4-arylazo-3,5-diamino-1H-pyrazole CDK inhibitors: SAR study, crystal structure in complex with CDK2, selectivity, and cellular effects

Targeting cyclin-dependent kinases: From pocket specificity to drug selectivity

The development of selective modulators of cyclin-dependent kinases (CDKs), a kinase family with numerous members and functional variations, is a significant preclinical challenge. Recent advancements in crystallography have revealed subtle differences in the highly conserved CDK pockets. Exploiting these differences has proven to be an effective strategy for achieving excellent drug selectivity. While previous reports briefly discussed the structural features that lead to selectivity in individual CDK members, attaining inhibitor selectivity requires consideration of not only the specific structures of the target CDK but also the features of off-target members. In this review, we summarize the structure-activity relationships (SARs) that influence selectivity in CDK drug development and analyze the pocket features that lead to selectivity using molecular-protein binding models. In addition, in recent years, novel CDK modulators have been developed, providing more avenues for achieving selectivity. These cases were also included. We hope that these efforts will assist in the development of novel CDK drugs.

A new polyazomethine-based pyrazole moiety and its reinforced nanocomposites @ ZnO for antimicrobial applications

A new class of biologically active polyazomethine/pyrazole and their related nanocomposites, polyazomethine/pyrazole/zinc oxide nanoparticles, have been successfully synthesized through the polycondensation technique in the form of polyazomethine pyrazole (PAZm/Py4-6) and polyazomethine/pyrazole/zinc oxide nanoparticles (PAZm/Py/ZnOa-c). The polymeric nanocomposites were prepared with a 5% loading of zinc oxide nanofiller using the same preparation technique, in addition to the help of ultrasonic radiation. The characteristics of the new polymers, such as solubility, viscometry, and molecular weight, were examined. All the polymers were completely soluble in the following solvents: concentrated sulfuric acid, formic acid, dimethylformamide, dimethyl sulfoxide, and tetrahydrofuran. Furthermore, the weight loss of the polyazomethine pyrazole (4, 5, and 6) at 800 °C was 67%, 95%, and 86%, respectively, which indicates the thermal stability of these polymers. At 800 °C, the polyazomethine/pyrazole/zinc oxide nanoparticles (a, b, and c) lost 74%, 68%, and 75% of their weight, respectively. This shows that adding zinc oxide nanoparticles made these compounds more stable at high temperatures. The X-Ray diffraction pattern of the polyazomethine pyrazole (PAZm/Py4-6) shows a number of sharp peaks with varying intensities. The polymers that were studied had straight crystal structures. Furthermore, the measurements of polyazomethine/pyrazole/zinc oxide nanoparticles (PAZm/Py/ZnOa-c) indicate a good merging of zinc oxide nanoparticles into the matrix of polymers. The antimicrobial activity of polymers and polymer nanocomposites was tested against some selected bacteria and fungi. The synthesized polymer (c) shows the highest activity against the two types of gram-negative bacteria selected. Most tested compounds were found to be effective against gram-positive bacteria except polyazomethine pyrazole (PAZm/Py5) and polyazomethine pyrazole (PAZm/Py6), which do not exhibit any activity. The synthesized polymers and their related nanocomposites were tested for their ability to kill the chosen fungi. All of them were effective against Aspergillus flavus, but only polyazomethine pyrazole (PAZm/Py4) and polyazomethine/pyrazole/zinc oxide (PAZm/Py/ZnOc) were effective against Candida albicans.

Design, synthesis, and biological evaluation of dinaciclib and CAN508 hybrids as CDK inhibitors

The scaffolds of two known CDK inhibitors (CAN508 and dinaciclib) were the starting point for synthesizing two series of pyarazolo[1,5-a]pyrimidines to obtain potent inhibitors with proper selectivity. The study presented four promising compounds; 10d, 10e, 16a, and 16c based on cytotoxic studies. Compound 16a revealed superior activity in the preliminary anticancer screening with GI % = 79.02-99.13 against 15 cancer cell lines at 10 μM from NCI full panel 60 cancer cell lines and was then selected for further investigation. Furthermore, the four compounds revealed good safety profile toward the normal cell lines WI-38. These four compounds were subjected to CDK inhibitory activity against four different isoforms. All of them showed potent inhibition against CDK5/P25 and CDK9/CYCLINT. Compound 10d revealed the best activity against CDK5/P25 (IC50 = 0.063 µM) with proper selectivity index against CDK1 and CDK2. Compound 16c exhibited the highest inhibitory activity against CDK9/CYCLINT (IC50 = 0.074 µM) with good selectivity index against other isoforms. Finally, docking simulations were performed for compounds 10e and 16c accompanied by molecular dynamic simulations to understand their behavior in the active site of the two CDKs with respect to both CAN508 and dinaciclib.

Amino-Pyrazoles in Medicinal Chemistry: A Review

A pyrazole nucleus is an easy-to-prepare scaffold with large therapeutic potential. Consequently, the search for new pyrazole-based compounds is of great interest to the academic community as well as industry. In the last ten years, a large number of papers and reviews on the design, synthesis, and biological evaluation of different classes of pyrazoles and many pyrazole-containing compounds have been published. However, an overview of pyrazole derivatives bearing a free amino group at the 3, 4, or 5 position (namely, 3-aminopyrazoles, 4-aminopyrazoles, and 5-aminopyrazoles, respectively) and their biological properties is still missing, despite the fact that aminopyrazoles are advantageous frameworks able to provide useful ligands for receptors or enzymes, such as p38MAPK, and different kinases, COX and others, as well as targets important for bacterial and virus infections. With the aim to fill this gap, the present review focuses on aminopyrazole-based compounds studied as active agents in different therapeutic areas, with particular attention on the design and structure-activity relationships defined by each class of compounds. In particular, the most relevant results have been obtained for anticancer/anti-inflammatory compounds, as the recent approval of Pirtobrutinib demonstrates. The data reported here are collected from different databases (Scifinder, Web of Science, Scopus, Google Scholar, and Pubmed) using "aminopyrazole" as the keyword.

