Fusion of Structure and Ligand Based Methods for Identification of Novel CDK2 Inhibitors

Alkaloids from Corydalis saxicola and their antiproliferative activity against cancer cells

Eight undescribed alkaloids named corydalisine D-K (1-7), including one isoquinoline benzopyranone alkaloid (1), one benzocyclopentanone alkaloid (2), four benzofuranone alkaloids (3, 4, and 5a/5b) and two protoberberine alkaloids (6 and 7), along with fourteen known ones, were isolated from the Corydalis saxicola. Their structures, including absolute configurations, were unambiguously identified using spectroscopic techniques, single-crystal X-ray diffraction and electron circular dichroism calculation. Compounds 2, 14 and 21 exhibit antiproliferative activity against five cancer cell lines. The aporphine alkaloid demethylsonodione (compound 14), which exhibited the best activity (IC50 = 3.68 ± 0.25 μM), was subjected to further investigation to determine its mechanism of action against the T24 cell line. The molecular mechanism was related to the arrest of cell cycle S-phase, inhibition of CDK2 expression, accumulation of reactive oxygen species (ROS), induction of cell apoptosis, inhibition of cell migration, and activation of p38 MAPK signaling pathway. The results indicated that 14 could be used as a potential candidate agent for further development of anti-bladder transitional cell carcinoma.

Pyrazolopyrimidinone Based Selective Inhibitors of PDE5 for the Treatment of Erectile Dysfunction

Continuing research with our earlier finding of sildenafil based analogs in the search of new inhibitors of PDE5 for erectile dysfunction suggested that there is a scope of modifications at N-methylpiperazine ring with hydrophobic region followed by hydrogen bond donor or acceptor region. However, the leads identified earlier had some limitations like poor pharmacokinetic (PK) profile, low aqueous solubility and poor bioavailability. In this direction, a new series of sildenafil based analogs were designed, synthesized and screened for their PDE5 inhibitory activity. In this series compound 18 was found to have excellent in vitro activity with selectivity towards PDE5 isozyme, also the in vivo activity and pharmacokinetic profile was excellent. The cyp inhibition and CaCO2 permeability was also excellent for compound 18.

Identification of 3-(piperazinylmethyl)benzofuran derivatives as novel type II CDK2 inhibitors: design, synthesis, biological evaluation, and in silico insights

In the current work, a hybridisation strategy was adopted between the privileged building blocks, benzofuran and piperazine, with the aim of designing novel CDK2 type II inhibitors. The hybrid structures were linked to different aromatic semicarbazide, thiosemicarbazide, or acylhydrazone tails to anchor the designed inhibitors onto the CDK2 kinase domain. The designed compounds showed promising CDK2 inhibitory activity. Compounds 9h, 11d, 11e and 13c showed potent inhibitory activity (IC₅₀ of 40.91, 41.70, 46.88, and 52.63 nM, respectively) compared to staurosporine (IC₅₀ of 56.76 nM). Moreover, benzofurans 9e, 9h, 11d, and 13b showed promising antiproliferative activities towards different cancer cell lines, and non-significant cytotoxicity on normal lung fibroblasts MRC-5 cell line. Furthermore, a cell cycle analysis as well as Annexin V-FITC apoptosis assay on Panc-1 cell line were performed. Molecular docking simulations were performed to explore the ability of target benzofurans to adopt the common binding pattern of CDK2 type II inhibitors.

Collaborative Approach between Explainable Artificial Intelligence and Simplified Chemical Interactions to Explore Active Ligands for Cyclin-Dependent Kinase 2

To improve virtual screening for drug discovery, we present a collaborative approach between explainable artificial intelligence (AI) and simplified chemical interaction scores to efficiently search for active ligands bound to the target receptor. In particular, we focus on cyclin-dependent kinase 2 (CDK2), which is well known as a cancer target protein. Docking simulation alone is insufficient to distinguish active ligands from decoy molecules. To identify active ligands, in this paper, machine learning is employed together with scoring functions that simplify the screened Coulomb and Lennard-Jones interactions between the ligands and residues of the target receptor. We demonstrate that these simplified interaction scores can significantly improve the classification ability of machine learning models. We also demonstrate that explainable AI together with the simplified scoring method can highlight the important residues of CDK2 for recognizing active ligands.

