3D-QSAR and virtual screening studies of thiazolidine-2,4-dione analogs: Validation of experimental inhibitory potencies towards PIM-1 kinase

Novel indole based fused triazole-thiadiazole derivatives as anti-diabetic agents: in vitro and in silico approaches

Aim: The current research presents novel library of indole derived fused triazole-thiadiazole derivatives (1-17) for treatment of diabetes mellitus.Methods & results: These compounds were synthesized by treating 2-(1H-indol-3-yl)acetic acid with hydrazinecarbothiohydrazide followed by treating the resultant compound with substituted benzoic acid. Structural validation was achieved spectroscopically (1HNMR, 13CNMR and HREI-MS). The synthesized compounds were subjected to biological evaluation to assess their potential as anti-diabetic. Molecular docking study was employed to investigate the binding interactions of these analogs with relevant proteins. ADMET analysis was used to predict their drug-like properties. Notably, compound-10 (IC50 = 1.27 ± 1.25 and 2.18 ± 2.45 μM) bearing para-substituted F atom exhibited the highest potency due to strong inhibitory interactions through hydrogen bonding.Conclusion: This study identifies promising compounds with anti-diabetic activity, paving the way for the treatment of diabetes mellitus.

In silico design and ADMET evaluation of new inhibitors for PIM1 kinase using QSAR studies, molecular docking, and molecular dynamic simulation

The proviral Integration site of Moloney (PIM) kinase is highly expressed in various diseases, including cancer, making the development of selective inhibitors for this protein important. A series of PIM1 inhibitors, triazolo [4, 3-b] pyridazin-3-yl-quinoline derivatives, have been studied to design new inhibitors. The activity and structural features of these derivatives were investigated to understand their interactions with PIM1 using molecular docking, molecular dynamic simulation, and QSAR techniques. In a study of 30 compounds using the structure-activity technique and the MLR method, a linear model with R2 train = 0.91 and R2 test = 0.96 was obtained. The model utilized descriptors such as RDF080v, RDF105v, RDF135v, Mor03v, and H046 to express the structural characteristics of the inhibitors. To enhance the model, the SVR non-linear method with the RBF function was also used, resulting in an improved model with R2 train = 0.98 and R2 test = 0.98. Furthermore, the molecular docking technique was employed to investigate the interaction of compounds with high (compound 25) and low (compound 13) inhibitory activity. It was observed that the rings with nitrogen atoms interacted with the protein. The molecular binding results indicate that groups such as OMe and rings with Nitrogen can enhance the inhibitory activity of the compounds. Additionally, oxygen and nitrogen atoms contribute to an increased number of hydrogen bonds, thereby increasing the inhibitory activity of the compounds. Additionally, the stability and bonding modes of active and inactive compounds were studied using molecular dynamic simulation. Based on the results, four new inhibitors were designed, demonstrating better inhibition efficiency with the PIM1 kinase compared to the reference compounds. Moreover, the designed compounds underwent evaluation for ADMET, yielding promising results.

Assessment of anti-hyperglycemic and anti-hyperlipidemic effects of thiazolidine-2,4-dione derivatives in HFD-STZ diabetic animal model