Recent Advancement in Drug Design and Discovery of Pyrazole Biomolecules as Cancer and Inflammation Therapeutics

Pyrazole, an important pharmacophore and a privileged scaffold of immense significance, is a five-membered heterocyclic moiety with an extensive therapeutic profile, viz., anti-inflammatory, anti-microbial, anti-anxiety, anticancer, analgesic, antipyretic, etc. Due to the expansion of pyrazolecent red pharmacological molecules at a quicker pace, there is an urgent need to put emphasis on recent literature with hitherto available information to recognize the status of this scaffold for pharmaceutical research. The reported potential pyrazole-containing compounds are highlighted in the manuscript for the treatment of cancer and inflammation, and the results are mentioned in % inhibition of inflammation, % growth inhibition, IC₅₀, etc. Pyrazole is an important heterocyclic moiety with a strong pharmacological profile, which may act as an important pharmacophore for the drug discovery process. In the struggle to cultivate suitable anti-inflammatory and anticancer agents, chemists have now focused on pyrazole biomolecules. This review conceals the recent expansion of pyrazole biomolecules as anti-inflammatory and anticancer agents with an aim to provide better correlation among different research going around the world.

Targeting cyclin-dependent kinase 9 in cancer therapy

Cyclin-dependent kinase (CDK) 9 associates mainly with cyclin T1 and forms the positive transcription elongation factor b (p-TEFb) complex responsible for transcriptional regulation. It has been shown that CDK9 modulates the expression and activity of oncogenes, such as MYC and murine double minute 4 (MDM4), and it also plays an important role in development and/or maintenance of the malignant cell phenotype. Malfunction of CDK9 is frequently observed in numerous cancers. Recent studies have highlighted the function of CDK9 through a variety of mechanisms in cancers, including the formation of new complexes and epigenetic alterations. Due to the importance of CDK9 activation in cancer cells, CDK9 inhibitors have emerged as promising candidates for cancer therapy. Natural product-derived and chemically synthesized CDK9 inhibitors are being examined in preclinical and clinical research. In this review, we summarize the current knowledge on the role of CDK9 in transcriptional regulation, epigenetic regulation, and different cellular factor interactions, focusing on new advances. We show the importance of CDK9 in mediating tumorigenesis and tumor progression. Then, we provide an overview of some CDK9 inhibitors supported by multiple oncologic preclinical and clinical investigations. Finally, we discuss the perspective and challenge of CDK9 modulation in cancer.

Natural Protein Kinase Inhibitors, Staurosporine, and Chelerythrine Suppress Wheat Blast Disease Caused by Magnaporthe oryzae Triticum

Protein kinases (PKs), being key regulatory enzymes of a wide range of signaling pathways, are potential targets for antifungal agents. Wheat blast disease, caused by Magnaporthe oryzae Triticum (MoT), is an existential threat to world food security. During the screening process of natural metabolites against MoT fungus, we find that two protein kinase inhibitors, staurosporine and chelerythrine chloride, remarkably inhibit MoT hyphal growth. This study further investigates the effects of staurosporine and chelerythrine chloride on MoT hyphal growth, conidia production, and development as well as wheat blast inhibition in comparison to a commercial fungicide, Nativo^®75WG. The growth of MoT mycelia is significantly inhibited by these compounds in a dose-dependent manner. These natural compounds greatly reduce conidia production in MoT mycelia along with suppression of conidial germination and triggered lysis, resulting in deformed germ tubes and appressoria. These metabolites greatly suppress blast development in artificially inoculated wheat plants in the field. This is the first report of the antagonistic effect of these two natural PKC inhibitory alkaloids on MoT fungal developmental processes in vitro and suppression of wheat blast disease on both leaves and spikes in vivo. Further research is needed to identify their precise mechanism of action to consider them as biopesticides or lead compounds for controlling wheat blast.

Applications of Choline Chlorine based Deep Eutectic Solvents as Sustainable Media and catalyst in the synthesis of Heterocyclic Scaffolds

Abstract:

Deep eutectic solvents (DESs), also referred to as low transition temperature mixtures (LTTMs), have emerged as sustainable and cheap alternatives to conventional organic solvents in organic synthesis. This is attributed to their exceptional characteristics viz. easy preparation with readily available cheap materials, water compatibility, non-flammability, non-toxicity, biocompatibility, biodegradability, etc. All these properties label them as versatile and cost-effective green solvents. The first reported DES, choline chloride urea mixture has appeared as an innocuous solvent and catalyst in many organic transformations. This prospective DES combination has been applied extensively to the synthesis of a wide range of heterocyclic compounds including quinolones, spirooxindoles, etc. The conditions employed are relatively mild and do not require additional acid catalysts or organic solvents. This eco-friendly blend for the synthesis of heterocycles reports excellent yields of products with shorter reaction times and a simple workup procedure. Evaluating these merits, this review focuses on the recent literature published on the use of choline chlorine-based DESs in the synthesis of a few important heterocyclic compounds.