Effect of fenofibrate on proliferation of SMMC-7721 cells via regulating cell cycle

Liver cancer is a malignant cancer with great harmfulness. Fenofibrate is a peroxisome proliferation activated receptor (PPARα) agonist widely used in the treatment of dyslipidemia. Previous studies have shown that fenofibrate may promote cell proliferation, but the underlying mechanism has not been fully characterized. The aim of this study was to investigate the role of PPARα agonist fenofibrate in cell proliferation of SMMC-7721 cells compared with that of THLE-2 cells. SMMC-7721 and THLE-2 cells were treated with different concentrations of fenofibrate. Cell proliferation was analyzed by MTT, using flow cytometry for cell cycle analysis, and CyclinD1, Cyclin-dependent kinases2 (CDK2) and Proliferating Cell Nuclear Antigen (PCNA) were analyzed by Western blotting. RT-qPCR method was used to assess CDK2, CyclinD1 and PCNA mRNA levels. The results showed that 10^-9-10^-4 mol/L fenofibrate could induce cell growth and 10^-4, 10^-5, 10^-6 mol/L fenofibrate could reduce the number of G0/G1 phase cells and increased in the number of cells in S and G2/M phase of cell cycle in SMMC-7721 cells. Furthermore, fenofibrate could significantly increase the expression of cell cycle related protein (CyclinD1, CDK2)and cell proliferation related proteins (PCNA). The use of PPARα inhibitor MT886 inhibited cell cycle progression and promote tumor cell apoptosis. But fenofibrate had no obvious effect on THLE-2 cells. These results revealed the effect of fenofibrate on the cell cycle of liver cancer cells, and provided a reasonable explanation for studying how fenofibrate promotes cell proliferation.

Using the Semiempirical Quantum Mechanics in Improving the Molecular Docking: A Case Study with CDK2

In this study, we use some modified semiempirical quantum mechanics (SQM) methods for improving the molecular docking process. To this end, the three popular SQM Hamiltonians, PM6, PM6-D3H4X, and PM7 are employed for geometry optimization of some binding modes of ligands docked into the human cyclin-dependent kinase 2 (CDK2) by two widely used docking tools, AutoDock and AutoDock Vina. The results were analyzed with two different evaluation metrics: the symmetry-corrected heavy-atom RMSD and the fraction of recovered ligand-protein contacts. It is shown that the evaluation of the fraction of recovered contacts is more useful to measure the similarity between two structures when interacting with a protein. It was also found that AutoDock is more successful than AutoDock Vina in producing the correct ligand poses (RMSD≤2.0 Å) and ranking of the poses. It is also demonstrated that the ligand optimization at the SQM level improves the docking results and the SQM structures have a significantly better fit to the observed crystal structures. Finally, the SQM optimizations reduce the number of close contacts in the docking poses and successfully remove most of the clash or bad contacts between ligand and protein.

Synthesis, Biological Evaluation and In Silico Studies of Certain Oxindole-Indole Conjugates as Anticancer CDK Inhibitors

