3D-QSAR, docking and molecular dynamics simulations of novel Pyrazolo-pyridazinone derivatives as covalent inhibitors of FGFR1: a scientific approach for possible anticancer agents

Novel pyridazinone derivatives bind to KSRP: Synthesis, anti-tumor biological evaluations and modelling insights

Pyridazinone derivatives have been extensively used as anticancer agents. IMB5036 is a structure specific pyridazinone compound with potential antitumor activity via targeting KSRP protein which controls gene expression at multiple levels. In this study, fifteen IMB5036 analogues were synthesized and preliminary structure-activity relationships were explored. Among them, compounds 8 and 10 exhibited remarkably anti-proliferation of various cancer cells and a good cancer cell selectivity (against human fetal hepatocyte L02 cells). More detailed investigation was included that both 8 and 10 inhibited colony formation and migration in concentration-dependent mode against MCF-7 cells. Additionally, 8 and 10 induced apoptosis and cell cycle arrest, decreased mitochondrial membrane potential, damaged DNA, and increased reactive oxygen species. Moreover, 8 displayed a potent antitumor efficacy (TGI = 74.2 %, at a dose of 30 mg/kg) in MCF-7 xenograft model by i.p. injection. Further, we synthesized a biotinylated probe 16 for identifying the detail domain of KSRP. Through pull down assay and molecular docking study, we validated that the KH23 domain functioned as the binding pocket for the compounds. Thus, compound 8 was identified as a novel targeting KSRP pyridazinone-based compound and exhibited excellent antitumor activity both in vitro and in vivo.

Deciphering quinazoline derivatives' interactions with EGFR: a computational quest for advanced cancer therapy through 3D-QSAR, virtual screening, and MD simulations

Introduction

The epidermal growth factor receptor (EGFR) presents a crucial target for combatting cancer mortality.

Methods

This study employs a suite of computational techniques, including 3D-QSAR, ligand-based virtual screening, molecular docking, fingerprinting analysis, ADME, and DFT-based analyses (MESP, HOMO, LUMO), supplemented by molecular dynamics simulations and MMGB/PBSA free energy calculations, to explore the binding dynamics of quinazoline derivatives with EGFR. With strong q2 and r2 values from CoMFA and CoMSIA models, our 3D- QSAR models reliably predict EGFR inhibitors' efficacy.

Results and Discussion

Utilizing a potent model compound as a reference, an E-pharmacophore model was developed to sift through the eMolecules database, identifying 19 virtual screening hits based on ShapeTanimoto, ColourTanimoto, and TanimotoCombo scores. These hits, assessed via 3D- QSAR, showed pIC50 predictions consistent with experimental data. Our analyses elucidate key features essential for EGFR inhibition, reinforced by ADME studies that reveal favorable pharmacokinetic profiles for most compounds. Among the primary phytochemicals examined, potential EGFR inhibitors were identified. Detailed MD simulation analyses on three select ligands-1Q1, 2Q17, and VS1-demonstrated their stability and consistent interaction over 200 ns, with MM/GBSA values corroborating their docking scores and highlighting 1Q1 and VS1's superior EGFR1 affinity. These results position VS1 as an especially promising lead in EGFR1 inhibitor development, contributing valuable insights towards crafting novel, effective EGFR1 inhibitors.

Sanggenol B, a plant bioactive, as a safer alternative to tackle cancer by antagonising human FGFR

Fibroblast Growth Receptor Factor (FGFR) are a family of proteins which are, in addition to their biological role, are involved in various pathological functions, such as cancer cellular proliferation, and metastasis. Deregulation of FGFRs at various points could result in malignancy. A conformational transition of the DFG (Asp-Phe-Gly) motif can switch the enzyme from a catalytically active (DFG-in) to an inactive (DFG-out) state. There are a few FDFR inhibitors which have received approval from the FDA, but these have adverse side effects. Hence, there is a demand for safer alternatives. With this aim, Ligand and Structure based virtual screening was carried to identify suitable lead molecule. In this process, Four Featured atom-based 3D Pharmacophore with quantitative structure-activity relationship analysis (3D-QSAR) was developed. The External validation of the hypothesis was carried invoking criteria such as Area under the ROC curve. Natural plant compound databases such as the Traditional Chinese medicine, NPACT and the ZINC Natural databases were chosen for pharmacophore filtering, which was followed by virtual screening against FGFR isoforms. The compound Sanggenol B was identified as the most suitable lead molecule. Structural stability of the protein-ligand complex and interactions of the ligand (Sanggenol B & the reference compound Ponatinib) with FGFR were analysed for 1000 ns (triplicate) by means of molecular simulation and the binding free energy was calculated using MMGBSA. Sanggenol B (PubChem CID: 15233694) binds effectively at the active site with favourable energies and is proposed as a safe alternative from a natural source.Communicated by Ramaswamy H. Sarma.