Conventional and microwave-assisted synthesis, anticancer evaluation, 99mTc-coupling and In-vivo study of some novel pyrazolone derivatives

New pyrazolone derivatives were successfully synthesized by both microwave-assisted and conventional techniques. Compound 3 (3-(3-Methyl-5-oxo-4,5-dihydro-1H-pyrazol-1-yl)-3-oxopropanehydrazide) displayed remarkable anti-cancer activity (IC₅₀ obtained at 8.71 and 10.63 µM for HCT-116 and MCF-7, respectively. Moreover, biodistribution study using radiolabeling approach revealed a remarked uptake of [^99mTc]Tc-compound 3 complex into tumour induced in mice. The biodistribution showed high accumulation in tumour tissues with T/NT of 6.92 after 60 min post injection. As a result of these promising data, the newly synthesized compounds especially compound 3 affords a potential radio-carrier that could be used as a tumour marker and can be used for cancer therapy after further preclinical studies.

Identification of Prognostic Biomarkers in Papillary Thyroid Cancer and Developing Non-Invasive Diagnostic Models Through Integrated Bioinformatics Analysis

BACKGROUND

Papillary thyroid cancer (PTC) is the most frequent subtype of thyroid carcinoma, mainly detected in patients with benign thyroid nodules (BTN). Due to the invasiveness of accurate diagnostic tests, there is a need to discover applicable biomarkers for PTC. So, in this study, we aimed to identify the genes associated with prognosis in PTC. Besides, we performed a machine learning tool to develop a non-invasive diagnostic approach for PTC.

METHODS

For the study purposes, the miRNA dataset GSE130512 was downloaded from the GEO database and then analyzed to identify the common differentially expressed miRNAs in patients with non-metastatic PTC (nm-PTC)/metastatic PTC (m-PTC) compared with BTNs. The SVM was also applied to differentiate patients with PTC from those patients with BTN using the common DEMs. A protein-protein interaction network was also constructed based on the targets of the common DEMs. Next, functional analysis was performed, the hub genes were determined, and survival analysis was then executed.

RESULTS

A total of three common miRNAs were found to be differentially expressed among patients with nm-PTC/m-PTC compared with BTNs. In addition, it was established that the autophagosome maturation, ciliary basal body-plasma membrane docking, antigen processing as ubiquitination & proteasome degradation, and class I MHC mediated antigen processing & presentation are associated with the pathogenesis of PTC. Furthermore, it was illustrated that RPS6KB1, CCNT1, SP1, and CHD4 might serve as new potential biomarkers for PTC prognosis.

CONCLUSION

RPS6KB1, CCNT1, SP1, and CHD4 may be considered new potential biomarkers used for prognostic aims in PTC. However, performing validation tests is inevitable in the future.

SAR study of 4-arylazo-3,5-diamino-1H-pyrazoles: identification of small molecules that induce dispersal of Pseudomonas aeruginosa biofilms

By screening of a collection of 50 000 small-molecule compounds, we recently identified 4-arylazo-3,5-diamino-1H-pyrazoles as a novel group of anti-biofilm agents. Here, we report a SAR study based on 60 analogues by examining ways in which the pharmacophore can be further optimized, for example, via substitutions in the aryl ring. The SAR study revealed the very potent anti-biofilm compound 4-(2-(2-fluorophenyl)hydrazineylidene)-5-imino-4,5-dihydro-1H-pyrazol-3-amine (2).

Design, synthesis, molecular modeling, and antimicrobial potential of novel 3-[(1H-pyrazol-3-yl)imino]indolin-2-one derivatives as DNA gyrase inhibitors

A series of 3-[(1H-pyrazol-3-yl)imino]indolin-2-one derivatives were designed using the molecular hybridization method, characterized using different spectroscopic techniques, and evaluated for their in vitro antimicrobial activity. Most of the target compounds demonstrated good to moderate antimicrobial activity compared with ciprofloxacin and fluconazole. Four compounds (8b, 9a, 9c, and 10a) showed encouraging results, with minimal inhibitory concentration (MIC) values (53.45-258.32 µM) comparable to those of norfloxacin (100.31-200.63 µM) and ciprofloxacin (48.33-96.68 µM). Noticeably, the four derivatives revealed excellent bactericidal and fungicidal activities, except for the bacteriostatic potential of compounds 8b and 9a against Escherichia coli and Staphylococcus aureus, respectively. The time-killing kinetic study against S. aureus confirmed the efficacy of these derivatives. Furthermore, two of the four promising derivatives, 9a and 10a, could prevent the formation of biofilms of S. aureus without affecting the bacterial growth at low concentrations. A combination study with seven commercial antibiotics against the multidrug-resistant bacterium P. aeruginosa showed a notable reduction in the antibiotic MIC values, represented mainly through a synergistic or additive effect. The enzymatic assay implied that the most active derivatives had inhibition potency against DNA gyrase comparable to that of ciprofloxacin. Molecular docking and density functional theory calculations were performed to explore the binding mode and study the reactivity of the promising compounds.

