In silico exploration of c-KIT inhibitors by pharmaco-informatics methodology: pharmacophore modeling, 3D QSAR, docking studies, and virtual screening

Mechanistic insights into the P-coumaric acid protection against bisphenol A-induced hepatotoxicity in in vivo and in silico models

Bisphenol A (BPA), commonly found in plastic containers and epoxy resins used for food products, presents substantial health risks, particularly in relation to hepatic toxicity. This study investigates BPA-induced liver damage and explores the mechanistic dose-dependent protective effects of P-coumaric acid (PCA). 50 male rats were divided into control, BPA-treated, BPA + PCA50, BPA + PCA100, and PCA100 groups. BPA exposure for 14 days induced oxidative stress, evidenced by elevated malondialdehyde levels and decreased activities of antioxidant enzymes (superoxide dismutase, glutathione peroxidase, and catalase). Higher doses of PCA effectively mitigated these effects by restoring redox balance and enhancing antioxidant enzyme activities. Additionally, BPA disrupted inflammation and apoptosis pathways, inhibiting anti-inflammatory markers and interfering with the nuclear factor erythroid 2-related factor 2/heme oxygenase-1 (Nrf2/HO-1) pathway. PCA exhibited dose-dependent protection against these disruptions. Computational analyses revealed that BPA inhibits cyclooxygenase-1 through stable hydrogen bonding with threonine at position 322. PCA's dual protective effect was confirmed by attenuating inflammatory pathways, including TNF-α inhibition and suppression of the Kelch-like ECH-associated protein 1 (KEAP1) and Nrf2 signaling pathway. Histopathological assessments confirmed that PCA alleviated significant hepatic damage induced by BPA. Immunohistochemical and immunofluorescence analyses further supported PCA's protective role against BPA-induced apoptosis and cellular hepatotoxicity. These findings underscore PCA's protective potential against BPA-induced hepatotoxicity and highlight novel mechanistic interactions that warrant further investigation in applied nutritional biochemistry.

Gallic acid's protective mechanisms against acrylamide-induced pulmonary injury: in vivo and in silico insights into the Nrf-2/HO-1/NFκB pathway modulation

Acrylamide (ACR) is a toxic compound formed during the heating of tobacco and starchy foods, contributing to increased reactive oxygen species (ROS) levels and significant health risks. This study evaluates the protective effects of gallic acid (GA), a natural polyphenol with potent antioxidant and anti-inflammatory properties, against ACR-induced lung injury. Fifty male rats were divided into five groups: Control, ACR, GA50 + ACR, GA100 + ACR, and GA100. Lung tissues were analyzed biochemically, histopathologically, immunohistochemically, and via immunofluorescence. GA exhibited dose-dependent protective effects by enhancing antioxidant defenses through Nrf-2 (43% increase) and HO-1 activation and reducing lipid peroxidation markers (MDA decreased by 38%). GA also suppressed pro-inflammatory mediators (TNF-α reduced by 35%) and restored anti-inflammatory levels by modulating the NF-κB pathway. Furthermore, GA reduced apoptosis (Caspase-3 activity decreased by 30%) and preserved lung tissue integrity by mitigating oxidative DNA damage (8-OHdG levels reduced by 29%) and pro-apoptotic signaling (Bax levels reduced by 34%). Computational analyses demonstrated GA's interaction with the KEAP1 protein, supporting its role in activating the KEAP1-Nrf2 pathway. These findings highlight GA's antioxidant, anti-inflammatory, and anti-apoptotic properties, suggesting its therapeutic potential for protecting against ACR-induced lung injury and paving the way for future research in lung health and toxicology.

Discovery and Anticancer Activity of Novel 1,3,4-Thiadiazole- and Aziridine-Based Indolin-2-ones via In Silico Design Followed by Supramolecular Green Synthesis

Three crucial anticancer scaffolds, namely indolin-2-one, 1,3,4-thiadiazole, and aziridine, are explored to synthesize virtually screened target molecules based on the c-KIT kinase protein. The stem cell factor receptor c-KIT was selected as target because most U.S. FDA-approved receptor tyrosine kinase inhibitors bearing the indolin-2-one scaffold profoundly inhibit c-KIT. Molecular hybrids of indolin-2-one with 1,3,4-thiadiazole (IIIa-m) and aziridine (VIa and VIc) were afforded through a modified Schiff base green synthesis using β-cyclodextrin-SO₃H in water as a recyclable proton-donor catalyst. A computational study found that indolin-2,3-dione forms a supramolecular inclusion complex with β-cyclodextrin-SO₃H through noncovalent interactions. A molecular docking study of all the synthesized compounds was executed on the c-KIT kinase domain, and most compounds displayed binding affinities similar to that of Sunitinib. On the basis of the pharmacokinetic significance of the aryl thioether linkage in small molecules, 1,3,4-thiadiazole hybrids (IIIa-m) were extended to a new series of 3-((5-(phenylthio)-1,3,4-thiadiazol-2-yl)imino)indolin-2-ones (IVa-m) via thioetherification using bis(triphenylphosphine)palladium(II)dichloride as the catalyst for C-S bond formation. Target compounds were tested against NCI-60 human cancer cell lines for a single-dose concentration. Among all three series of indolin-2-ones, the majority of compounds demonstrated broad-spectrum activity toward various cancer cell lines. Compounds IVc and VIc were further evaluated for a five-dose anticancer study. Compound IVc showed a potent activity of IC₅₀ = 1.47 μM against a panel of breast cancer cell lines, whereas compound VIc exhibited the highest inhibition for a panel of colon cancer cell lines at IC₅₀ = 1.40 μM. In silico ADME property descriptors of all the target molecules are in an acceptable range. Machine learning algorithms were used to examine the metabolites and phase I and II regioselectivities of compounds IVc and VIc, and the results suggested that these two compounds could be potential leads for the treatment of cancer.

