Fishing wild-type sparing inhibitors of proto-oncogene c-met variants in renal cell carcinoma from a curated tyrosine kinase inhibitor pool using analog-sensitive kinase technology

Intrinsic relative preference profile of pan-kinase inhibitor drug staurosporine towards the clinically occurring gatekeeper mutations in Protein Tyrosine Kinases

Protein tyrosine kinases (PTKs) have been recognized as the attractive druggable targets of various diseases including cancer. However, many PTKs are clinically observed to establish a gatekeeper mutation in the peripheral hinge section of active site, which plays a primary role in development of acquired drug resistance to kinase inhibitors. The natural product Staurosporine, an ATP-competitive reversible pan-kinase inhibitor, has been found to exhibit wild type-sparing selectivity for some PTK gatekeeper mutants. In this study, totally 23 acquired drug-resistant gatekeeper mutations harbored on 17 PTKs involved in diverse cancers were curated, from which only five amino acid types, namely Thr, Met, Val, Leu and Ile, were observed at both wild-type and mutant residues of these clinically occurring gatekeeper sites. Here, an integrative strategy that combined molecular modeling and kinase assay was described to systematically investigate the relative preference of Staurosporine towards the five gatekeeper amino acid types in real kinase context and in a psendokinase model. A kinase-free, intrinsic relative preference profile of Staurosporine to gatekeeper amino acids was created: (dispreferred) Thr⊳Val⊳Ile⊳Leu⊳Met (preferred). It is found that kinase context has no essential effect on the profile; different kinases and even psendokinase can obtain a consistent conclusion for the preference order. Theoretically, we can use the profile to predict Staurosporine response to any gatekeeper mutation between the five amino acid types in any PTK. Structural and energetic analyses revealed that the multiple-aromatic ring system of Staurosporine can form multiple noncovalent interactions with the weakly polar side chain of Met and can pack tightly or moderately against the nonpolar side chains of Val, Ile and Leu, thus stabilizing the kinase-inhibitor system (ΔU < 0), whereas the polar side chain of Thr may cause unfavorable electronegative and solvent effects with the aromatic electrons of Staurosporine, thus destabilizing the system (ΔU > 0).

Structure-guided design and development of novel N-phenylpyrimidin-2-amine derivatives as potential c-Met inhibitors

The HGF/Met signaling pathway is over-expressed in many types of cancers and closely related to oncogenesis and metastasis. Thus, we developed novel N-phenylpyrimidin-2-amine derivatives to test their inhibitory activities towards c-Met kinase, and most of the compounds (15a-i, 15o-r, 20 and 34a-c) could inhibit the target with IC₅₀ values from 550.8 nM to 15.0 nM. Subsequently, compound 15b, 15d, 15f, 15i, 15o, 15r, 20, 34a and 34b also showed high antiproliferative activities in c-Met sensitive tumor cell lines (PC-3, Panc-1, HepG2, HCT116 and Caki-1) with IC₅₀ values from 0.53 to 1.37 μM. The lead compound 34a displayed outstanding c-Met inhibitory activity (IC₅₀: 15.0 nM) and antiproliferative activities. Furthermore, 34a also performed favorable pharmacokinetic properties in mice (F%: 59.3) and an acceptable safety profile in preclinical studies. Further docking studies showed a common interaction of 34a with c-Met at the ATP-binding site, which indicated that 34a could be a potential candidate for c-Met inhibitors.

Inverse in silico-in vitro fishing of unexpected paroxetine kinase targets from tumor druggable kinome

The serotonin selective reuptake inhibitor paroxetine has been clinically observed to reposition a significant suppressing potency on human tumors by unexpectedly targeting diverse kinase pathways involved in tumorigenesis. Here, we describe an inverse in silico-in vitro strategy to fish potential kinase targets using the paroxetine as bait. This is different (inverse) to the traditional drug discovery process that commonly screens small-molecule inhibitors for a specific kinase target. In the procedure, cell viability assays demonstrate that paroxetine has strong cytotoxicity on human tumor cell lines. Various protooncogene protein kinases are ontologically/manually enriched to define a druggable kinome, and a systematic interaction profile of paroxetine with the kinome is created, which indicates that paroxetine can potentially bind to some known targets or key regulators of human tumors. Kinase assays determine that paroxetine can effectively inhibit c-Src family kinases at nanomolar or micromolar levels. It is observed that the paroxetine ligand forms a tightly packed interface against the active site of these unexpected kinase targets to constitute several specific hydrogen bonds/π-π/cation-π stackings and a number of nonspecific hydrophobic/vdW contacts, while exposing a portion of molecular surface to solvent. More significantly, the ligand adopts two distinct binding modes (i.e., class I and class II) to interact with different kinases; the class-I mode has a higher stability and inhibitory activity than class-II mode. Steric clash seems to cause the ligand flipping from class I to class II. Graphical abstract.