Synthesis, in vitro anticancer activity and in silico studies of certain pyrazole-based derivatives as potential inhibitors of cyclin dependent kinases (CDKs)

New diphenyl-1H-pyrazoles were synthesized and screened for CDK2 inhibition where 8d, 9b, 9c, and 9e exhibited promising activity (IC₅₀ = 51.21, 41.36, 29.31, and 40.54 nM respectively) compared to R-Roscovitine (IC₅₀ = 43.25 nM). Furthermore, preliminary anti-proliferative activity screening of some selected compounds on 60 cancer cell lines was performed at the (NCI/USA). Compounds 8a-c displayed promising growth inhibitory activity (mean %GI; 73.74, 94.32 and 74.19, respectively). Additionally, they were further selected by the NCI for five-dose assay, exhibiting pronounced activity against almost the full panel (GI₅₀ ranges; 0.181-5.19, 1.07-4.12 and 1.07-4.82 µM, respectively) and (Full panel GI₅₀ (MG-MID); 2.838, 2.306 and 2.770 µM, respectively). Screening the synthesized compounds 8a-c for inhibition of CDK isoforms revealed that compound 8a exhibited nearly equal inhibition to all the tested CDK isoforms, while compound 8b inhibits CDK4/D1 preferentially than the other isoforms and compound 8c inhibits CDK1, CDK2 and CDK4 more than CDK7. Flow cytometry cell cycle assay of 8a-c on Non-small cell lung carcinoma (NSCL HOP-92) cell line revealed S phase arrest by 8a and G1/S phase arrest by 8b and 8c. Apoptotic induction in HOP-92 cell line was also observed upon treatment with compounds 8a-c. Docking to CDK2 ATP binding site revealed similar interactions as the co-crystallized ligand R-Roscovitine (PDB code; 3ddq). These findings present compounds 8a-c as promising anti-proliferative agents.

Computational Prediction of Binding Affinity for CDK2-ligand Complexes. A Protein Target for Cancer Drug Discovery

BACKGROUND

CDK2 participates in the control of eukaryotic cell-cycle progression. Due to the great interest in CDK2 for drug development and the relative easiness in crystallizing this enzyme, we have over 400 structural studies focused on this protein target. This structural data is the basis for the development of computational models to estimate CDK2-ligand binding affinity.

OBJECTIVE

This work focuses on the recent developments in the application of supervised machine learning modeling to develop scoring functions to predict the binding affinity of CDK2.

METHOD

We employed the structures available at the protein data bank and the ligand information accessed from the BindingDB, Binding MOAD, and PDBbind to evaluate the predictive performance of machine learning techniques combined with physical modeling used to calculate binding affinity. We compared this hybrid methodology with classical scoring functions available in docking programs.

RESULTS

Our comparative analysis of previously published models indicated that a model created using a combination of a mass-spring system and cross-validated Elastic Net to predict the binding affinity of CDK2-inhibitor complexes outperformed classical scoring functions available in AutoDock4 and AutoDock Vina.

CONCLUSION

All studies reviewed here suggest that targeted machine learning models are superior to classical scoring functions to calculate binding affinities. Specifically for CDK2, we see that the combination of physical modeling with supervised machine learning techniques exhibits improved predictive performance to calculate the protein-ligand binding affinity. These results find theoretical support in the application of the concept of scoring function space.

Synthesis of 4-styrylpyrazoles and evaluation of their inhibitory effects on cyclin-dependent kinases

BACKGROUND

Cycle-regulating and transcriptional cyclin-dependent kinases (CDKs) are attractive targets in cancer drug development. Several CDK inhibitors have already been obtained or are close to regulatory approval for clinical applications.

OBJECTIVE

Phenylazopyrazole CAN508 has been described as the first selective CDK9 inhibitor with an IC50 of 350 nM. Since the azo-moiety is not a suitable functionality for drugs due to pharmacological reasons, the preparation of carbo-analogues of CAN508 with similar biological activities is desirable. The present work is focused on the synthesis of carbo-analogues similar to CAN508 and their CDK inhibition activity.

METHODS

Herein, the synthesis of 21 novel carbo analogues of CAN508 and their intermediates is reported. Subsequently, target compounds 8a - 8u were evaluated for protein kinase inhibition (CDK2/cyclin E, CDK4/cyclin D, CDK9/cyclin T) and antiproliferative activities in cell lines (K562, MCF-7, MV4-11). Moreover, the binding mode of derivative 8s in the active site of CDK9 was revealed by molecular docking.

RESULTS

Compounds 8a - 8u were obtained from key intermediate 7, which was prepared by linear synthesis involving Vilsmeier-Haack, Knoevenagel, Hunsdiecker, and Suzuki-Miyaura reactions. Styrylpyrazoles 8t and 8u were the most potent CDK9 inhibitors with IC50 values of approximately 1 µM. Molecular modelling suggested binding in the active site of CDK9 and CDK2. The flow cytometric analysis of MV4-11 cells treated with the most active styrylpyrazoles showed a significant G1-arrest.

CONCLUSION

The prepared styrylpyrazoles showed inhibition activity towards CDKs and can provide a novel chemotype of kinase inhibitors.

Identification of small molecules that interfere with c-di-GMP signaling and induce dispersal of Pseudomonas aeruginosa biofilms

Microbial biofilms are involved in a number of infections that cannot be cured, as microbes in biofilms resist host immune defenses and antibiotic therapies. With no strict biofilm-antibiotic in the current pipelines, there is an unmet need for drug candidates that enable the current antibiotics to eradicate bacteria in biofilms. We used high-throughput screening to identify chemical compounds that reduce the intracellular c-di-GMP content in Pseudomonas aeruginosa. This led to the identification of a small molecule that efficiently depletes P. aeruginosa for c-di-GMP, inhibits biofilm formation, and disperses established biofilm. A combination of our lead compound with standard of care antibiotics showed improved eradication of an implant-associated infection established in mice. Genetic analyses provided evidence that the anti-biofilm compound stimulates the activity of the c-di-GMP phosphodiesterase BifA in P. aeruginosa. Our work constitutes a proof of concept for c-di-GMP phosphodiesterase-activating drugs administered in combination with antibiotics as a viable treatment strategy for otherwise recalcitrant infections.