Type 2 diabetes mellitus (T2DM) is a chronic endocrine/metabolic disorder characterized by elevated postprandial and fasting glycemic levels that result in disturbances in primary metabolism. In this study, we evaluated the metabolic effects of thiazolidine-2,4-dione derivatives in Wistar rats and Swiss mice that were fed a high-fat diet (HFD) for 4 weeks and received 90 mg/kg of streptozotocin (STZ) intraperitoneally as a T2DM model. The HFD consisted of 17% carbohydrate, 58% fat, and 25% protein, as a percentage of total kcal. The thiazolidine-2,4-dione derivatives treatments reduced fasting blood glucose (FBG) levels by an average of 23.98%-50.84%, which were also improved during the oral starch tolerance test (OSTT). Treatment with thiazolidine-2,4-dione derivatives also improved triglyceride (TG), low-density lipoprotein cholesterol (LDL-c), and total cholesterol levels (P < 0.05). The treatment intake has also shown a significant effect to modulate the altered hepatic and renal biomarkers. Further treatment with thiazolidine-2,4-dione derivatives for 28 days significantly ameliorated changes in appearance and metabolic risk factors, including favorable changes in histopathology of the liver, kidney, and pancreas compared with the HFD/STZ-treated group, suggesting its potential role in the management of diabetes. Thiazolidine-2,4-dione derivatives are a class of drugs that act as insulin sensitizers by activating peroxisome proliferator-activated receptor-gamma (PPAR-γ), a nuclear receptor that regulates glucose and lipid metabolism. The results of this study suggest that thiazolidine-2,4-dione derivatives may be a promising treatment option for T2DM by improving glycemic control, lipid metabolism, and renal and hepatic function.

Multistage in silico approach to identify novel quinoline derivatives as potential c-kit kinase inhibitors

The type II-C-KIT signaling network has been extensively studied for its potential as a target for cancer treatment, leading to the investigation of quinoline derivatives as compounds with inhibitory effects on c-Kit kinase. In this study, a multistage approach was employed, including the creation of pharmacophore models, 3D QSAR analysis, virtual screening, docking investigations, and molecular dynamics stimulation. The pharmacophore evaluation included a data set of 29 ligands, which resulted in the generation of the ADDHR_1pharmacophore model as the most promising, with a survival score of 5.6812. The main objective was to utilize the atom-based 3D-QSAR approach for generating robust 3D-QSAR models aimed at identifying new TypeII-C-kit kinase inhibitors. The evaluations of these models have convincingly demonstrated their high predictive power (Q2 = 0.6547, R2 = 0.9947). Using atom-based 3D-QSAR data, a total of 7564 novel compounds were generated from R-group enumeration. Molecular docking and MM-GBSA study revealed that compound A1 exhibited the highest binding score of -9.30 kcal/mol and a Δ GBind value of -90.56 kcal/mol. The ZINC compounds were then screened using the pharmacophore model, followed by virtual screening, which identified ZINC65798256, ZINC09317958, ZINC73187176, and ZINC76176670 as potential candidates with promising docking scores. Among these, ZINC65798256 demonstrated the best binding interactions with amino acid residues, ASP810, LYS623, CYS673, and THR670 (PDB ID: 1T46). To further analyze the structural features and molecular interactions, molecular dynamics simulation was conducted for a time scale of 100 ns.

Rhodanine-Based Chromophores: Fast Access to Capable Photoswitches and Application in Light-Induced Apoptosis

Molecular photoswitches are highly desirable in all chemistry-related areas of research. They provide effective outside control over geometric and electronic changes at the nanoscale using an easy to apply, waste-free stimulus. However, simple and effective access to such molecular tools is typically not granted, and elaborate syntheses and substitution schemes are needed in order to obtain efficient photoswitching properties. Here we present a series of rhodanine-based photoswitches that can be prepared in one simple synthetic step without requiring elaborate purification. Photoswitching is induced by UV and visible light in both switching directions, and thermal stabilities of the metastable states as well as quantum yields are very high. An additional benefit is the hydrogen-bonding capacity of the rhodanine fragment, which enables applications in supramolecular or medicinal chemistry. We further show that the known rhodanine-based inhibitor SMI-16a is a photoswitchable apoptosis inducer. The biological activity of SMI-16a can effectively be switched ON or OFF by reversible photoisomerization between the inactive E and the active Z isomer. Rhodanine-based photoswitches therefore represent an easy to access and highly valuable molecular toolbox for implementing light responsiveness to the breadth of functional molecular systems.

