Structure-based and shape-complemented pharmacophore modeling for the discovery of novel checkpoint kinase 1 inhibitors

Discovery of novel and highly potential inhibitors of glycogen synthase kinase 3-beta (GSK-3β) through structure-based pharmacophore modeling, virtual computational screening, docking and in silico ADMET analysis

The protein Glycogen Synthase Kinase 3-Beta (GSK-3β), is a promising therapeutic target for treating various diseases such as neurodegenerative disorders, diabetes, inflammation and cancer. This study aims to investigate the potential of compounds targeting inflammation or carbohydrate metabolism to selectively inhibit GSK3β by binding to its ATP site. To achieve this goal, we filtered a database of 49367 molecules involved in carbohydrate metabolism or targeting inflammation using various computational analyses, including pharmacophore modeling, molecular docking, dynamic simulation, prime MM-GBSA calculation, and in silico ADME studies. We generated a pharmacophore model (hypo S: AADDHRR) using two different crystallographic complexes of GSK3β and evaluated the model's performance in identifying hits using various parameters, including EF, GH, ROC, AUC and BEDROC. Subsequently, we performed various dockings (HTVS, SP, XP and IFD) for the retrieved hits and found that, 5 out of the top 10 ranked compounds had the scaffold of pyrazolidine 3,5-dione, which has never been reported to inhibit kinases. We also conducted ADMET studies to and concluded that compound N6 exhibited the best pharmacokinetic profile passing the blood-brain barrier, possessing high lipophilicity and a high coefficient of skin permeability in the intestines, along with good bioavailability and low toxicity risk assessment. Dynamic simulation were also performed indicating that compounds N6 derived from pyrazolidine 3,5-dione demonstrated better binding potential for GSK3β during the simulation period. Therefore, we propose that compounds derived from pyrazolidine-3,5-dione, which modulate the activity of lysosomal alpha-glucosidase could serve as a novel scaffold for the selective inhibition of GSK-3β.Communicated by Ramaswamy H. Sarma.

Cisplatin and Procaterol Combination in Gastric Cancer? Targeting Checkpoint Kinase 1 for Cancer Drug Discovery and Repurposing by an Integrated Computational and Experimental Approach

Checkpoint kinase 1 (CHK1), a serine/threonine kinase, plays a crucial role in cell cycle arrest and is a promising therapeutic target for drug development against cancers. CHK1 coordinates cell cycle checkpoints in response to DNA damage, facilitating repair of single-strand breaks, and maintains the genome integrity in response to replication stress. In this study, we employed an integrated computational and experimental approach to drug discovery and repurposing, aiming to identify a potent CHK1 inhibitor among existing drugs. An e-pharmacophore model was developed based on the three-dimensional crystal structure of the CHK1 protein in complex with CCT245737. This model, characterized by seven key molecular features, guided the screening of a library of drugs through molecular docking. The top 10% of scored ligands were further examined, with procaterol emerging as the leading candidate. Procaterol demonstrated interaction patterns with the CHK1 active site similar to CHK1 inhibitor (CCT245737), as shown by molecular dynamics analysis. Subsequent in vitro assays, including cell proliferation, colony formation, and cell cycle analysis, were conducted on gastric adenocarcinoma cells treated with procaterol, both as a monotherapy and in combination with cisplatin. Procaterol, in synergy with cisplatin, significantly inhibited cell growth, suggesting a potentiated therapeutic effect. Thus, we propose the combined application of cisplatin and procaterol as a novel potential therapeutic strategy against human gastric cancer. The findings also highlight the relevance of CHK1 kinase as a drug target for enhancing the sensitivity of cytotoxic agents in cancer.

