The crystal structure of a previously reported screening hit 1 (CCT018159) bound to the N terminal domain of molecular chaperone Hsp90 has been used to design 5-amide analogues. These exhibit enhanced potency against the target in binding and functional assays with accompanying appropriate cellular pharmacodynamic changes. Compound 11 (VER-49009) compares favorably with the clinically evaluated 17-AAG.
Inhibitors of the Hsp90 molecular chaperone are showing considerable promise as potential molecular therapeutic agents for the treatment of cancer. Here we describe novel 2-aminothieno[2,3-d]pyrimidine ATP competitive Hsp90 inhibitors, which were designed by combining structural elements of distinct low affinity hits generated from fragment-based and in silico screening exercises in concert with structural information from X-ray protein crystallography. Examples from this series have high affinity (IC50 = 50-100 nM) for Hsp90 as measured in a fluorescence polarization (FP) competitive binding assay and are active in human cancer cell lines where they inhibit cell proliferation and exhibit a characteristic profile of depletion of oncogenic proteins and concomitant elevation of Hsp72. Several examples (34a, 34d and 34i) caused tumor growth regression at well tolerated doses when administered orally in a human BT474 human breast cancer xenograft model.
There is a pressing need for new technologies that improve the efficacy and efficiency of drug discovery. Structure-based methods have contributed towards this goal but they focus on predicting the binding affinity of protein-ligand complexes, which is notoriously difficult. We adopt an alternative approach that evaluates structural, rather than thermodynamic, stability. As bioactive molecules present a static binding mode, we devised dynamic undocking (DUck), a fast computational method to calculate the work necessary to reach a quasi-bound state at which the ligand has just broken the most important native contact with the receptor. This non-equilibrium property is surprisingly effective in virtual screening because true ligands form more-resilient interactions than decoys. Notably, DUck is orthogonal to docking and other 'thermodynamic' methods. We demonstrate the potential of the docking-undocking combination in a fragment screening against the molecular chaperone and oncology target Hsp90, for which we obtain novel chemotypes and a hit rate that approaches 40%.
We have implemented five drug-like filters, based on 1D and 2D molecular descriptors, and applied them to characterize the drug-like properties of commercially available chemical compounds. In addition to previously published filters (Lipinski and Veber), we implemented a filter for medicinal chemistry tractability based on lists of chemical features drawn up by a panel of medicinal chemists. A filter based on the modeling of aqueous solubility (>1 microM) was derived in-house, as well as another based on the modeling of Caco-2 passive membrane permeability (>10 nm/s). A library of 2.7 million compounds was collated from the 23 compound suppliers and analyzed with these filters, highlighting a tendency toward highly lipophilic compounds. The library contains 1.6 M unique structures, of which 37% (607,223) passed all five drug-like filters. None of the 23 suppliers provides all the members of the drug-like subset, emphasizing the benefit of considering compounds from various compound suppliers as a source of diversity for drug discovery.
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