Dibenzepinones, dibenzoxepines and benzosuberones based p38α MAP kinase inhibitors: Their pharmacophore modelling, 3D-QSAR and docking studies

Small Molecule Compound DHPA Screened by Computer-Aided Drug Design and Molecular Dynamics Simulation Inhibits Neuroblastoma Cell Proliferation by Targeting TrkB

Neuroblastoma (NB) is a rare and malignant pediatric solid tumor. Due to its heterogeneity, it poses significant challenges for treatment, resulting in a high mortality rate. This study aimed to identify new therapeutic drugs by modeling the TrkB receptor from PDB 4AT5 and conducting virtual screening of compounds from the YaTCM database (containing 47,696 compounds derived from 6220 Traditional Chinese Medicines). The screening utilized the E-pharmacophore approach to select compounds with potential binding affinity to TrkB. The binding abilities of these compounds were tested through molecular dynamics simulations, stretch dynamics simulations, and US simulations. Among the top 11 optimized hit compounds, DHPA and 3″-demethylhexahydrocurcumin are prominent. Further simulations reveal that they form stable receptor-ligand binary complexes with TrkB. In subsequent in vitro cell experiments, 3″-demethylhexahydrocurcumin is eliminated due to its high IC50 for killing NB cells. Low concentrations of DHPA can significantly kill NB cells. Additionally, DHPA can inhibit the expression of TrkB, the activation of TrkB's downstream signaling pathways, and affect the thermal stability of TrkB protein and its response to streptase protease degradation. DHPA may be a potential TrkB inhibitor.

Identification of novel curcumin derivatives against pancreatic cancer: a comprehensive approach integrating 3D-QSAR pharmacophore modeling, virtual screening, and molecular dynamics simulations

Pancreatic cancer, known as the "silent killer," poses a daunting challenge in cancer therapy. The dysregulation of the PI3Kα signaling pathway in pancreatic cancer has attracted considerable interest as a promising target for therapeutic intervention. In this regard, the use of curcumin derivatives as inhibitors of PI3Kα has emerged, providing a novel and promising avenue for developing effective treatments for this devastating disease. Computational approaches were employed to explore this potential and investigate 58 curcumin derivatives with cytotoxic activity against the Panc-1 cell line. Our approach involved ligand-based pharmacophore modeling and atom-based 3D-QSAR analysis. The resulting QSAR model derived from the best-fitted pharmacophore hypothesis (AAHRR_1) demonstrated remarkable performance with high correlation coefficients (R2) of 0.990 for the training set and 0.977 for the test set. The cross-validation coefficient (Q2) of 0.971 also validated the model's predictive power. Tropsha's recommended criteria, including the Y-randomization test, were employed to ensure its reliability. Furthermore, an enrichment study was conducted to evaluate the model's performance in identifying active compounds. AAHRR_1 was used to screen a curated PubChem database of curcumin-related compounds. Two molecules (CID156189304 and CID154728220) exhibited promising pharmacokinetic properties and higher docking scores than Alpelisib, warranting further investigation. Extensive molecular dynamics simulations provided crucial insights into the conformational dynamics within the binding site, validating their stability and behavior. These findings contribute to our understanding of the potential therapeutic effectiveness of these compounds as PI3Kα inhibitors in pancreatic cancer.Communicated by Ramaswamy H. Sarma.

Design, synthesis and evaluation of 5-chloro-6-methylaurone derivatives as potential anti-cancer agents