Identification of selective Lyn inhibitors from the chemical databases through integrated molecular modelling approaches

In the current study, the Asinex and ChEBI databases were virtually screened for the identification of potential Lyn protein inhibitors. Therefore, a multi-steps molecular docking study was carried out using the VSW utility tool embedded in Maestro user interface of the Schrödinger suite. On initial screening, molecules having a higher XP-docking score and binding free energy compared to Staurosporin were considered for further assessment. Based on in silico pharmacokinetic analysis and a common-feature pharmacophore mapping model developed from the Staurosporin, four molecules were proposed as promising Lyn inhibitors. The binding interactions of all proposed Lyn inhibitors revealed strong ligand efficiency in terms of energy score obtained in molecular modelling analyses. Furthermore, the dynamic behaviour of each molecule in association with the Lyn protein-bound state was assessed through an all-atoms molecular dynamics (MD) simulation study. MD simulation analyses were confirmed with notable intermolecular interactions and consistent stability for the Lyn protein-ligand complexes throughout the simulation. High negative binding free energy of identified four compounds calculated through MM-PBSA approach demonstrated a strong binding affinity towards the Lyn protein. Hence, the proposed compounds might be taken forward as potential next-generation Lyn kinase inhibitors for managing numerous Lyn associated diseases or health complications after experimental validation.

The Multiplicity of Polypeptide GalNAc-Transferase: Assays, Inhibitors, and Structures

Mucin-type O-glycosylation is the dominant form of glycosylation in eukaryotes and plays an important role in various physiological processes. The polypeptide GalNAc-transferase (GalNAc-T) catalyzes the first step in the attachment of mucin-type O-glycosylation. GalNAc-T was recently uncovered to be linked with cancer, atherogenic dyslipidemia, and X-linked hypophosphatemic rickets. Therefore, it has attracted increasing interest as a new target for exploring the underlying mechanism and developing new treatments for related diseases. Decades of studies on GalNAc-T have laid a stable foundation for understanding the catalytic mechanism, determining atom-resolution three-dimensional structures, and developing various types of biochemical assays as well as small-molecule inhibitor leads. Here, we systematically summarize this invaluable knowledge on GalNAc-T and cultivate new perspectives to foster breakthrough points for mucin-type O-glycosylation.

Design, synthesis, and screening of ortho-amino thiophene carboxamide derivatives on hepatocellular carcinomaas VEGFR-2Inhibitors

In this work, design, synthesis, and screening of thiophene carboxamides 4-13 and 16-23 as dual vascular endothelial growth factor receptors (VEGFRs) and mitotic inhibitors was reported. All compounds were screened against two gastrointestinal solid cancer cells, HepG-2 and HCT-116 cell lines. The most active cytotoxic derivatives 5 and 21 displayed 2.3- and 1.7-fold higher cytotoxicity than Sorafenib against HepG-2 cells. Cell cycle and apoptosis analyses for compounds 5 and 21 showed cells accumulation in the sub-G1 phase, and cell cycle arrest at G2/M phase. The apoptotic inducing activities of compounds 5 and 21were correlated to the elevation of p53, increase in Bax/Bcl-2 ratio, and increase in caspase-3/7.Compounds 5 and 21 showed potent inhibition againstVEGFR-2 (IC50 = 0.59 and 1.29 μM) and β-tubulin polymerization (73% and 86% inhibition at their IC50 values).Molecular docking was performed with VEGFR-2 and tubulin binding sites to explain the displayed inhibitory activities.

Design, synthesis, and biological evaluation of polo-like kinase 1/eukaryotic elongation factor 2 kinase (PLK1/EEF2K) dual inhibitors for regulating breast cancer cells apoptosis and autophagy

Both PLK1 and EEF2K are serine⁄threonine kinases that play important roles in the proliferation and programmed cell death of various types of cancer. They are highly expressed in breast cancer tissues. Based on the multiple-complexes generated pharmacophore models of PLK1 and homology models of EEF2K, the integrated virtual screening is performed to discover novel PLK1/EEF2K dual inhibitors. The top ten hit compounds are selected and tested in vitro, and five of them display PLK1 and EEF2K inhibition in vitro. Based on the docking modes of the most potent hit compound, a series of derivatives are synthesized, characterized and biological assayed on the PLK1, EEF2K as well as breast cancer cell proliferation models. Compound 18i with satisfied inhibitory potency are shifted to molecular mechanism studies contained molecular dynamics simulations, cell cycles, apoptosis and autophagy assays. Our results suggested that these novel PLK1/EEF2K dual inhibitors can be used as lead compounds for further development breast cancer chemotherapy.