On account of their overexpression in a wide range of human malignancies, cyclin-dependent kinases (CDKs) are among the most validated cancer targets, and their inhibition has been featured as a valuable strategy for anticancer drug discovery. In this study, a hybrid pharmacophore approach was adopted to develop two series of oxindole-indole conjugates (6a-i and 9a-f) and carbocycle-indole conjugates (11a,b) as efficient antitumor agents with potential inhibitory action toward CDK4. All oxindole-indole conjugates, except 6i, 9b, and 9c efficiently affected the growth of the human breast cancer MCF-7 (IC₅₀: 0.39 ± 0.05-21.40 ± 1.58 μM) and/or MDA-MB-231 (IC₅₀: 1.03 ± 0.04-22.54 ± 1.67 μM) cell lines, whereas bioisosteric replacement of the oxindole nucleus with indane or tetralin rings (compounds 11a,b) diminished the anti-proliferative activity. In addition, hybrids 6e and 6f displayed effective cell cycle disturbance and proapoptotic capabilities in MCF-7 cells. Furthermore, the efficient anti-proliferative agents towards MCF-7 and/or MDA-MB-231 cell lines (6a-h, 9a, and 9e) were investigated for their potential inhibitory action toward CDK4. Hybrids 6a and 6e displayed good CDK4 inhibitory activity with IC₅₀s equal 1.82 and 1.26 µM, respectively. The molecular docking study revealed that oxindole moiety is implicated in two H-bonding interactions via both (NH) and (C=O) groups with the key amino acids Glu94 and Val96, respectively, whereas the indole framework is stably accommodated in a hydrophobic sub-pocket establishing hydrophobic interactions with the amino acid residues of Ile12, Val20, and Gln98 lining this sub-pocket. Collectively, these results highlighted hybrids 6a and 6e as good leads for further optimization as promising antitumor drugs toward breast malignancy and CDK inhibitors.

Inhibition of Oncogenic Kinases: An In Vitro Validated Computational Approach Identified Potential Multi-Target Anticancer Compounds

Tumorigenesis in humans is a multistep progression that imitates genetic changes leading to cell transformation and malignancy. Oncogenic kinases play a central role in cancer progression, rendering them putative targets for the design of anti-cancer drugs. The presented work aims to identify the potential multi-target inhibitors of oncogenic receptor tyrosine kinases (RTKs) and serine/threonine kinases (STKs). For this, chemoinformatics and structure-based virtual screening approaches were combined with an in vitro validation of lead hits on both cancerous and non-cancerous cell lines. A total of 16 different kinase structures were screened against ~739,000 prefiltered compounds using diversity selection, after which the top hits were filtered for promising pharmacokinetic properties. This led to the identification of 12 and 9 compounds against RTKs and STKs, respectively. Molecular dynamics (MD) simulations were carried out to better comprehend the stability of the predicted hit kinase-compound complexes. Two top-ranked compounds against each kinase class were tested in vitro for cytotoxicity, with compound F34 showing the most promising inhibitory activity in HeLa, HepG2, and Vero cell lines with IC50 values of 145.46 μM, 175.48 μM, and 130.52 μM, respectively. Additional docking of F34 against various RTKs was carried out to support potential multi-target inhibition. Together with reliable MD simulations, these results suggest the promising potential of identified multi-target STK and RTK scaffolds for further kinase-specific anti-cancer drug development toward combinatorial therapies.

Combining ligand- and structure-based in silico methods for the identification of natural product-based inhibitors of Akt1

The traditional method of drug discovery process has been surpassed by a rational approach where computer-aided drug designing plays a vital role in the identification of leads from large compound databases. Further, natural products have an important role in drug discovery as these have been the source of most active ingredients of medicines. Herein, in silico structure- and ligand-based approaches have been applied to screen in-house IIIM natural product repository for Akt1 (serine/threonine protein kinases) which is a well-known therapeutic target for cancer due to its overexpression and preventing the cells from undergoing apoptosis. Combined ligand-based and structure-based strategies were applied on to the existing library comprising of about 700 pure natural products, and the compounds identified from screening were biologically evaluated for Akt1 inhibition using Akt1 kinase activity assay. Fourteen promising compounds showed significant inhibition at 500 nM through in vitro screening, and from them, eight were new for Akt1 inhibition. Through the MD studies of Akt1 with the most active compound IN00145, it was inferred that Lys179, Glu191, Glu228, Ala230, Glu234 and Asp292 are the important amino acid residues which provide stability to the Akt1-IN00145 complex. Lead optimization studies were also performed around the actives to design better and selective inhibitors for Akt1. The results emphasized the successful application of virtual screening to identify new Akt1 inhibitor scaffolds that can be developed into a drug candidate in drug discovery programme.