Novel pyrrolizines bearing 3,4,5-trimethoxyphenyl moiety: design, synthesis, molecular docking, and biological evaluation as potential multi-target cytotoxic agents

In the present study, two new series of pyrrolizines bearing 3,4,5-trimethoxyphenyl moiety were designed, synthesised, and evaluated for their cytotoxic activity. The benzamide derivatives 16a-e showed higher cytotoxicity than their corresponding Schiff bases 15a-e. Compounds 16a,b,d also inhibited the growth of MCF-7/ADR cells with IC₅₀ in the range of 0.52-6.26 μM. Interestingly, the new compounds were less cytotoxic against normal MRC-5 cells (IC₅₀=0.155-17.08 μM). Mechanistic studies revealed the ability of compounds 16a,b,d to inhibit tubulin polymerisation and multiple oncogenic kinases. Moreover, compounds 16a,b,d induced preG₁ and G₂/M cell cycle arrest and early apoptosis in MCF-7 cells. The molecular docking analyses of compounds 16a,b,d into the active site in tubulin, CDK-2, and EGFR proteins revealed higher binding affinities compared to the co-crystallised ligands. These preliminary results suggested that compounds 16a,b,d could serve as promising lead compounds for the future development of new potent anticancer agents.HighlightsTwo new series of pyrrolizines bearing 3,4,5-trimethoxyphenyl moieties were synthesized.Compounds 16a,b,d displayed the highest cytotoxicity against the three cancer cell lines.Kinase profiling test revealed inhibition of multiple oncogenic kinases by compounds 16a,b,d.Compounds 16a,b,d exhibited weak to moderate inhibition of tubulin-polymerization.Compounds 16a,b,d induced preG₁ and G₂/M cell cycle arrest and early apoptosis in MCF-7 cells.Docking studies revealed high binding affinities for compounds 16a,b towards tubulin and CDK-2.

Machine Learning-Based Scoring Functions, Development and Applications with SAnDReS

BACKGROUND

Analysis of atomic coordinates of protein-ligand complexes can provide three-dimensional data to generate computational models to evaluate binding affinity and thermodynamic state functions. Application of machine learning techniques can create models to assess protein-ligand potential energy and binding affinity. These methods show superior predictive performance when compared with classical scoring functions available in docking programs.

OBJECTIVE

Our purpose here is to review the development and application of the program SAnDReS. We describe the creation of machine learning models to assess the binding affinity of protein-ligand complexes.

METHODS

SAnDReS implements machine learning methods available in the scikit-learn library. This program is available for download at https://github.com/azevedolab/sandres. SAnDReS uses crystallographic structures, binding and thermodynamic data to create targeted scoring functions.

RESULTS

Recent applications of the program SAnDReS to drug targets such as Coagulation factor Xa, cyclin-dependent kinases and HIV-1 protease were able to create targeted scoring functions to predict inhibition of these proteins. These targeted models outperform classical scoring functions.

CONCLUSION

Here, we reviewed the development of machine learning scoring functions to predict binding affinity through the application of the program SAnDReS. Our studies show the superior predictive performance of the SAnDReS-developed models when compared with classical scoring functions available in the programs such as AutoDock4, Molegro Virtual Docker and AutoDock Vina.

Small Molecule CDK Inhibitors for the Therapeutic Management of Cancer

Cyclin-dependent kinases (CDKs) are a group of multifunctional enzymes consisting of catalytic and regulatory subunits. The regulatory subunit, cyclin, remains dissociated under normal circumstances, and complexation of cyclin with the catalytic subunit of CDK leads to its activation for phosphorylation of protein substrates. The primary role of CDKs is in the regulation of the cell cycle. Retinoblastoma protein (Rb) is one of the widely investigated tumor suppressor protein substrates of CDK, which prevents cells from entering into cell-cycle under normal conditions. Phosphorylation of Rb by CDKs causes its inactivation and ultimately allows cells to enter a new cell cycle. Many cancers are associated with hyperactivation of CDKs as a result of mutation of the CDK genes or CDK inhibitor genes. Therefore, CDK modulators are of great interest to explore as novel therapeutic agents against cancer and led to the discovery of several CDK inhibitors to clinics. This review focuses on the current progress and development of anti-cancer CDK inhibitors from preclinical to clinical and synthetic to natural small molecules.

Application of Machine Learning Techniques to Predict Binding Affinity for Drug Targets: A Study of Cyclin-Dependent Kinase 2

BACKGROUND

The elucidation of the structure of cyclin-dependent kinase 2 (CDK2) made it possible to develop targeted scoring functions for virtual screening aimed to identify new inhibitors for this enzyme. CDK2 is a protein target for the development of drugs intended to modulate cellcycle progression and control. Such drugs have potential anticancer activities.

OBJECTIVE

Our goal here is to review recent applications of machine learning methods to predict ligand- binding affinity for protein targets. To assess the predictive performance of classical scoring functions and targeted scoring functions, we focused our analysis on CDK2 structures.

METHODS

We have experimental structural data for hundreds of binary complexes of CDK2 with different ligands, many of them with inhibition constant information. We investigate here computational methods to calculate the binding affinity of CDK2 through classical scoring functions and machine- learning models.

RESULTS

Analysis of the predictive performance of classical scoring functions available in docking programs such as Molegro Virtual Docker, AutoDock4, and Autodock Vina indicated that these methods failed to predict binding affinity with significant correlation with experimental data. Targeted scoring functions developed through supervised machine learning techniques showed a significant correlation with experimental data.

CONCLUSION

Here, we described the application of supervised machine learning techniques to generate a scoring function to predict binding affinity. Machine learning models showed superior predictive performance when compared with classical scoring functions. Analysis of the computational models obtained through machine learning could capture essential structural features responsible for binding affinity against CDK2.