Multi-conformation dynamic pharmacophore modeling of the peroxisome proliferator-activated receptor γ for the discovery of novel agonists

Activation of the peroxisome proliferator-activated receptor γ (PPARγ) is important for the treatment of type 2 diabetes and obesity through the regulation of glucose metabolism and fatty acid accumulation. Hence, the discovery of novel PPARγ agonists is necessary to overcome these diseases. In this study, a newly developed approach, multi-conformation dynamic pharmacophore modeling (MCDPM), was used for screening candidate compounds that can properly bind PPARγ. Highly populated structures obtained from molecular dynamics (MD) simulations were selected by clustering analysis. Based on these structures, pharmacophore models were generated from the ligand-binding pocket and then validated to check the rationality. Consequently, two hits were retrieved as final candidates by utilizing virtual screening and molecular docking simulations. These compounds can be used in the design of novel PPARγ agonists.

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.

Identification of novel polo-like kinase 1 inhibitors by a hybrid virtual screening

Polo-like kinase 1 is an important and attractive oncological target that plays a key role in mitosis and cytokinesis. A combined pharmacophore- and docking-based virtual screening was performed to identify novel polo-like kinase 1 inhibitors. A total of 34 hit compounds were selected and tested in vitro, and some compounds showed inhibition of polo-like kinase 1 and human tumor cell growth. The most potent compound (66) inhibited polo-like kinase 1 with an IC(50) value of 6.99 μm. The docked binding models of two hit compounds were discussed in detail. These compounds contained novel chemical scaffolds and may be used as foundations for the development of novel classes of polo-like kinase 1 inhibitors.

From the protein's perspective: the benefits and challenges of protein structure-based pharmacophore modeling

Protein structure-based pharmacophore (SBP) models derive the molecular features a ligand must contain to be biologically active by conversion of protein properties to reciprocal ligand space. SBPs improve molecular understanding of ligand–protein interactions and can be used as valuable tools for hit and lead optimization, compound library design, and target hopping.

Pharmacophore modeling and virtual screening studies to identify new c-Met inhibitors

Mesenchymal epithelial transition factor (c-Met) is an attractive target for cancer therapy. Three-dimensional pharmacophore hypotheses were built based on a set of known structurally diverse c-Met inhibitors. The best pharmacophore model, which identified inhibitors with an associated correlation coefficient of 0.983 between their experimental and estimated IC(50) values, consisted of two hydrogen-bond acceptors, one hydrophobic, and one ring aromatic feature. The highly predictive power of the model was rigorously validated by test set prediction and Fischer's randomization method. The high values of enrichment factor and receiver operating characteristic (ROC) score indicated the model performed fairly well at distinguishing active from inactive compounds. The model was then applied to screen compound database for potential c-Met inhibitors. A filtering protocol, including druggability and molecular docking, were also applied in hits selection. The final 38 molecules, which exhibited good estimated activities, desired binding mode and favorable drug likeness were identified as potential c-Met inhibitors. Their novel backbone structures could be served as scaffolds for further study, which may facilitate the discovery and rational design of potent c-Met kinase inhibitors.

ATP and its N⁶-substituted analogues: parameterization, molecular dynamics simulation and conformational analysis

In this work we used a combination of classical molecular dynamics and simulated annealing techniques to shed more light on the conformational flexibility of 12 adenosine triphosphate (ATP) analogues in a water environment. We present simulations in AMBER force field for ATP and 12 published analogues [Shah et al. (1997) Proc Natl Acad Sci USA 94: 3565–3570]. The calculations were carried out using the generalized Born (GB) solvation model in the presence of the cation Mg²⁺. The ion was placed at a close distance (2 Å) from the charged oxygen atoms of the beta and gamma phosphate groups of the −3 negatively charged ATP analogue molecules. Analysis of the results revealed the distribution of inter-proton distances H8–H1′ and H8–H2′ versus the torsion angle ψ (C4–N9-C1′–O4′) for all conformations of ATP analogues. There are two gaps in the distribution of torsion angle ψ values: the first is between −30 and 30 degrees and is described by cis-conformation; and the second is between 90 and 175 degrees, which mostly covers a region of anti conformation. Our results compare favorably with results obtained in experimental assays [Jiang and Mao (2002) Polyhedron 21:435–438].

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