Integrated fragment-based drug design and virtual screening techniques for exploring the antidiabetic potential of thiazolidine-2,4-diones: Design, synthesis and in vivo studies

Diabetes mellitus is a metabolic disorder characterized by elevated blood sugar levels and related complications. This study focuses on harnessing and integrating fragment-based drug design and virtual screening techniques to explore the antidiabetic potential of newly synthesized thiazolidine-2,4-dione derivatives. The research involves the design of novel variations of thiazolidine-2,4-dione compounds by Fragment-Based Drug Design. The screening process involves pharmacophore based virtual screening through docking algorithms, and the identification of newly twelve top-scoring compounds. The molecular docking analysis revealed that compounds SP4e, SP4f showed highest docking scores of -9.082 and -10.345. The binding free energies of the compounds SP4e, SP4f and pioglitazone was found to be -19.9, -16.1 and -13 respectively, calculated using the Prime MM/GBSA approach. The molecular dynamic study validates the docking results. Furthermore, In the Swiss albino mice model, both SP4e and SP4f exhibited significant hypoglycaemic effects, comparable to the reference drug pioglitazone. Furthermore, these compounds demonstrated favorable effects on the lipid profile, reducing total cholesterol, triglycerides, and LDL levels while increasing HDL levels. In mice tissue, the disease control group showed PPAR-γ expression of 4.200 ± 0.24, while compound SP4f displayed higher activation at 7.84 ± 0.431 compared to compound SP4e with an activation of 7.68 ± 0.65. In zebrafish model, SP4e and SP4f showed significant reductions in blood glucose levels and lipid peroxidation, along with increased glutathione levels and catalase activity. These findings highlighted the potential of SP4e and SP4f as antidiabetic agents, warranting further exploration for therapeutic applications. The in vitro study was performed in HEK-2 cell line, the pioglitazone group demonstrated PPAR-γ expression of EC50 = 575.2, while compound SP4f exhibited enhanced activation at EC50 = 739.0 in contrast to compound SP4e activation of EC50 = 826.7.

Combining machine learning and structure-based approaches to develop oncogene PIM kinase inhibitors

Introduction: PIM kinases are targets for therapeutic intervention since they are associated with a number of malignancies by boosting cell survival and proliferation. Over the past years, the rate of new PIM inhibitors discovery has increased significantly, however, new generation of potent molecules with the right pharmacologic profiles were in demand that can probably lead to the development of Pim kinase inhibitors that are effective against human cancer.

Method: In the current study, a machine learning and structure based approaches were used to generate novel and effective chemical therapeutics for PIM-1 kinase. Four different machine learning methods, namely, support vector machine, random forest, k-nearest neighbour and XGBoost have been used for the development of models. Total, 54 Descriptors have been selected using the Boruta method.

Results: SVM, Random Forest and XGBoost shows better performance as compared to k-NN. An ensemble approach was implemented and, finally, four potential molecules (CHEMBL303779, CHEMBL690270, MHC07198, and CHEMBL748285) were found to be effective for the modulation of PIM-1 activity. Molecular docking and molecular dynamic simulation corroborated the potentiality of the selected molecules. The molecular dynamics (MD) simulation study indicated the stability between protein and ligands.

Discussion: Our findings suggest that the selected models are robust and can be potentially useful for facilitating the discovery against PIM kinase.

Discovery of novel ALK2 inhibitors of pyrazolo-pyrimidines: A computational study

ALK2 is a serine/threonine kinase, involved in different signaling pathways and associated with cell proliferation and differentiation. The present study includes development of pharmacophore, 3-D QSAR, docking and virtual screening studies on 30 different pyrazolo[1,5-a]pyrimidine derivatives. The pharmacophore study provides ARRR_2 hypothesis with four different features essential for ALK2 kinase inhibitory activity. The 3 D-QSAR study determined the statistically significant model by using partial least-square regression (PLS) method with R² value of 0.9711 and Q² value of 0.6846. Validation of 3 D-QSAR has been performed by LOO cross-validation method where with R²CV value of 0.56. The virtual screening study on ZINC database provides compounds such as ZINC66091638, ZINC43524105, ZINC19458227 and ZINC72441013 involved good binding interactions (docking scores -8.91, -7.40, -8.43, and -9.47, respectively) with ALK2 kinase (PDB ID: 3Q4U). The docking study of pyrazolo-pyrimidines derivatives found potent compounds, 7i, 13r, 13d, and 21 with docking scores -9.83, -9.75, -9.76, and -9.75, respectively. The important interactions with amino acid residues were HID 286, ASN341. ADME properties further assist to provide important structural features of ALK2 kinase. The present study may be help to medicinal scientists in the direction to develop potent inhibitors against ALK2 kinase.Communicated by Ramaswamy H. Sarma.

