Discovery of 1,4-dihydroindeno[1,2-c]pyrazoles as a novel class of potent and selective checkpoint kinase 1 inhibitors

Kinome analyses of Candida albicans, C. parapsilosis and C. tropicalis enable novel kinases as therapeutic drug targets in candidiasis

Candida spp. have attracted considerable attention as they cause serious human diseases in immunocompromised individuals. The genomes of the pathogenic Candida spp. have been sequenced, but systemic characterizations of their kinomes are yet to be reported. As in various eukaryotes, the protein kinases play crucial regulatory roles in pathogenicity of Candida. Increased frequency of antifungal resistance in Candida spp. requires significant attention to explore novel therapeutic molecules for their control. The present in-silico study involves novel bioinformatics strategies to identify the kinase proteins and their potential drug targets with the purpose to combat fungal infections. The study reports 103, 107 and 106 kinase proteins from 3 Candida spp., C. albicans, C. parapsilosis and C. tropicalis, respectively. Moreover, 79 common kinase proteins were identified, of which 54 proteins play essential roles in Candida spp. and 42 proteins were human non-homologues. Among the essential and human non-homologous protein kinases, 9 were found to be common essential human non-homologues, of which 6 are uniquely present in Candida. These 6 protein kinases namely, Hsl1, Npr1, Ptk2, Kin2, Ksp1 and orf19.3854 (CAALFM_CR06040WA) are involved in various molecular and cellular processes regulating virulence or pathogenicity. Further, these 6 kinases are prioritized as potential drug targets and explored for discovering new lead compounds against candidiasis. The drug repurposing approach for these 6 kinases show 13 approved drugs and investigational compounds that might play substantial inhibitory roles during combating candidiasis.

Proposed Allosteric Inhibitors Bind to the ATP Site of CK2α

CK2α is a ubiquitous, well-studied kinase that is a target for small-molecule inhibition, for treatment of cancers. While many different classes of adenosine 5'-triphosphate (ATP)-competitive inhibitors have been described for CK2α, they tend to suffer from significant off-target activity and new approaches are needed. A series of inhibitors of CK2α has recently been described as allosteric, acting at a previously unidentified binding site. Given the similarity of these inhibitors to known ATP-competitive inhibitors, we have investigated them further. In our thorough structural and biophysical analyses, we have found no evidence that these inhibitors bind to the proposed allosteric site. Rather, we report crystal structures, competitive isothermal titration calorimetry (ITC) and NMR, hydrogen-deuterium exchange (HDX) mass spectrometry, and chemoinformatic analyses that all point to these compounds binding in the ATP pocket. Comparisons of our results and experimental approach with the data presented in the original report suggest that the primary reason for the disparity is nonspecific inhibition by aggregation.

Selected arylsulphonyl pyrazole derivatives as potential Chk1 kinase ligands-computational investigations

Protein kinases control diversity of biochemical processes in human organism. Checkpoint 1 kinase (Chk1) is an important element of the checkpoint signalling pathways and is responsible for DNA damage repair. Hence, this kinase plays an essential role in cancer cells survival and has become an important target for anticancer agents. Our previous investigations showed that some arylsulphonyl indazole derivatives displayed anticancer effect in vitro. In the present study, in order to verify possibility of interactions of pyrazole and indazole derivatives with Chk1, we focused on the docking of selected tosyl derivatives of indazole and condensed pyrazole 1-7 to the Chk1 pocket, analysis of interactions involving optimized ligand-protein system using DFT formalism, and estimation of the interaction enthalpy of the ligand-protein complex by applying the PM7 method. The estimation of binding affinity seems to indicate that the indazole 5-substituted with 3,5-dimethylpyrazole 4 and condensed pyrazoloquinoline derivative 7 fit the best to the Chk1-binding pocket. The values of the energy of interaction, i.e. the enthalpy change (ΔHint), were between - 85.06 and - 124.04 kcal mol-1 for the optimized ligand-Chk1 complexes. The relaxation of the ligands within the complexes azole-protein as well as the distribution of hydrogen contacts between the ligands and kinase pocket amino acids was also analysed using molecular dynamics as a supporting method. Graphical Abstract Presentation of methods used to describe the interactions between arylsulphonyl pyrazole derivatives and Chk1 kinase.

