Structure-based virtual screening, pharmacokinetic prediction, molecular dynamics studies for the identification of novel EGFR inhibitors in breast cancer

Unveiling the Mechanism of the ChaiShao Shugan Formula Against Triple-Negative Breast Cancer

Background

The ChaiShao Shugan Formula (CSSGF) is a traditional Chinese medicine formula with recently identified therapeutic value in triple-negative breast cancer (TNBC). This study aimed to elucidate the underlying mechanism of CSSGF in TNBC treatment.

Methods

TNBC targets were analyzed using R and data were from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The major ingredients and related protein targets of CSSGF were explored via the Traditional Chinese Medicine Systems Pharmacology database, and an ingredient-target network was constructed via Cytoscape to identify hub genes. The STRING database was used to construct the PPI network. GO and KEGG enrichment analyses were performed via R to obtain the main targets. The online tool Kaplan‒Meier plotter was used to identify the prognostic genes. Molecular docking was applied to the core target genes and active ingredients. MDA-MB-231 and MCF-7 cell lines were used to verify the efficacy of the various drugs.

Results

A total of 4562 genes were screened as TNBC target genes. The PPI network consisted of 89 nodes and 845 edges. Our study indicated that quercetin, beta-sitosterol, luteolin and catechin might be the core ingredients of CSSGF, and EGFR and c-Myc might be the latent therapeutic targets of CSSGF in the treatment of TNBC. GO and KEGG analyses indicated that the anticancer effect of CSSGF on TNBC was mainly associated with DNA binding, transcription factor binding, and other biological processes. The related signaling pathways mainly involved the TNF-a, IL-17, and apoptosis pathways. The molecular docking data indicated that quercetin, beta-sitosterol, luteolin, and catechin had high affinity for EGFR, JUN, Caspase-3 and ESR1, respectively. In vitro, we found that CSSGF could suppress the expression of c-Myc or promote the expression of EGFR. In addition, we found that quercetin downregulates c-Myc expression in two BC cell lines.

Conclusion

This study revealed the effective ingredients and latent molecular mechanism of action of CSSGF against TNBC and confirmed that quercetin could target c-Myc to induce anti-BC effects.

Revealing the binding mechanism of BACE1 inhibitors through molecular dynamics simulations

Alzheimer's disease is a debilitating neurodegenerative disorder, and the Beta-Site Amyloid Precursor Protein Cleaving Enzyme 1 (BACE1) is a key therapeutic target in its treatment. This study employs molecular dynamics simulations and binding energy analysis to investigate the binding interactions between BACE1 and four selected small molecules: CNP520, D9W, NB641, and NB360. The binding model analysis indicates that the binding of BACE1 with four molecules are stable, except the loop regions show significant fluctuation. The binding free energy analyses reveal that NB360 exhibits the highest binding affinity with BACE1, surpassing other molecules (CNP520, D9W, and NB641). Detailed energy component assessments highlight the critical roles of electrostatic interactions and van der Waals forces in the binding process. Furthermore, residue contribution analysis identifies key amino acids influencing the binding process across all systems. Hydrogen bond analysis reveals a limited number of bonds between BACE1 and each small molecule, highlighting the importance of structural modifications to enable more stable hydrogen bonds. This research provides valuable insights into the molecular mechanisms of potential Alzheimer's disease therapeutics, guiding the way for improved drug design and the development of effective treatments targeting BACE1.Communicated by Ramaswamy H. Sarma.

A combined in silico approaches of 2D-QSAR, molecular docking, molecular dynamics and ADMET prediction of anti-cancer inhibitor activity for actinonin derivatives

Inhibition of human mitochondrial peptide deformylase (HsPDF) plays a major role in reducing growth, proliferation, and cellular cancer survival. In this work, a series of 32 actinonin derivatives for HsPDF (PDB: 3G5K) inhibitor's anticancer activity was computationally analyzed for the first time, using an in silico study considering 2D-QSAR modeling, and molecular docking studies, and validated by molecular dynamics and ADMET properties. The results of multilinear regression (MLR) and artificial neural networks (ANN) statistical analysis reveal a good correlation between pIC50 activity and the seven (7) descriptors. The developed models were highly significant with cross-validation, the Y-randomization test and their applicability range. In addition, all considered data sets show that the AC30 compound, exhibits the best binding affinity (docking score = -212.074 kcal/mol and H-bonding energy = -15.879 kcal/mol). Furthermore, molecular dynamics simulations were performed at 500 ns, confirming the stability of the studied complexes under physiological conditions and validating the molecular docking results. Five selected actinonin derivatives (AC1, AC8, AC15, AC18 and AC30), exhibiting best docking score, were rationalized as potential leads for HsPDF inhibition, in well agreement with experimental outcomes. Furthermore, based on the in silico study, new six molecules (AC32, AC33, AC34, AC35, AC36 and AC37) were suggested as HsPDF inhibition candidates, which would be combined with in-vitro and in-vivo studies to perspective validation of their anticancer activity. Indeed, the ADMET predictions indicate that these six new ligands have demonstrated a fairly good drug-likeness profile.