Exploring potential molecular targets and therapeutic efficacy of beauvericin in triple-negative breast cancer cells

Triple negative breast cancer (TNBC) presents a significant global health concern due to its aggressive nature, high mortality rate and limited treatment options, highlighting the urgent need for targeted therapies. Beauvericin, a bioactive fungal secondary metabolite, possess significant anticancer potential, although its molecular targets in cancer cells remain unexplored. This study has investigated possible molecular targets of beauvericin and its therapeutic insights in TNBC cells. In silico studies using molecular docking and MD simulation predicted the molecular targets of beauvericin. The identified targets included MRP-1 (ABCC1), HDAC-1, HDAC-2, LCK and SYK with average binding energy of -90.1, -44.3, -72.1, -105 and -60.8 KJ/mol, respectively, implying its multifaceted roles in reversing drug resistance, inhibiting epigenetic modulators and oncogenic tyrosine kinases. Beauvericin has significantly reduced the viability of MDA-MB-231 and MDA-MB-468 cells, with IC50 concentrations of 4.4 and 3.9 µM, while concurrently elevating the intracellular ROS by 9.0 and 7.9 folds, respectively. Subsequent reduction of mitochondrial transmembrane potential in TNBC cells, has confirmed the induction of oxidative stress, leading to apoptotic cell death, as observed by flow cytometric analyses. Beauvericin has also arrested cell cycle at G1-phase and impaired the spheroid formation and clonal expansion abilities of TNBC cells. The viability of spheroids was reduced upon beauvericin treatment, exhibiting IC50 concentrations of 10.3 and 6.2 µM in MDA-MB-468 and MDA-MB-231 cells, respectively. In conclusion, beauvericin has demonstrated promising therapeutic potential against TNBC cells through possible inhibition of MRP-1 (ABCC1), HDAC-1, HDAC-2, LCK and SYK.

Network Pharmacology and Experimental Verification Reveal the Regulatory Mechanism of Chuanbeimu in Treating Chronic Obstructive Pulmonary Disease

Background

Chronic obstructive pulmonary disease (COPD) is a common respiratory disorder in pulmonology. Chuanbeimu (CBM) is a traditional Chinese medicinal herb for treating COPD and has been widely utilized in clinical practice. However, the mechanism of CBM in the treatment of COPD remains incompletely understood. This study aims to investigate the underlying therapeutic mechanism of CBM for COPD using network pharmacology and experimental approaches.

Methods

Active ingredients and their targets were obtained from the Traditional Chinese Medicine Systems Pharmacology database. COPD-associated targets were retrieved from the GeneCards database. The common targets for CBM and COPD were identified through Venn diagram analysis. Protein-protein interaction (PPI) networks and disease-herb-ingredient-target networks were constructed. Subsequently, the results of the network pharmacology were validated by molecular docking and in vitro experiments.

Results

Seven active ingredients and 32 potential targets for CBM were identified as closely associated with COPD. The results of the disease-herb-ingredient-target network and PPI network showed that peimisine emerged as the core ingredient, and SRC, ADRB2, MMP2, and NOS3 were the potential targets for CBM in treating COPD. Molecular docking analysis confirmed that peimisine exhibited high binding affinity with SRC, ADRB2, MMP2, and NOS3. In vitro experiments demonstrated that peimisine significantly upregulated the expression of ADRB2 and NOS3 and downregulated the expression of SRC and MMP2.

Conclusion

These findings indicate that CBM may modulate the expression of SRC, ADRB2, MMP2, and NOS3, thereby exerting a protective effect against COPD.

Integrated computational approaches for designing potent pyrimidine-based CDK9 inhibitors: 3D-QSAR, docking, and molecular dynamics simulations

CDK9 is an emerging target for the development of anticancer drugs. The development of CDK9 inhibitors with significant potency had consistently posed a formidable challenge. In the current research, a number of computational methodologies, such as, 3D-QSAR, molecular docking, fingerprint analysis, molecular dynamic (MD) simulations followed by MMGB/PBSA and ADMET studies were used systemically to uncover the binding mechanism of pyrimidine derivatives against CDK9. The CoMFA and CoMSIA models having high q2 (0.53, 0.54) and r2 values (0.96, 0.93) respectively indicating that model could accurately predict the bioactivities of CDK9 inhibitors. Using the R-group exploration technique implemented by the Spark™ by Cresset group, the structural requirements revealed by the contour maps of model were utilized strategically to create an in-house library of 100 new CDK9 inhibitors. Additionally, the compounds from the in-house library were mapped into 3D-QSAR model which predicted pIC50 values comparable to the experimental values. A comparison between 3D-QSAR generated contours and molecular docking conformation of ligands was performed to elucidate the essentials of CDK9 inhibitor design. MD simulations (100 ns) were performed on the selected docked complexes A21, A14 and D98 which contributed in validating the binding interactions. According to the findings of binding free energy analysis (MMGB/PBSA), It was observed that residues CYS106 and GLU107 had a considerable tendency to facilitate ligand-protein interactions via H-bond interactions. The aforementioned findings have the potential to enhance researchers comprehension of the mechanism underlying CDK9 inhibition and may be utilized in the development of innovative and efficacious CDK9 inhibitors.