Design, Synthesis, and Molecular Docking of Paracyclophanyl-Thiazole Hybrids as Novel CDK1 Inhibitors and Apoptosis Inducing Anti-Melanoma Agents

Three new series of paracyclophanyl-dihydronaphtho[2,3-d]thiazoles and paracyclophanyl-thiazolium bromides were designed, synthesized, and characterized by their spectroscopic data, along with X-ray analysis. One-dose assay results of anticancer activity indicated that 3a–e had the highest ability to inhibit the proliferation of different cancer cell lines. Moreover, the hybrids 3c–e were selected for five-dose analyses to demonstrate a broad spectrum of antitumor activity without apparent selectivity. Interestingly, series I compounds (Z)-N-substituted-4,9-dihydronaphtho[2,3-d]thiazol-3(2H)-yl)-4′-[2.2]paracyclophanylamide) that are carrying 1,4-dihydronaphthoquinone were more active as antiproliferative agents than their naphthalene-containing congeners (series II: substituted 2-(4′-[2.2]paracyclophanyl)hydrazinyl)-4-(naphth-2-yl)-thiazol-3-ium bromide hybrids) and (series III: 3-(4′-[2.2]paracyclophanyl)amido-2-(cyclopropylamino)-4-(naphth-2-yl)thiazol-3-ium bromide) toward the SK-MEL-5 melanoma cell line. Further antiproliferation investigations of 3c and 3e on the healthy, normal unaffected SK-MEL-5 cell line indicated their relative safety. Compound 3c showed an inhibition of eight isoforms of cyclin-dependent kinases (CDK); however, it exhibited the lowest IC50 of 54.8 nM on CDK1 in comparison to Dinaciclib as a reference. Additionally, compound 3c revealed a remarkable downregulation of phospho-Tyr15 with a level (7.45 pg/mL) close to the reference. 3c mainly showed cell cycle arrest in the pre-G1 and G2/M phases upon analysis of the SK-MEL-5 cell line. The sequential caspase-3 assay for 3c indicated a remarkable overexpression level. Finally, a molecular docking study was adopted to elucidate the binding mode and interactions of the target compounds with CDK1

Design, Synthesis, and Molecular Docking of Paracyclophanyl-Thiazole Hybrids as Novel CDK1 Inhibitors and Apoptosis Inducing Anti-Melanoma Agents

Three new series of paracyclophanyl-dihydronaphtho[2,3-d]thiazoles and paracyclophanyl-thiazolium bromides were designed, synthesized, and characterized by their spectroscopic data, along with X-ray analysis. One-dose assay results of anticancer activity indicated that 3a–e had the highest ability to inhibit the proliferation of different cancer cell lines. Moreover, the hybrids 3c–e were selected for five-dose analyses to demonstrate a broad spectrum of antitumor activity without apparent selectivity. Interestingly, series I compounds (Z)-N-substituted-4,9-dihydronaphtho[2,3-d]thiazol-3(2H)-yl)-4′-[2.2]paracyclophanylamide) that are carrying 1,4-dihydronaphthoquinone were more active as antiproliferative agents than their naphthalene-containing congeners (series II: substituted 2-(4′-[2.2]paracyclophanyl)hydrazinyl)-4-(naphth-2-yl)-thiazol-3-ium bromide hybrids) and (series III: 3-(4′-[2.2]paracyclophanyl)amido-2-(cyclopropylamino)-4-(naphth-2-yl)thiazol-3-ium bromide) toward the SK-MEL-5 melanoma cell line. Further antiproliferation investigations of 3c and 3e on the healthy, normal unaffected SK-MEL-5 cell line indicated their relative safety. Compound 3c showed an inhibition of eight isoforms of cyclin-dependent kinases (CDK); however, it exhibited the lowest IC50 of 54.8 nM on CDK1 in comparison to Dinaciclib as a reference. Additionally, compound 3c revealed a remarkable downregulation of phospho-Tyr15 with a level (7.45 pg/mL) close to the reference. 3c mainly showed cell cycle arrest in the pre-G1 and G2/M phases upon analysis of the SK-MEL-5 cell line. The sequential caspase-3 assay for 3c indicated a remarkable overexpression level. Finally, a molecular docking study was adopted to elucidate the binding mode and interactions of the target compounds with CDK1

DESIGN, SYNTHESIS AND BIOLOGICAL EVALUATION OF NOVEL SELECTIVE CANNABINOID RECEPTOR 2 (CB2) LIGANDS WITH THERAPEUTIC POTENTIALS