Pharmacophore hybridization approach to discover novel pyrazoline-based hydantoin analogs with anti-tumor efficacy

In search for new and safer anti-cancer agents, a structurally guided pharmacophore hybridization strategy of two privileged scaffolds, namely diaryl pyrazolines and imidazolidine-2,4-dione (hydantoin), was adopted resulting in a newfangled series of compounds (H1-H22). Herein, a bio-isosteric replacement of "pyrrolidine-2,5-dione" moiety of our recently reported antitumor hybrid incorporating diaryl pyrazoline and pyrrolidine-2,5-dione scaffolds with "imidazoline-2,4-dione" moiety has been incorporated. Complete biological studies revealed the most potent analog among all i.e. compound H13, which was at-least 10-fold more potent compared to the corresponding pyrrolidine-2,5-dione, in colon and breast cancer cells. In-vitro studies showed activation of caspases, arrest of G0/G1 phase of cell cycle, decrease in the expression of anti-apoptotic protein (Bcl-2) and increased DNA damage. In-vivo assay on HT-29 (human colorectal adenocarcinoma) animal xenograft model unveiled the significant anti-tumor efficacy along with oral bioavailability with maximum TGI 36% (i.p.) and 44% (per os) at 50 mg/kg dose. These findings confirm the suitability of hybridized pyrazoline and imidazolidine-2,4-dione analog H13 for its anti-cancer potential and starting-point for the development of more efficacious analogs.

Synthesis of new arylazopyrazoles as apoptosis inducers: Candidates to inhibit proliferation of MCF-7 cells

New 4-arylazo-3,5-diamino-1H-pyrazole derivatives substituted in the 4-aryl ring with the acetyl moiety were designed and synthesized. The antiproliferative activity of the novel arylazopyrazoles was examined against the MCF-7 cell line. Among all target compounds, 8b (IC₅₀ 3.0 µM) and 8f (IC₅₀ 4.0 µM) displayed higher cytotoxicity as compared with the reference standard imatinib (IC₅₀ 7.0 µM). Further studies to explore the mechanism of action were performed on the most active hit of our library, 8b, via anti-CDK2 kinase activity. It demonstrated good inhibitory effects for CDK2 (IC₅₀ 0.24 µM) with 62.5% inhibition, compared with imatinib. The cell cycle analysis in the MCF-7 cell line revealed apoptosis induction by 8b and cell cycle arrest at the S phase. Docking in the CDK2 active site and pharmacophore modeling confirmed the affinity of 8b to the CDK2 active site. Absorption, distribution, metabolism, and excretion studies revealed that our target compounds are orally bioavailable, with no permeation through the blood-brain barrier.

Molecular Dynamics Simulations with NAMD2

X-ray diffraction crystallography is the primary technique to determine the three-dimensional structures of biomolecules. Although a robust method, X-ray crystallography is not able to access the dynamical behavior of macromolecules. To do so, we have to carry out molecular dynamics simulations taking as an initial system the three-dimensional structure obtained from experimental techniques or generated using homology modeling. In this chapter, we describe in detail a tutorial to carry out molecular dynamics simulations using the program NAMD2. We chose as a molecular system to simulate the structure of human cyclin-dependent kinase 2.

Docking with AutoDock4

AutoDock is one of the most popular receptor-ligand docking simulation programs. It was first released in the early 1990s and is in continuous development and adapted to specific protein targets. AutoDock has been applied to a wide range of biological systems. It has been used not only for protein-ligand docking simulation but also for the prediction of binding affinity with good correlation with experimental binding affinity for several protein systems. The latest version makes use of a semi-empirical force field to evaluate protein-ligand binding affinity and for selecting the lowest energy pose in docking simulation. AutoDock4.2.6 has an arsenal of four search algorithms to carry out docking simulation including simulated annealing, genetic algorithm, and Lamarckian algorithm. In this chapter, we describe a tutorial about how to perform docking with AutoDock4. We focus our simulations on the protein target cyclin-dependent kinase 2.

Sulfonamide-based ring-fused analogues for CAN508 as novel carbonic anhydrase inhibitors endowed with antitumor activity: Design, synthesis, and in vitro biological evaluation

In the present study, we report the design and synthesis of novel CAN508 sulfonamide-based analogues (4, 8a-e, 9a-h and 10a-e) as novel carbonic anhydrase (CA) inhibitors with potential CDK inhibitory activity. A bioisosteric replacement approach was adopted to replace the phenolic OH of CAN508 with a sulfamoyl group to afford compound 4. Thereafter, a ring-fusion approach was utilized to furnish the 5/5 fused imidazopyrazoles 8a-e which were subsequently expanded to 6/5 pyrazolopyrimidines 9a-h and 10a-e. All the synthesized analogues were evaluated for their inhibitory activity toward isoforms hCA I, II, IX and XII. The target tumor-associated isoforms hCA IX and XII were effectively inhibited with K_Is ranges 6-67.6 and 10.1-88.6 nM, respectively. Furthermore, all compounds were evaluated for their potential CDK2 and 9 inhibitory activities. Pyrazolopyrimidines 9d, 9e and 10b displayed weak CDK2 inhibitory activity (IC₅₀ = 6.4, 8.0 and 11.6 μM, respectively), along with abolished CDK9 inhibitory activity. This trend suggested that pyrazolopyrimidine derivatives merit further optimization to furnish more effective CDK2 inhibitor lead. On account of their excellent activity and selectivity towards hCA IX and XII, pyrazolopyrimidines 10 were evaluated for their anti-proliferative activity toward breast cancer MCF-7 and MDA-MB-468 cell lines under normoxic and hypoxic conditions. The most potent anti-proliferative agents 10a, 10c and 10d significantly increased cell percentage at sub-G1 and G2-M phases with concomitant decrease in the S phase population in MCF-7 treated cells. Finally, a docking study was undertaken to investigate the binding mode for the most selective hCA IX and XII inhibitors 10a-e, within hCA II, IX and XII active sites.