Computational systematic selectivity of the Fasalog inhibitors between ROCK-I and ROCK-II kinase isoforms in Alzheimer's disease

Human Rho-associated coiled-coil forming kinase (ROCK) is a class of essential neurokinases that consists of two structurally conserved isoforms ROCK-I and ROCK-II; they have been revealed to play distinct roles in the pathogenesis of Alzheimer's disease (AD) and other neurological disorders. Selective targeting of the two kinase isoforms with small-molecule inhibitors is a great challenge due to the surprisingly high homology in kinase domain (92 %) and the full identity in kinase active site (100 %). Here, we describe a computational protocol to systematically profile the selectivity of Fasudil and its 25 analogs (termed as Fasalogs) between the two kinase isoforms. It is suggested that the substitution of Fasudil's 1,4-diazepane moiety with rigid ring such as Ripasudil and Dimehtylfasudil would render the resulting inhibitors of ROCK-II over ROCK-I (II-o-I) selectivity, while the substitution with long, flexible group such as H-89 and BDBM92607 tends to have I-o-II selectivity. Structural analysis reveals that the inhibitor affinity is not only determined by the identical active site, but also contributed from the non-identical first and second shells of the site as well as other non-conserved kinase regions, which can indirectly influence the active site and inhibitor binding through allosteric effect. A further kinase assay basically confirms the computational findings, which also exhibits a good consistence with theoretical selectivity over 10 tested samples (Rp = 0.89). In particular, the Fasalog compounds Dimehtylfasudil and H-89 are identified as II-o-I and I-o-II selective inhibitors. They can be considered as promising lead molecular entities to develop new specific ROCK isoform-selective Fasalog inhibitors.

Systematic response of staurosporine scaffold-based inhibitors to drug-resistant cancer kinase mutations

Human protein kinases have been established as promising druggable targets in cancer therapy. However, a large number of acquired drug-resistant kinase mutations are observed after first- and second-line kinase inhibitor treatments, largely limiting the application of small-molecule inhibitors in the targeted cancer therapy. Previously, the pan-kinase inhibitor staurosporine and its derivatives have been reported to selectively inhibit gatekeeper mutants over wild-type kinases, suggesting that the staurosporine scaffold is potentially helpful in developing wild-type-sparing inhibitors of drug-resistant kinase mutants. Here, a systematic response profile of 32 staurosporine scaffold-based inhibitors (SSBIs) for 61 ontology-enriched drug-resistant cancer kinase mutations is created using a combination of in silico analysis and in vitro assay, from which it is possible to identify those mutations that have the potential to cause resistance or confer sensitivity to SSBIs. The profile reveals that SSBIs exhibit distinct responses to kinase gatekeeper and nongatekeeper mutations, and SSBIs bearing p7 substituents can considerably influence their response to kinase gatekeeper mutations, particularly for the mutations of the Ile residue, which possesses a Cβ methyl group that tends to cause steric clash with bound SSBIs. Nongatekeeper mutations generally have a moderate and unfavorable effect on SSBI activity, as most of them are outside the kinase active site and do not directly contact inhibitor ligands. In addition, it is found that resistance is commonly caused by mutation-induced hindrance effects, whereas sensitivity is primarily conferred by mutation-established additional interactions.

Systematic profiling of staralog response to acquired drug resistant kinase gatekeeper mutations in targeted cancer therapy

Kinase-targeted therapy has been widely used as a lifesaving strategy for cancer patients. However, many patients treated with targeted cancer drugs are clinically observed to rapidly develop acquired resistance. Kinase gatekeeper mutation is one of the most chief factors contributing to the resistance, which modulates the accessibility of kinase's ATP-binding pocket. Previously, the pan-kinase inhibitor Staurosporine and its analogs (termed as Staralogs) have been reported to exhibit wild-type sparing selectivity for some kinase gatekeeper mutants, such as EGFR T790M, Her2 T798M and cSrc T338M. Here, we describe an integrative approach to systematically profile the molecular response of 15 representative Staralogs to 17 kinase gatekeeper mutations in targeted cancer therapy. With the profile we are able to divide gatekeeper mutations into three classes (i.e. classes I, II and III) and to divide Staralogs into two groups (i.e. groups 1 and 2) using heuristic clustering. The class I and II mutations confer consistent sensitivity and resistance for all Staralogs, respectively, while the class III mutations address divergent effects on different Staralogs. The mutations to Ile residue can generally reduce Staralog affinity by inducing unfavorable steric hindrance, whereas the mutations to Met and Leu residues would improve Staralog affinity by establishing favorable S···π interaction, van der Waals packing and/or hydrophobic contact. The group 1 and 2 Staralogs are primarily determined by carbonyl or hydroxyl substitution state at the position 7 of Staralog core, where points to kinase gatekeeper residue and can thus be directly influenced by gatekeeper mutation.

Inverse screening of Simvastatin kinase targets from glioblastoma druggable kinome

The statin drug Simvastatin is a HMG-CoA reductase inhibitor that has been widely used to lower blood lipid. However, the drug is clinically observed to reposition a significant suppressing potency on glioblastoma (GBM) by unexpectedly targeting diverse kinase pathways involved in GBM tumorigensis. Here, an inverse screening strategy is described to discover potential kinase targets of Simvastatin. Various human protein kinases implicated in GBM are enriched to define a druggable kinome; the binding behavior of Simvastatin to the kinome is profiled systematically via an integrative computational approach, from which most kinases have only low or moderate binding potency to Simvastatin, while only few are identified as promising kinase hits. It is revealed that Simvastatin can potentially interact with certain known targets or key regulators of GBM such as ErbB, c-Src and FGFR signaling pathways, but exhibit low affinity to the well-established GBM target of PI3K/Akt/mTOR pathway. Further assays determine that Simvastatin can inhibit kinase hits EGFR, MET, SRC and HER2 at nanomolar level, which are comparable with those of cognate kinase inhibitors. Structural analyses reveal that the sophisticated T790 M gatekeeper mutation can considerably reduce Simvastatin sensitivity to EGFR by inducing the ligand change between different binding modes.