Computational identification of 2,4-disubstituted amino-pyrimidines as L858R/T790M-EGFR double mutant inhibitors using pharmacophore mapping, molecular docking, binding free energy calculation, DFT study and molecular dynamic simulation

Pharmacophore modelling studies have been performed for a series of 2,4-disubstituted-pyrimidines derivatives as EGFR L858R/T790M tyrosine kinase inhibitors. The high scoring AARR.15 hypothesis was selected as the best pharmacophore model with the highest survival score of 3.436 having two hydrogen bond acceptors and two aromatic ring features. Pharmacophore-based virtual screening followed by structure-based yielded the six molecules (ZINC17013227, ZINC17013215, ZINC9573324, ZINC9573445, ZINC24023331 and ZINC17013503) from the ZINC database with significant in silico predicted activity and strong binding affinity towords the EGFR L858R/T790M tyrosine kinase. In silico toxicity and cytochrome profiling indicates that all the 06 virtually screened compounds were substrate/inhibitors of the CYP-3A4 metabolizing enzyme and were non-carcinogenic and devoid of Ames mutagenesis. Density functional theory (DFT) and molecular dynamic (MD) simulation further validated the obtained hits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-021-00113-x.

A holistic view on c-Kit in cancer: Structure, signaling, pathophysiology and its inhibitors

Receptor tyrosine kinases play an important role in many cellular processes, and their dysregulation leads to diseases, most importantly cancer. One such receptor tyrosine kinase is c-Kit, a type-III receptor tyrosine kinase, which is involved in various intracellular signaling pathways. The role of different mutant isoforms of c-Kit has been established in several types of cancers. Accordingly, promising c-Kit inhibition results have been reported for the treatment of different cancers (e.g., gastrointestinal stromal tumors, melanoma, acute myeloid leukemia, and other tumors). Therefore, lots of effort has been put to target c-Kit for the treatment of cancer. Here, we provide a comprehensive compilation to provide an insight into c-Kit inhibitor discovery. This compilation provides key information regarding the structure, signaling pathways related to c-Kit, and, more importantly, pharmacophores, binding modes, and SAR analysis for almost all small-molecule heterocycles reported for their c-Kit inhibitory activity. This work could be used as a guide in understanding the basic requirements for targeting c-Kit, and how the selectivity and efficacy of the molecules have been achieved till today.

Discovery of novel potential KIT inhibitors for the treatment of gastrointestinal stromal tumor

Numerous inhibitors of tyrosine-protein kinase KIT, a receptor tyrosine kinase, have been explored as a viable therapy for the treatment of gastrointestinal stromal tumor (GIST). However, drug resistance due to acquired mutations in KIT makes these drugs almost useless. The present study was designed to screen the novel inhibitors against the activity of the KIT mutants through pharmacophore modeling and molecular docking. The best two pharmacophore models were established using the KIT mutants’ crystal complexes and were used to screen the new compounds with possible KIT inhibitory activity against both activation loop and ATP-binding mutants. As a result, two compounds were identified as potential candidates from the virtual screening, which satisfied the potential binding capabilities, molecular modeling characteristics, and predicted absorption, distribution, metabolism, excretion, toxicity (ADMET) properties. Further molecular docking simulations showed that two compounds made strong hydrogen bond interaction with different KIT mutant proteins. Our results indicated that pharmacophore models based on the receptor–ligand complex had excellent ability to screen KIT inhibitors, and two compounds may have the potential to develop further as the future KIT inhibitors for GIST treatment.

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.

Hyphenated 3D-QSAR statistical model-drug repurposing analysis for the identification of potent neuraminidase inhibitor