How Docking Programs Work

Protein-ligand docking simulations are of central interest for computer-aided drug design. Docking is also of pivotal importance to understand the structural basis for protein-ligand binding affinity. In the last decades, we have seen an explosion in the number of three-dimensional structures of protein-ligand complexes available at the Protein Data Bank. These structures gave further support for the development and validation of in silico approaches to address the binding of small molecules to proteins. As a result, we have now dozens of open source programs and web servers to carry out molecular docking simulations. The development of the docking programs and the success of such simulations called the attention of a broad spectrum of researchers not necessarily familiar with computer simulations. In this scenario, it is essential for those involved in experimental studies of protein-ligand interactions and biophysical techniques to have a glimpse of the basics of the protein-ligand docking simulations. Applications of protein-ligand docking simulations to drug development and discovery were able to identify hits, inhibitors, and even drugs. In the present chapter, we cover the fundamental ideas behind protein-ligand docking programs for non-specialists, which may benefit from such knowledge when studying molecular recognition mechanism.

A Dual Inhibitor of Cdc7/Cdk9 Potently Suppresses T Cell Activation

T cell activation is mediated by signaling pathways originating from the T cell receptor (TCR). Propagation of signals downstream of the TCR involves a cascade of numerous kinases, some of which have yet to be identified. Through a screening strategy that we have previously introduced, PHA-767491, an inhibitor of the kinases Cdc7 and Cdk9, was identified to impede TCR signaling. PHA-767491 suppressed several T cell activation phenomena, including the expression of activation markers, proliferation, and effector functions. We also observed a defect in TCR signaling pathways upon PHA-767491 treatment. Inhibition of Cdc7/Cdk9 impairs T cell responses, which could potentially be detrimental for the immune response to tumors, and also compromises the ability to resist infections. The Cdc7/Cdk9 inhibitor is a strong candidate as a cancer therapeutic, but its effect on the immune system poses a problem for clinical applications.

Synthesis, In Vitro Antimicrobial and Cytotoxic Activities of Some New Pyrazolo[1,5-a]pyrimidine Derivatives

A new series of pyrazole 4⁻7 and pyrazolo[1,5-a]pyrimidine 8⁻13 were synthesized by using a simple, efficient procedure, and screened for their in-vitro antimicrobial and antitumor activities. Symmetrical and asymmetrical 3,6-diarylazo-2,5,7-triaminopyrazolo[1,5-a]pyrimidine were synthesized by the conventional method and also subjected to microwave irradiation and under ultrasound conditions. The biological results revealed that most of the tested compounds proved to be active as antibacterial and antifungal agents. The antitumor activity of the synthesized compounds was evaluated against human cancer cell lines, MCF-7, HCT-116, and HepG-2, as compared with Doxorubicin as a control.

Studies with 2-Arylhydrazononitriles: Further Investigations on the Utility of 2-Arylhydrazononitriles as Precursors to 1,2,3-Triazole Amines

3-Oxo-2-arylhydrazonobutanenitriles react with hydroxylamine hydrochloride in ethanolic sodium acetate to yield either amidoximes or isoxazolamines depending on the nature of the substituent. The amidoximes cyclise in refluxing DMF containing piperidine to form 2-aryl-1,2,3-triazol-5-amines. The isoxazolamines rearranged into 1,2,3-triazolamines on refluxing in DMF. Amidoxime 2c cyclised in acetic anhydride to give 2-arylhydrazono-1,2,4-oxadiazole 9c, which rearranged to acetylamino-1,2,3-triazole 8c. The prepared acetyl-1,2,3-triazolamines 8b,c were utilised as precursors to triazolopyridines and pyrazolyltriazoles.

Recent development of CDK inhibitors: An overview of CDK/inhibitor co-crystal structures

The cyclin-dependent protein kinases (CDKs) are protein-serine/threonine kinases that display crucial effects in regulation of cell cycle and transcription. While the excessive expression of CDKs is intimate related to the development of diseases including cancers, which provides opportunities for disease treatment. A large number of small molecules are explored targeting CDKs. CDK/inhibitor co-crystal structures play an important role during the exploration of inhibitors. So far nine kinds of CDK/inhibitor co-crystals have been determined, they account for the highest proportion among the Protein Data Bank (PDB) deposited crystal structures. Herein, we review main co-crystals of CDKs in complex with corresponding inhibitors reported in recent years, focusing our attention on the binding models and the pharmacological activities of inhibitors.

Docking with GemDock

GEMDOCK is a protein-ligand docking software that makes use of an elegant biologically inspired computational methodology based on the differential evolution algorithm. As any docking program, GEMDOCK has two major features to predict the binding of a small-molecule ligand to the binding site of a protein target: the search algorithm and the scoring function to evaluate the generated poses. The GEMDOCK scoring function uses a piecewise potential energy function integrated into the differential evolutionary algorithm. GEMDOCK has been applied to a wide range of protein systems with docking accuracy similar to other docking programs such as Molegro Virtual Docker, AutoDock4, and AutoDock Vina. In this chapter, we explain how to carry out protein-ligand docking simulations with GEMDOCK. We focus this tutorial on the protein target cyclin-dependent kinase 2.