Docking-based 3D-QSAR study of pyridyl aminothiazole derivatives as checkpoint kinase 1 inhibitors

Checkpoint kinase 1 (Chk1) is a promising target for the design of novel anticancer agents. In the present work, molecular docking simulations and three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on pyridyl aminothiazole derivatives as Chk1 inhibitors. AutoDock was used to determine the probable binding conformations of all the compounds inside the active site of Chk1. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were developed based on the docking conformations and alignments. The CoMFA model produced statistically significant results with a cross-validated correlation coefficient (q2) of 0.608 and a coefficient of determination (r2) of 0.972. The reliable CoMSIA model with q2 of 0.662 and r2 of 0.970 was obtained from the combination of steric, electrostatic and hydrogen bond acceptor fields. The predictive power of the models were assessed using an external test set of 14 compounds and showed reasonable external predictabilities (r(2)pred) of 0.668 and 0.641 for CoMFA and CoMSIA models, respectively. The models were further evaluated by leave-ten-out cross-validation, bootstrapping and progressive scrambling analyses. The study provides valuable information about the key structural elements that are required in the rational design of potential drug candidates of this class of Chk1 inhibitors.

Docking challenge: protein sampling and molecular docking performance

Computational tools are essential in the drug design process, especially in order to take advantage of the increasing numbers of solved X-ray and NMR protein-ligand structures. Nowadays, molecular docking methods are routinely used for prediction of protein-ligand interactions and to aid in selecting potent molecules as a part of virtual screening of large databases. The improvements and advances in computational capacity in the past decade have allowed for further developments in molecular docking algorithms to address more complicated aspects such as protein flexibility. The effects of incorporation of active site water molecules and implicit or explicit solvation of the binding site are other relevant issues to be addressed in the docking procedures. Using the right docking algorithm at the right stage of virtual screening is most important. We report a staged study to address the effects of various aspects of protein flexibility and inclusion of active site water molecules on docking effectiveness to retrieve (and to be able to predict) correct ligand poses and to rank docked ligands in relation to their biological activity for CHK1, ERK2, LpxC, and UPA. We generated multiple conformers for the ligand and compared different docking algorithms that use a variety of approaches to protein flexibility, including rigid receptor, soft receptor, flexible side chains, induced fit, and multiple structure algorithms. Docking accuracy varied from 1% to 84%, demonstrating that the choice of method is important.

SFCscore(RF): a random forest-based scoring function for improved affinity prediction of protein-ligand complexes

A major shortcoming of empirical scoring functions for protein-ligand complexes is the low degree of correlation between predicted and experimental binding affinities, as frequently observed not only for large and diverse data sets but also for SAR series of individual targets. Improvements can be envisaged by developing new descriptors, employing larger training sets of higher quality, and resorting to more sophisticated regression methods. Herein, we describe the use of SFCscore descriptors to develop an improved scoring function by means of a PDBbind training set of 1005 complexes in combination with random forest for regression. This provided SFCscore(RF) as a new scoring function with significantly improved performance on the PDBbind and CSAR-NRC HiQ benchmarks in comparison to previously developed SFCscore functions. A leave-cluster-out cross-validation and performance in the CSAR 2012 scoring exercise point out remaining limitations but also directions for further improvements of SFCscore(RF) and empirical scoring functions in general.