A series of novel 5-chloro-6-methylaurone derivatives (6a-p) were synthesized and characterized by various spectroscopic techniques. The synthesized compounds were tested for anticancer activity against 60-human cancer cell line panel derived from nine cancer types at NCI, Bethesda, USA. Among the synthesized compounds, six compounds (6e, 6f, 6h, 6i, 6k and 6 m) exhibited growth inhibition and cytotoxic activity against various human cancer cell lines in one-dose data. The most potent compound among the series, 6i was active against 55 out of 60 human cancer cell lines. Compound 6i showed remarkable % growth inhibition and cytotoxicity against various cancer cell lines exhibiting % GI in the range 36.05-199.03. The compound 6i was further evaluated for five dose assay and exhibited GI50 1.90 µM and 2.70 µM against melanoma and breast cancer cell lines respectively. Further evaluation of 6i for five-dose assay exhibited a diverse spectrum of anti-cancer activity towards all the 60 human cancer cell line panel with the selectivity index ratio ranging 0.854-1.42  and 0.66-1.35  for GI50 and TGI respectively. Based on one-dose and five-dose data compound 6i was further evaluated for cell apoptosis against MDA-MB-468 breast cancer cell line and was found to induce early apoptosis in cells explaining its mode of action. The in-silico studies for the synthesized compounds as LSD1 inhibitors (2H94) have shown better docking score and binding energy comparable to vafidemstat. All the compounds followed Lipinski rule of five. These findings concluded that the compound 6i could lead to the development of a promising therapeutic anticancer agent.

Binding mechanism of inhibitors to p38α MAP kinase deciphered by using multiple replica Gaussian accelerated molecular dynamics and calculations of binding free energies

The p38α MAP Kinase has been an important target of drug design for treatment of inflammatory diseases and cancers. This work applies multiple replica Gaussian accelerated molecular dynamics (MR-GaMD) simulations and the molecular mechanics generalized Born surface area (MM-GBSA) method to probe the binding mechanism of inhibitors L51, R24 and 1AU to p38α. Dynamics analyses show that inhibitor bindings exert significant effect on conformational changes of the active helix α2 and the conserved DFG loop. The rank of binding free energies calculated with MM-GBSA not only agrees well with that determined by the experimental IC50 values but also suggests that mutual compensation between the enthalpy and entropy changes can improve binding of inhibitors to p38α. The analyses of free energy landscapes indicate that the L51, R24 and 1AU bound p38α display a DFG-out conformation. The residue-based free energy decomposition method is used to evaluate contributions of separate residues to the inhibitor-p38α binding and the results imply that residues V30, V38, L74, L75, I84, T106, H107, L108, M109, L167, F169 and D168 can be utilized as efficient targets of potent inhibitors toward p38α.

Computational Identification of Potential Anti-Inflammatory Natural Compounds Targeting the p38 Mitogen-Activated Protein Kinase (MAPK): Implications for COVID-19-Induced Cytokine Storm

Severely ill coronavirus disease 2019 (COVID-19) patients show elevated concentrations of pro-inflammatory cytokines, a situation commonly known as a cytokine storm. The p38 MAPK receptor is considered a plausible therapeutic target because of its involvement in the platelet activation processes leading to inflammation. This study aimed to identify potential natural product-derived inhibitory molecules against the p38α MAPK receptor to mitigate the eliciting of pro-inflammatory cytokines using computational techniques. The 3D X-ray structure of the receptor with PDB ID 3ZS5 was energy minimized using GROMACS and used for molecular docking via AutoDock Vina. The molecular docking was validated with an acceptable area under the curve (AUC) of 0.704, which was computed from the receiver operating characteristic (ROC) curve. A compendium of 38,271 natural products originating from Africa and China together with eleven known p38 MAPK inhibitors were screened against the receptor. Four potential lead compounds ZINC1691180, ZINC5519433, ZINC4520996 and ZINC5733756 were identified. The compounds formed strong intermolecular bonds with critical residues Val38, Ala51, Lys53, Thr106, Leu108, Met109 and Phe169. Additionally, they exhibited appreciably low binding energies which were corroborated via molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. The compounds were also predicted to have plausible pharmacological profiles with insignificant toxicity. The molecules were also predicted to be anti-inflammatory, kinase inhibitors, antiviral, platelet aggregation inhibitors, and immunosuppressive, with probable activity (Pa) greater than probable inactivity (Pi). ZINC5733756 is structurally similar to estradiol with a Tanimoto coefficient value of 0.73, which exhibits anti-inflammatory activity by targeting the activation of Nrf2. Similarly, ZINC1691180 has been reported to elicit anti-inflammatory activity in vitro. The compounds may serve as scaffolds for the design of potential biotherapeutic molecules against the cytokine storm associated with COVID-19.