Screening of phytochemicals from Clerodendrum inerme (L.) Gaertn as potential anti-breast cancer compounds targeting EGFR: an in-silico approach

Breast cancer (BC) is the most prevalent malignancy among women around the world. The epidermal growth factor receptor (EGFR) is a tyrosine kinase receptor (RTK) of the ErbB/HER family. It is essential for triggering the cellular signaling cascades that control cell growth and survival. However, perturbations in EGFR signaling lead to cancer development and progression. Hence, EGFR is regarded as a prominent therapeutic target for breast cancer. Therefore, in the current investigation, EGFR was targeted with phytochemicals from Clerodendrum inerme (L.) Gaertn (C. inerme). A total of 121 phytochemicals identified by gas chromatography-mass spectrometry (GC-MS) analysis were screened against EGFR through molecular docking, ADMET analyses (Absorption, Distribution, Metabolism, Excretion, and Toxicity), PASS predictions, and molecular dynamics simulation, which revealed three potential hit compounds with CIDs 10586 [i.e. alpha-bisabolol (-6.4 kcal/mol)], 550281 [i.e. 2,(4,4-Trimethyl-3-hydroxymethyl-5a-(3-methyl-but-2-enyl)-cyclohexene) (-6.5 kcal/mol)], and 161271 [i.e. salvigenin (-7.4 kcal/mol)]. The FDA-approved drug gefitinib was used to compare the inhibitory effects of the phytochemicals. The top selected compounds exhibited good ADMET properties and obeyed Lipinski's rule of five (ROF). The molecular docking analysis showed that salvigenin was the best among the three compounds and formed bonds with the key residue Met 793. Furthermore, the molecular mechanics generalized born surface area (MMGBSA) calculations, molecular dynamics simulation, and normal mode analysis validated the binding affinity of the compounds and also revealed the strong stability and compactness of phytochemicals at the docked site. Additionally, DFT and DOS analyses were done to study the reactivity of the compounds and to further validate the selected phytochemicals. These results suggest that the identified phytochemicals possess high inhibitory potential against the target EGFR and can treat breast cancer. However, further in vitro and in vivo investigations are warranted towards the development of these constituents into novel anti-cancer drugs.Communicated by Ramaswamy H. Sarma.

Exploring the Promotive Effects and Mechanisms of Different Polyphenolic Extracts from Prinsepia utilis Royle Seed Shell on Tyrosinase

Prinsepia utilis Royle (P. utilis) is commonly used as a food ingredient and herbal medicine according to folk records, yet little research has been done on the seed shell, a processing waste. The aim of this study was to investigate the distribution of polyphenolic components and the tyrosinase activation activity of different extracts from the seed shell by UHPLC-ESI-HRMS/MS, in vitro tyrosinase activity assay, molecular docking and molecular dynamics. A total of 16 phytochemicals were identified, of which (+)-catechin and (-)-epicatechin were the major polyphenolic compounds. Both the esterified and insoluble bound polyphenols exhibited tyrosinase activation activity, and the esterified polyphenols showed better tyrosinase activation activity. (+)-Catechin and (-)-epicatechin might be the main activators of tyrosinase, both of which may act as substrate to affect tyrosinase activity. By molecular docking and molecular dynamics simulation studies, (+)-catechin and (-)-epicatechin can be efficiently and stably bound to the tyrosinase active site through hydrogen bonds, van der Waals forces and π-bonds. The results of this study may not only provide a scientific basis for exploring P. utilis seed shell as a potential activator of tyrosinase, but also contribute to the high value utilization of P. utilis processing by-products.

Structure-based pharmacophore mapping and virtual screening of natural products to identify polypharmacological inhibitor against c-MET/EGFR/VEGFR-2

Three receptor tyrosine kinases (RTKs), c-MET, EGFR, and VEGFR-2 have been identified as potential oncogenic targets involved in tumor development, metastasis, and invasion. Designing inhibitors that can simultaneously interact with multiple targets is a promising approach, therefore, inhibiting these three RTKs with a single chemical component might give an effective chemotherapeutic strategy for addressing the disease while limiting adverse effects. The in-silico methods have been developed to identify the polypharmacological inhibitors particularly for drug repurposing and multitarget drug design. Here, to find a viable inhibitor from natural source against these three RTKs, structure-based pharmacophore mapping and virtual screening of SN-II database were carried out. The filtered compound SN00020821, identified as Cedeodarin, from different computational approaches, demonstrated good interactions with all the three targets, c-MET/EGFR/VEGFR-2, with interaction energies of -42.35 kcal/mol, -49.32 kcal/mol and -44.83 kcal/mol, respectively. SN00020821displayed stable key interactions with critical amino acids of all the three receptors' kinase catalytic domains including "DFG motif" explored through the MD simulations. Furthermore, it also met the ADMET requirements and was determined to be drug-like as predicted from the Lipinski's rule of five and Veber's rule. Finally, SN00020821 provides a novel molecular scaffold that could be investigated further as a polypharmacological anticancer therapeutic candidate that targets the three RTKs.Communicated by Ramaswamy H. Sarma.