The Influenza A virus is one of the principle causes of respiratory illness in human. The surface glycoprotein of the influenza virus, neuraminidase (NA), has a vital role in the release of new viral particle and spreads infection in the respiratory tract. It has been long recognized as a valid drug target for influenza A virus infection. Oseltamivir is used as a standard drug of choice for the treatment of influenza. However, the emergence of mutants with novel mutations has increased the resistance to potent NA inhibitor. In the present investigation, we have employed computer-assisted combinatorial techniques in the screening of 8621 molecules from Drug Bank to find potent NA inhibitors. A three-dimensional pharmacophore model was generated from the previously reported 28 carbocylic influenza NA inhibitors along with oseltamivir using PHASE module of Schrödinger Suite. The model generated consists of one hydrogen bond acceptor (A), one hydrogen bond donors (D), one hydrophobic group (H), and one positively charged group (P), ADHP. The hypothesis was further validated for its integrity and significance using enrichment analysis. Subsequently, an atom-based 3D-QSAR model was built using the common pharmacophore hypothesis (CPH). The developed 3D-QSAR model was found to be statistically significant with R² value of 0.9866 and Q² value of 0.7629. Further screening was accomplished using three-stage docking process using the Glide algorithm. The resultant lead molecules were examined for its drug-like properties using the Qikprop algorithm. Finally, the calculated pIC₅₀ values of the lead compounds were validated by the AutoQSAR algorithm. Overall, the results from our analysis highlights that lisinopril (DB00722) is predicted to bind better with NA than currently approved drug. In addition, it has the best match in binding geometry conformations with the existing NA inhibitor. Note that the antiviral activity of lisinopril is reported in the literature. However, our paper is the first report on lisinopril activity against influenza A virus infection. These results are envisioned to help design the novel NA inhibitors with an increased antiviral efficacy.

Design, synthesis, biological assessment and molecular docking studies of new 2-aminoimidazole-quinoxaline hybrids as potential anticancer agents

In a search for novel antiproliferative agents, a series of quinoxaline derivatives containing 2-aminoimidazole (8a-8x) were designed and synthesized. The structures of synthesized compounds were confirmed by IR, ¹H NMR, ¹³C NMR, Mass Spectroscopy and analyzed using HSQC, COSY, ROESY, HMBC techniques. The anticancer activity of all derivatives were evaluated for colon cancer and breast cancer cell lines by the MTT assay and acridine orange/ethidium bromide double staining method. The anti-cancer effect in human colon cancer (HCT-116) and breast cancer (MCF-7) cell lines exhibited that compounds 8a, 8s, 8t, 8w, 8x appeared as potent antiproliferative agents and especially inhibited the human colon cancer cell proliferation with percentage of inhibition by over 50%. The most active compound was (E)-4-phenyl-1-((quinoxalin-2-ylmethylene)amino)-1H-imidazol-2-amine (8a) with the highest inhibition for MCF-7 (83.3%) and HCT-116 (70%) cell lines after 48 and 24h, respectively. Molecular docking studies of these derivatives within c-kit active site as a validated target might be suggested them as appropriate candidates for further efforts toward more potent anticancer compounds.

Design, sythesis and evaluation of a series of 3- or 4-alkoxy substituted phenoxy derivatives as PPARs agonists

Peroxisome proliferators-activated receptors (PPARα, γ and δ) are potentially effective targets for Type 2 diabetes mellitus therapy. The severe effects of known glitazones and the successfully approved agents (saroglitazar and lobeglitazone) motivated us to study novelly potent PPARs drugs with improved safety profile. In this work, we received 15 carboxylic acids based on the combination principle to integrate the polar head of bezafibrate with the hydrophobic tail of pioglitazone. Another 12 tetrazoles based on the bioisosterism principle were obtained accordingly. Furthermore, in vitro PPARs transactivation assays on these 3- or 4-alkoxy substituted phenoxy derivatives afforded six compounds. Interactions and binding stability from the docking analysis and 20 ns molecular dynamic simulations confirmed the representative compounds to be suitable and plausible for PPARs pockets. The above-mentioned results demonstrated that the compounds may be used as reference for further optimization for enhanced PPARs activities and wide safety range.

QSAR modeling and in silico design of small-molecule inhibitors targeting the interaction between E3 ligase VHL and HIF-1α

Protein-protein interactions (PPIs) have attracted much attention recently because of their preponderant role in most biological processes. The prevention of the interaction between E3 ligase VHL and HIF-1[Formula: see text] may improve tolerance to hypoxia and ameliorate the prognosis of many diseases. To obtain novel potent inhibitors of VHL/HIF-1[Formula: see text] interaction, a series of hydroxyproline-based inhibitors were investigated for structural optimization using a combination of QSAR modeling and molecular docking. Here, 2D- and 3D-QSAR models were developed by genetic function approximation (GFA) and comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods, respectively. The top-ranked models with strict validation revealed satisfactory statistical parameters (CoMFA with [Formula: see text], 0.637; [Formula: see text], 0.955; [Formula: see text], 0.944; CoMSIA with [Formula: see text], 0.649; [Formula: see text], 0.954; [Formula: see text], 0.911; GFA with [Formula: see text], 0.721; [Formula: see text], 0.801; [Formula: see text], 0.861). The selected five 2D-QSAR descriptors were in good accordance with the 3D-QSAR results, and contour maps gave the visualization of feature requirements for inhibitory activity. A new diverse molecular database was created by molecular fragment replacement and BREED techniques for subsequent virtual screening. Eventually, 31 novel hydroxyproline derivatives stood out as potential VHL/HIF-1[Formula: see text] inhibitors with favorable predictions by the CoMFA, CoMSIA and GFA models. The reliability of this protocol suggests that it could also be applied to the exploration of lead optimization of other PPI targets.