CSAR benchmark exercise 2011-2012: evaluation of results from docking and relative ranking of blinded congeneric series

The Community Structure-Activity Resource (CSAR) recently held its first blinded exercise based on data provided by Abbott, Vertex, and colleagues at the University of Michigan, Ann Arbor. A total of 20 research groups submitted results for the benchmark exercise where the goal was to compare different improvements for pose prediction, enrichment, and relative ranking of congeneric series of compounds. The exercise was built around blinded high-quality experimental data from four protein targets: LpxC, Urokinase, Chk1, and Erk2. Pose prediction proved to be the most straightforward task, and most methods were able to successfully reproduce binding poses when the crystal structure employed was co-crystallized with a ligand from the same chemical series. Multiple evaluation metrics were examined, and we found that RMSD and native contact metrics together provide a robust evaluation of the predicted poses. It was notable that most scoring functions underpredicted contacts between the hetero atoms (i.e., N, O, S, etc.) of the protein and ligand. Relative ranking was found to be the most difficult area for the methods, but many of the scoring functions were able to properly identify Urokinase actives from the inactives in the series. Lastly, we found that minimizing the protein and correcting histidine tautomeric states positively trended with low RMSD for pose prediction but minimizing the ligand negatively trended. Pregenerated ligand conformations performed better than those that were generated on the fly. Optimizing docking parameters and pretraining with the native ligand had a positive effect on the docking performance as did using restraints, substructure fitting, and shape fitting. Lastly, for both sampling and ranking scoring functions, the use of the empirical scoring function appeared to trend positively with the RMSD. Here, by combining the results of many methods, we hope to provide a statistically relevant evaluation and elucidate specific shortcomings of docking methodology for the community.

Identification of new checkpoint kinase-1 (Chk1) inhibitors by docking, 3D-QSAR, and pharmacophore-modeling methods

Inhibition of checkpoint kinase-1 (Chk1) by small molecules is of great therapeutic interest in the field of oncology and for understanding cell-cycle regulations. This paper presents a model with elements from docking, pharmacophore mapping, the 3D-QSAR approaches CoMFA, CoMSIA and CoRIA, and virtual screening to identify novel hits against Chk1. Docking, 3D-QSAR (CoRIA, CoMFA and CoMSIA), and pharmacophore studies delineate crucial site points on the Chk1 inhibitors, which can be modified to improve activity. The docking analysis showed residues in the proximity of the ligands that are involved in ligand–receptor interactions, whereas CoRIA models were able to derive the magnitude of these interactions that impact the activity. The ligand-based 3D-QSAR methods (CoMFA and CoMSIA) highlight key areas on the molecules that are beneficial and (or) detrimental for activity. The docking studies and 3D-QSAR models are in excellent agreement in terms of binding-site interactions. The pharmacophore hypotheses validated using sensitivity, selectivity, and specificity parameters is a four-point model, characterized by a hydrogen-bond acceptor (A), hydrogen-bond donor (D), and two hydrophobes (H). This map was used to screen a database of 2.7 million druglike compounds, which were pruned to a small set of potential inhibitors by CoRIA, CoMFA, and CoMSIA models with predicted activity in the range of 8.5–10.5 log units.

Discovery of novel checkpoint kinase 1 inhibitors by virtual screening based on multiple crystal structures

Incorporating receptor flexibility is considered crucial for improvement of docking-based virtual screening. With an abundance of crystallographic structures freely available, docking with multiple crystal structures is believed to be a practical approach to cope with protein flexibility. Here we describe a successful application of the docking of multiple structures to discover novel and potent Chk1 inhibitors. Forty-six Chk1 structures were first compared in single structure docking by predicting the binding mode and recovering known ligands. Combinations of different protein structures were then compared by recovery of known ligands and an optimal ensemble of Chk1 structures were selected. The chosen structures were used in the virtual screening of over 60 000 diverse compounds for Chk1 inhibitors. Six novel compounds ranked at the top of the hits list were tested experimentally, and two of these compounds inhibited Chk1 activity-the best with an IC(50) value of 9.6 μM. Further study indicated that achieving a better enrichment and identifying more diverse compounds was more likely using multiple structures than using only a single structure even when protein structures were randomly selected. Taking into account conformational energy difference did not help to improve enrichment in the top ranked list.