Comprehensive 3D-QSAR Model Predicts Binding Affinity of Structurally Diverse Sigma 1 Receptor Ligands

The Sigma 1 Receptor (S1R) has attracted intense interest as a pharmaceutical target for various therapeutic indications, including the treatment of neuropathic pain and the potentiation of opioid analgesia. Efforts by drug developers to rationally design S1R antagonists have been spurred recently by the 2016 publication of the high-resolution X-ray crystal structure of the ligand-bound human S1R. Until now, however, the absence in the published literature of a single, large-scale, and comprehensive quantitative structure-activity relationship (QSAR) model that encompasses a structurally diverse collection of S1R ligands has impaired rapid progress. To our best knowledge, the present study represents the first report of a statistically robust and highly predictive 3D-QSAR model (R2 = 0.92, Q2 = 0.62, Rpred2 = 0.81) based on the X-ray crystal structure of human S1R and constructed from a pooled compilation of 180 S1R antagonists that encompass five structurally diverse chemical families investigated using identical experimental protocols. Best practices, as recommended by the Organization for Economic Cooperation and Development (OECD: http://www.oecd.org/ ), were adopted for pooling data from disparate sources and for QSAR model development and both internal and external model validation. The practical utility of the final 3D-QSAR model was tested by virtual screening of the DrugBank database of FDA approved drugs supplemented by eight reported S1R antagonists. Among the top-ranked 40 DrugBank hits, four approved drugs which were previously unknown as S1R antagonists were tested using in vitro radiolabeled human S1R binding assays. Of these, two drugs (diphenhydramine and phenyltoloxamine) exhibited potent S1R binding affinity with Ki = 58 nM and 160 nM, respectively. As diphenhydramine is approved as an antiallergic, and phenyltoloxamine as an analgesic and sedative, each of these compounds represents a viable starting point for a drug discovery campaign aimed at the development of novel S1R antagonists for a wide range of therapeutic indications.

New thiazol-hydrazono-coumarin hybrids targeting human cervical cancer cells: Synthesis, CDK2 inhibition, QSAR and molecular docking studies

Motivated by the potential anticancer activity of both coumarin and 2-aminothiazole nuclei, a new set of thiazol-2-yl hydrazono-chromen-2-one analogs were efficiently synthesized aiming to obtain novel hybrids with potential cytotoxic activity. MTT assay investigated the significant potency of all the target compounds against the human cervical cancer cell lines (HeLa cells). Cell cycle analysis showed that the representative compound 8a led to cell cycle cessation at G0/G1 phase indicating that CDK2/E1complex could be the plausible biological target for these newly synthesized compounds. Thus, the most active compounds (7c and 8a-c) were tested for their CDK2 inhibitory activity. The biological results revealed their significant CDK2 inhibitory activity with IC₅₀ range of 0.022-1.629 nM. Moreover, RT-PCR gene expression assay showed that compound 8a increased the levels of the nuclear CDK2 regulators P21 and P27 by 2.30 and 5.7 folds, respectively. ELISA tequnique showed also that compound 8a led to remarkable activation of caspases-9 and -3 inducing cell apoptosis. QSAR study showed that the charge distribution and molecular hydrophobicity are the structural features affecting cytotoxic activity in this series. Molecular docking study for the most potent cytotoxic compounds (7c and 8a-c) rationalized their superior CDK2 inhibitory activity through their hydrogen bonding and hydrophobic interactions with the key amino acids in the CDK2 binding site. Pharmacokinetic properties prediction of the most potent compounds showed that the newly synthesized compounds are not only with promising antitumor activity but also possess promising pharmacokinetic properties.

Identifying a novel anticancer agent with microtubule-stabilizing effects through computational cell-based bioactivity prediction models and bioassays

G03 is a novel anticancer agent with unusual microtubule-stabilizing effects.