Computational Approaches for the Design of Novel Anticancer Compounds Based on Pyrazolo[3,4-d]pyrimidine Derivatives as TRAP1 Inhibitor

In the present in-silico study, various computational techniques were applied to determine potent compounds against TRAP1 kinase. The pharmacophore hypothesis DHHRR_1 consists of important features required for activity. The 3D QSAR study showed a statistically significant model with R² = 0.96 and Q² = 0.57. Leave one out (LOO) cross-validation (R² CV = 0.58) was used to validate the QSAR model. The molecular docking study showed maximum XP docking scores (−11.265, −10.532, −10.422, −10.827, −10.753 kcal/mol) for potent pyrazole analogs (42, 46, 49, 56, 43), respectively, with significant interactions with amino acid residues (ASP 594, CYS 532, PHE 583, SER 536) against TRAP1 kinase receptors (PDB ID: 5Y3N). Furthermore, the docking results were validated using the 100 ns MD simulations performed for the selected five docked complexes. The selected inhibitors showed relatively higher binding affinities than the TRAP1 inhibitor molecules present in the literature. The ZINC database was used for a virtual screening study that screened ZINC05297837, ZINC05434822, and ZINC72286418, which showed similar binding interactions to those shown by potent ligands. Absorption, distribution, metabolism, and excretion (ADME) analysis showed noticeable results. The results of the study may be helpful for the further development of potent TRAP1 inhibitors

5-[(Z)-5-Chloro-2-oxoindolin-3-ylidene]-3-{(E)-[(4-hydroxyphenyl)imino]methyl}-2-thioxothiazolidin-4-one

N-aminorhodanine as well as isatin are highly solicited motifs known for their wide potential for biological activity. The objective of this work was to synthesize hybrid molecules as kinase inhibitors from these two motifs. In order to study the reactivity of the two active centers in aminorhodanine (N-amino group and the 5-methylene group) toward two carbonyl groups (aromatic aldehyde and ketone of isatin), we decided to carry out a one-pot multi-component reaction by simultaneously introducing aminorhodanine, isatin, and an aromatic aldehyde in ethanol in the presence of AcOEt. Under these conditions, this reaction led to a single adduct. The reaction product structure was confirmed by 1H, 13C-NMR, X-ray single crystal analysis, and high-resolution mass HRMS analysis. As a result, the method used has been very effective and totally stereo- and regioselective.

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.

A Systematic Analysis of the Binding Affinity between the Pim-1 Kinase and Its Inhibitors Based on the MM/3D-RISM/KH Method

A systematic study of the binding affinities of 16 lead compounds targeting the Pim-1 kinase based on the 3D-RISM/KH theory and MD simulations is reported. The results show a correlation coefficient R = 0.69 between the theoretical and experimental values of the binding free energy. This demonstrates that the method is applicable to the problem of compound screening and lead optimization, for which relative values of the free energy among the compounds have significance. We elucidate the contribution of the ligand fragments to the binding free energy. Our results indicate that the interactions between the residues and the triazolo[4,3-b]pyridazine scaffold as well as the phenyl ring of the ligand molecule make significant contributions to stabilization of the complex. Using the 3D-RISM/KH theory, we further analyze the probability distribution of a ligand fragment around the protein-ligand complex in which the substituent around the phenyl ring is removed from the ligand. The results demonstrate that the 3D-RISM/KH theory is capable of predicting the position of substitution on a ligand that has a higher affinity to a target protein.