Cannabinoid receptors 1 and 2 (CB1 and CB2) belong to the rhodopsin-like family of the G-Protein Coupled Receptors (GPCRs). CB1 receptors are highly expressed in the central nervous system, while CB2 receptors are expressed mainly in the immune cells and the periphery. Targeting the CB2 receptors is believed to avoid the psychoactive side effects associated with CB1 receptors. CB2 receptors have been shown to be involved in several physiological functions as well as diseases, such as pain, multiple sclerosis, osteoporosis, and cancer demonstrating the importance of the CB2 receptors. In the present study, we employed chemistry design and discovery to identify novel CB2 ligands, carried out in-vitro functional studies, and evaluated the therapeutic potentials. Several chemical scaffolds were discovered and evaluated. The di-amide scaffold was discovered utilizing pharmacophore drug discovery and molecular docking studies. Several derivatives of the di-amide scaffold demonstrated potent and highly selective CB2 inverse agonists as well as potent anti-osteoclast formation capabilities. The di-amide derivatives suffered from weak anti-multiple myeloma (MM) properties and poor pharmacokinetic properties. A new scaffold was identified utilizing scaffold hopping and molecular docking studies. However, the 2-(sulfonylamino)-2-phenylacetamide scaffold demonstrated weak CB2 binding affinity. Due to the limitation of the two previous scaffolds, virtual high-throughput screening as well as structure-based drug design were utilized for scaffold hopping in order to identify new CB2 scaffolds. A new lead compound was identified and structure activity relationship (SAR) studies were conducted on the scaffold 4-(aminomethyl)-N,N-diethylaniline. Several novel compounds were discovered with high potency and selectivity. Functional experiments showed different functionality (agonist and inverse agonist) of these compounds. Nevertheless, therapeutic studies showed that inverse agonism is essential for the OCL inhibition effects while anti-MM experiments showed that CB2 agonists are more effective than inverse agonists

MDP, a database linking drug response data to genomic information, identifies dasatinib and statins as a combinatorial strategy to inhibit YAP/TAZ in cancer cells

Targeted anticancer therapies represent the most effective pharmacological strategies in terms of clinical responses. In this context, genetic alteration of several oncogenes represents an optimal predictor of response to targeted therapy. Integration of large-scale molecular and pharmacological data from cancer cell lines promises to be effective in the discovery of new genetic markers of drug sensitivity and of clinically relevant anticancer compounds. To define novel pharmacogenomic dependencies in cancer, we created the Mutations and Drugs Portal (MDP, http://mdp.unimore.it), a web accessible database that combines the cell-based NCI60 screening of more than 50,000 compounds with genomic data extracted from the Cancer Cell Line Encyclopedia and the NCI60 DTP projects. MDP can be queried for drugs active in cancer cell lines carrying mutations in specific cancer genes or for genetic markers associated to sensitivity or resistance to a given compound. As proof of performance, we interrogated MDP to identify both known and novel pharmacogenomics associations and unveiled an unpredicted combination of two FDA-approved compounds, namely statins and Dasatinib, as an effective strategy to potently inhibit YAP/TAZ in cancer cells

COMPUTATIONAL DESIGN OF 3-PHOSPHOINOSITIDE DEPENDENT KINASE-1 INHIBITORS AS POTENTIAL ANTI-CANCER AGENTS

Computational drug design methods have great potential in drug discovery particularly in lead identification and lead optimization. 3-Phosphoinositide dependent kinase-1 (PDK1) is a protein kinase and a well validated anti-cancer target. Inhibitors of PDK1 have the potential to be developed as anti-cancer drugs. In this work, we have applied various novel computational drug design strategies to design and identify new PDK1 inhibitors with potential anti-cancer activity. We have pursued novel structure-based drug design strategies and identified a new binding mode for celecoxib and its derivatives binding with PDK1. This new binding mode provides a valuable basis for rational design of potent PDK1 inhibitors. In order to understand the structure-activity relationship of indolinone-based PDK1 inhibitors, we have carried out a combined molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling study. The predictive ability of the developed 3D-QSAR models were validated using an external test set of compounds. An efficient strategy of the hierarchical virtual screening with increasing complexity was pursued to identify new hits against PDK1. Our approach uses a combination of ligand-based and structure-based virtual screening including shape-based filtering, rigid docking, and flexible docking. In addition, a more sophisticated molecular dynamics/molecular mechanics- Poisson-Boltzmann surface area (MD/MM-PBSA) analysis was used as the final filter in the virtual screening. Our screening strategy has led to the identification of a new PDK1 inhibitor. The anticancer activities of this compound have been confirmed by the anticancer activity assays of national cancer institute-developmental therapeutics program (NCI-DTP) using 60 cancer cell lines. The PDK1-inhibitor binding mode determined in this study may be valuable in future de novo drug design. The virtual screening approach tested and used in this study could also be applied to lead identification in other drug discovery efforts

Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian hierarchical approach

Cellular response to a perturbation is the result of a dynamic system of biological variables linked in a complex network. A major challenge in drug and disease studies is identifying the key factors of a biological network that are essential in determining the cell's fate. Here our goal is the identification of perturbed pathways from high-throughput gene expression data. We develop a three-level hierarchical model, where (i) the first level captures the relationship between gene expression and biological pathways using confirmatory factor analysis, (ii) the second level models the behavior within an underlying network of pathways induced by an unknown perturbation using a conditional autoregressive model, and (iii) the third level is a spike-and-slab prior on the perturbations. We then identify perturbations through posterior-based variable selection. We illustrate our approach using gene transcription drug perturbation profiles from the DREAM7 drug sensitivity predication challenge data set. Our proposed method identified regulatory pathways that are known to play a causative role and that were not readily resolved using gene set enrichment analysis or exploratory factor models. Simulation results are presented assessing the performance of this model relative to a network-free variant and its robustness to inaccuracies in biological databases

Uniformly curated signaling pathways reveal tissue-specific cross-talks and support drug target discovery

Motivation: Signaling pathways control a large variety of cellular processes. However, currently, even within the same database signaling pathways are often curated at different levels of detail. This makes comparative and cross-talk analyses difficult. Results: We present SignaLink, a database containing 8 major signaling pathways from Caenorhabditis elegans, Drosophila melanogaster, and humans. Based on 170 review and approx. 800 research articles, we have compiled pathways with semi-automatic searches and uniform, well-documented curation rules. We found that in humans any two of the 8 pathways can cross-talk. We quantified the possible tissue- and cancer-specific activity of cross-talks and found pathway-specific expression profiles. In addition, we identified 327 proteins relevant for drug target discovery. Conclusions: We provide a novel resource for comparative and cross-talk analyses of signaling pathways. The identified multi-pathway and tissue-specific cross-talks contribute to the understanding of the signaling complexity in health and disease and underscore its importance in network-based drug target selection. Availability: http://SignaLink.orgComment: 9 pages, 4 figures, 2 tables and a supplementary info with 5 Figures and 13 Table

The discovery of potential acetylcholinesterase inhibitors: A combination of pharmacophore modeling, virtual screening, and molecular docking studies

<p>Abstract</p> <p>Background</p> <p>Alzheimer's disease (AD) is the most common cause of dementia characterized by progressive cognitive impairment in the elderly people. The most dramatic abnormalities are those of the cholinergic system. Acetylcholinesterase (AChE) plays a key role in the regulation of the cholinergic system, and hence, inhibition of AChE has emerged as one of the most promising strategies for the treatment of AD.</p> <p>Methods</p> <p>In this study, we suggest a workflow for the identification and prioritization of potential compounds targeted against AChE. In order to elucidate the essential structural features for AChE, three-dimensional pharmacophore models were constructed using Discovery Studio 2.5.5 (DS 2.5.5) program based on a set of known AChE inhibitors.</p> <p>Results</p> <p>The best five-features pharmacophore model, which includes one hydrogen bond donor and four hydrophobic features, was generated from a training set of 62 compounds that yielded a correlation coefficient of R = 0.851 and a high prediction of fit values for a set of 26 test molecules with a correlation of R²= 0.830. Our pharmacophore model also has a high Güner-Henry score and enrichment factor. Virtual screening performed on the NCI database obtained new inhibitors which have the potential to inhibit AChE and to protect neurons from Aβ toxicity. The hit compounds were subsequently subjected to molecular docking and evaluated by consensus scoring function, which resulted in 9 compounds with high pharmacophore fit values and predicted biological activity scores. These compounds showed interactions with important residues at the active site.</p> <p>Conclusions</p> <p>The information gained from this study may assist in the discovery of potential AChE inhibitors that are highly selective for its dual binding sites.</p