Binding studies and quantitative structure-activity relationship of 3-amino-1H-indazoles as inhibitors of GSK3β

Docking of 3-amino-1H-indazoles complexed with glycogen synthase kinase 3 beta (GSK3β) was performed to gain insight into the structural requirements and preferred conformations of these inhibitors. The study was conducted on a selected set of 57 compounds with variation in structure and activity. We found that the most active compounds established three hydrogen bonds with the residues of the hinge region of GSK3β, but some of the less active compounds have other binding modes. In addition, models able to predict GSK3β inhibitory activities (IC(50) ) of the studied compounds were obtained by 3D-QSAR methods CoMFA and CoMSIA. Ligand-based and receptor-guided alignment methods were utilized. Adequate R(2) and Q(2) values were obtained by each method, although some striking differences existed between the obtained contour maps. Each of the predictive models exhibited a similar ability to predict the activity of a test set. The application of docking and quantitative structure-activity relationship together allowed conclusions to be drawn for the choice of suitable GSK3β inhibitors.

Design of targeted libraries against the human Chk1 kinase using PGVL Hub

PGVL Hub is a Pfizer internal desktop tool for chemical library and singleton design. In this chapter, we give a short introduction to PGVL Hub, the core workflow it supports, and the rich design capabilities it provides. By re-creating two legacy targeted libraries against the human checkpoint kinase 1 (Chk1) as a showcase, we illustrate how PGVL Hub could be used to help library designers carry out the steps in library design and realize design objectives such as SAR expansion and improvement in both kinase selectivity and compound aqueous solubility. Finally we share several tips about library design and usage of PGVL Hub.

Identification of inhibitors of checkpoint kinase 1 through template screening

Checkpoint kinase 1 (CHK1) is an oncology target of significant current interest. Inhibition of CHK1 abrogates DNA damage-induced cell cycle checkpoints and sensitizes p53 deficient cancer cells to genotoxic therapies. Using template screening, a fragment-based approach to small molecule hit generation, we have identified multiple CHK1 inhibitor scaffolds suitable for further optimization. The sequential combination of in silico low molecular weight template selection, a high concentration biochemical assay and hit validation through protein-ligand X-ray crystallography provided 13 template hits from an initial in silico screening library of ca. 15000 compounds. The use of appropriate counter-screening to rule out nonspecific aggregation by test compounds was essential for optimum performance of the high concentration bioassay. One low molecular weight, weakly active purine template hit was progressed by iterative structure-based design to give submicromolar pyrazolopyridines with good ligand efficiency and appropriate CHK1-mediated cellular activity in HT29 colon cancer cells.

Investigation of novel 7,8-disubstituted-5,10-dihydro-dibenzo[b,e][1,4]diazepin-11-ones as potent Chk1 inhibitors

The synthesis and structure-activity relationships (SAR) of Chk1 inhibitors based on a 5,10-dihydro-dibenzo[b,e][1,4]diazepin-11-one core are described. Specifically, an exploration of the 7 and 8 positions on this previously disclosed core afforded compounds with improved enzymatic and cellular potency.

Synthesis, checkpoint kinase 1 inhibitory properties and in vitro antiproliferative activities of new pyrrolocarbazoles

In the course of structure-activity relationship studies on granulatimide analogues, new pyrrolo[3,4-c]carbazoles have been synthesized in which the imidazole heterocycle was replaced by a five-membered ring lactam system or a dimethylcyclopentanedione. Moreover, the synthesis of an original structure in which a sugar moiety is attached to the indole nitrogen and to a six-membered D ring via an oxygen is reported. The inhibitory activities of the newly synthesized compounds toward checkpoint kinase 1 and their in vitro antiproliferative activities toward three tumor cell lines: murine leukemia L1210, and human colon carcinoma HT29 and HCT116 are described.