SAnDReS: A Computational Tool for Docking

Since the early 1980s, we have witnessed considerable progress in the development and application of docking programs to assess protein-ligand interactions. Most of these applications had as a goal the identification of potential new binders to protein targets. Another remarkable progress is taking place in the determination of the structures of protein-ligand complexes, mostly using X-ray diffraction crystallography. Considering these developments, we have a favorable scenario for the creation of a computational tool that integrates into one workflow all steps involved in molecular docking simulations. We had these goals in mind when we developed the program SAnDReS. This program allows the integration of all computational features related to modern docking studies into one workflow. SAnDReS not only carries out docking simulations but also evaluates several docking protocols allowing the selection of the best approach for a given protein system. SAnDReS is a free and open-source (GNU General Public License) computational environment for running docking simulations. Here, we describe the combination of SAnDReS and AutoDock4 for protein-ligand docking simulations. AutoDock4 is a free program that has been applied to over a thousand receptor-ligand docking simulations. The dataset described in this chapter is available for downloading at https://github.com/azevedolab/sandres.

Van der Waals Potential in Protein Complexes

Van der Waals forces are determinants of the formation of protein-ligand complexes. Physical models based on the Lennard-Jones potential can estimate van der Waals interactions with considerable accuracy and with a computational complexity that allows its application to molecular docking simulations and virtual screening of large databases of small organic molecules. Several empirical scoring functions used to evaluate protein-ligand interactions approximate van der Waals interactions with the Lennard-Jones potential. In this chapter, we present the main concepts necessary to understand van der Waals interactions relevant to molecular recognition of a ligand by the binding pocket of a protein target. We describe the Lennard-Jones potential and its application to calculate potential energy for an ensemble of structures to highlight the main features related to the importance of this interaction for binding affinity.

Molegro Virtual Docker for Docking

Molegro Virtual Docker is a protein-ligand docking simulation program that allows us to carry out docking simulations in a fully integrated computational package. MVD has been successfully applied to hundreds of different proteins, with docking performance similar to other docking programs such as AutoDock4 and AutoDock Vina. The program MVD has four search algorithms and four native scoring functions. Considering that we may have water molecules or not in the docking simulations, we have a total of 32 docking protocols. The integration of the programs SAnDReS ( https://github.com/azevedolab/sandres ) and MVD opens the possibility to carry out a detailed statistical analysis of docking results, which adds to the native capabilities of the program MVD. In this chapter, we describe a tutorial to carry out docking simulations with MVD and how to perform a statistical analysis of the docking results with the program SAnDReS. To illustrate the integration of both programs, we describe the redocking simulation focused the cyclin-dependent kinase 2 in complex with a competitive inhibitor.

Molecular Docking Simulations with ArgusLab

Molecular docking is the major computational technique employed in the early stages of computer-aided drug discovery. The availability of free software to carry out docking simulations of protein-ligand systems has allowed for an increasing number of studies using this technique. Among the available free docking programs, we discuss the use of ArgusLab ( http://www.arguslab.com/arguslab.com/ArgusLab.html ) for protein-ligand docking simulation. This easy-to-use computational tool makes use of a genetic algorithm as a search algorithm and a fast scoring function that allows users with minimal experience in the simulations of protein-ligand simulations to carry out docking simulations. In this chapter, we present a detailed tutorial to perform docking simulations using ArgusLab.

Homology Modeling of Protein Targets with MODELLER

Homology modeling is a computational approach to generate three-dimensional structures of protein targets when experimental data about similar proteins are available. Although experimental methods such as X-ray crystallography and nuclear magnetic resonance spectroscopy successfully solved the structures of nearly 150,000 macromolecules, there is still a gap in our structural knowledge. We can fulfill this gap with computational methodologies. Our goal in this chapter is to explain how to perform homology modeling of protein targets for drug development. We choose as a homology modeling tool the program MODELLER. To illustrate its use, we describe how to model the structure of human cyclin-dependent kinase 3 using MODELLER. We explain the modeling procedure of CDK3 apoenzyme and the structure of this enzyme in complex with roscovitine.

Machine Learning to Predict Binding Affinity

Recent progress in the development of scientific libraries with machine-learning techniques paved the way for the implementation of integrated computational tools to predict ligand-binding affinity. The prediction of binding affinity uses the atomic coordinates of protein-ligand complexes. These new computational tools made application of a broad spectrum of machine-learning techniques to study protein-ligand interactions possible. The essential aspect of these machine-learning approaches is to train a new computational model by using technologies such as supervised machine-learning techniques, convolutional neural network, and random forest to mention the most commonly applied methods. In this chapter, we focus on supervised machine-learning techniques and their applications in the development of protein-targeted scoring functions for the prediction of binding affinity. We discuss the development of the program SAnDReS and its application to the creation of machine-learning models to predict inhibition of cyclin-dependent kinase and HIV-1 protease. Moreover, we describe the scoring function space, and how to use it to explain the development of targeted scoring functions.

Docking with SwissDock

Protein-ligand docking simulation is central in drug design and development. Therefore, the development of web servers intended to docking simulations is of pivotal importance. SwissDock is a web server dedicated to carrying out protein-ligand docking simulation intuitively and elegantly. SwissDock is based on the protein-ligand docking program EADock DSS and has a simple and integrated interface. The SwissDock allows the user to upload structure files for a protein and a ligand, and returns the results by e-mail. To facilitate the upload of the protein and ligand files, we can prepare these input files using the program UCSF Chimera. In this chapter, we describe how to use UCSF Chimera and SwissDock to perform protein-ligand docking simulations. To illustrate the process, we describe the molecular docking of the competitive inhibitor roscovitine against the structure of human cyclin-dependent kinase 2.