Discovery of 4′-(1,4-dihydro-indeno[1,2-c]pyrazol-3-yl)-benzonitriles and 4′-(1,4-dihydro-indeno[1,2-c]pyrazol-3-yl)-pyridine-2′-carbonitriles as potent checkpoint kinase 1 (Chk1) inhibitors

An extensive structure-activity relationship study of the 3-position of a series of tricyclic pyrazole-based Chk1 inhibitors is described. As a result, 4'-(1,4-dihydro-indeno[1,2-c]pyrazol-3-yl)-benzonitriles (4) and 4'-(1,4-dihydro-indeno[1,2-c]pyrazol-3-yl)-pyridine-2'-carbonitriles (29) emerged as new lead series. Compared with the original lead compound 2, these new leads fully retain the biological activity in both enzymatic inhibition and cell-based assays. More importantly, the new leads 4 and 29 exhibit favorable physicochemical properties such as lower molecular weight, lower Clog P, and the absence of a hydroxyl group. Furthermore, structure-activity relationship studies were performed at the 6- and 7-positions of 4, which led to the identification of ideal Chk1 inhibitors 49, 50, 51, and 55. These compounds not only potently inhibit Chk1 in an enzymatic assay but also significantly potentiate the cytotoxicity of DNA-damaging agents in cell-based assays while they show little single agent activity. A cell cycle analysis by FACS confirmed that these Chk1 inhibitors efficiently abrogate the G2/M and S checkpoints induced by DNA-damaging agent. The current work paved the way to the identification of several potent Chk1 inhibitors with good pharmacokinetics that are suitable for in vivo study with oral dosing.

Cyanopyridyl containing 1,4-dihydroindeno[1,2-c]pyrazoles as potent checkpoint kinase 1 inhibitors: Improving oral biovailability

A series of 1,4-dihydroindeno[1,2-c]pyrazole compounds with a cyanopyridine moiety at the 3-position of the tricyclic pyrazole core was explored as potent CHK-1 inhibitors. The impact of substitutions at the 6 and/or 7-position of the core on pharmacokinetic properties was studied in detail. Compounds carrying a side chain with an ether linker at the 7-position and a terminal morpholino group, such as 29 and 30, exhibited much-improved oral biovailability in mice as compared to earlier generation inhibitors. These compounds also possessed desirable cellular activity in potentiating doxorubicin and will serve as valuable tool compounds for in vivo evaluation of CHK-1 inhibitors to sensitize DNA-damaging agents.

Synthesis and biological evaluation of 4'-(6,7-disubstituted-2,4-dihydro-indeno[1,2-c]pyrazol-3-yl)-biphenyl-4-ol as potent Chk1 inhibitors

A new series of potent tricyclic pyrazole-based Chk1 inhibitors are described. Analogues disubstituted on the 6- and 7-positions show improved Chk1 inhibition potency compared with analogues with a single substituent on either the 6- or 7-position. Based on the lead compound 4'-(6,7-dimethoxy-2,4-dihydro-indeno[1,2-c]pyrazol-3-yl)-biphenyl-4-ol (2), detailed SAR studies on the 6- and 7-positions were performed. 3'-morpholin-4'-yl-propoxy, pyridin-4'-ylmethoxy, pyridin-3'-ylmethoxy, 2'-(5''-ethyl-pyridin-2''-yl)-ethoxy, pyridin-2'-ylethoxy, (6'-methyl-pyridin-2'-yl)-propoxyethoxy, 2',3'-dihydroxyl-1'-yl-propoxy, and tetrahydro-furan-3'-yloxy have been identified as the best groups on the 6-position when the 7-position is substituted with methoxyl group. Pyridin-2'-ylmethoxy and pyridin-3'-ylmethoxy have been identified as the best substituents at the 7-position while the 6-position bearing methoxyl group. These compounds significantly potentiate the cytotoxicity of DNA-damaging antitumor agents in a cell-based assay and efficiently abrogate the doxorubicin-induced G2/M and the camptothecin-induced S checkpoints, suggesting that their potent biological activities are mechanism-based through Chk1 inhibition.