Issue #5: Integrated cytotoxicity screening and in silico analysis of coumarin nucleoside conjugates as computationally modeled VEGFR-2 inhibitors: oncocyte cytotoxicity, molecular docking, and dynamics simulation studies.

🚀 Today’s Top Signal

Integrated cytotoxicity screening and in silico analysis of coumarin nucleoside conjugates as computationally modeled VEGFR-2 inhibitors: oncocyte cytotoxicity, molecular docking, and dynamics simulation studies.

🧬 Abstract

The development of small-molecule tyrosine kinase inhibitors remains a high-priority strategy in modern oncology, particularly those targeting the Vascular Endothelial Growth Factor Receptor 2 (VEGFR-2) to disrupt pathological angiogenesis. This study utilized a dual-methodology approach to evaluate a novel series of five coumarin nucleoside conjugates ( 5a - 5e ) as potential anti-cancer agents. Initially, the compounds’ drug-likeness was confirmed via ADMET prediction, which established favorable pharmacokinetic profiles. This was followed by an integrated MTT cytotoxicity screening against Oct1 (head and neck) and C33a (cervical) cancer cell lines, which identified compound 5d as the most potent cellular agent. The core of the investigation involved a comprehensive in silico analysis targeting the VEGFR-2 tyrosine kinase domain (TKD). Molecular docking revealed that all five compounds possess significantly superior predicted binding affinities compared to the native ligand, ATP (- 25.44 kJ/mol). Critically, the primary cellular lead 5d (- 29.46 kJ/mol) and the strongest binder 5e (- 31.30 kJ/mol) both surpassed the affinity of the clinical benchmark, Sorafenib (- 28.80 kJ/mol), confirming their high potential as competitive inhibitors. Further validation using Molecular Dynamics (MD) simulation and MMPBSA analysis demonstrated exceptional dynamic stability and thermodynamic preference for the TKD-ligand complexes, firmly supporting the predicted binding hypothesis. In conclusion, compounds 5d and 5e are validated lead candidates possessing favorable absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, direct cellular cytotoxicity, and a robust computationally modeled dual-action profile. Future research is urgently mandated to perform VEGFR-2-specific functional assays to definitively validate the predicted anti-angiogenic mechanism and conduct in-vivo studies to assess therapeutic efficacy.

Why it matters: Essential ground-truth data for validating next-gen foundation models like Boltz or Chai.

⭐ Additional Signals

Cytotoxicity, apoptosis, molecular docking, and molecular dynamics study of novel compounds of Sulfamide derivatives coupled with DHP scaffolds as potent inhibitors of the MCF-7, A549, SKOV-3, and EA. yh926 carcinoma cells.

A novel series of dihydropyridine-sulfonyl derivatives (AG-CHO and analogues A1-A7) were synthesized and structurally characterized. Molecular docking demonstrated favorable binding of these compounds to autophagy-associated and cancer-related targets, while molecular dynamics simulations confirmed A5 as the most stable ligand protein interactions. Functional assays in SKOV-3, MCF-7, A549, and EA.hy.926 cells using acridine orange staining and flow cytometry revealed significant autophagy induction. Among all tested compounds AG-CHO emerged as the most potent inducer of autophagy. Notably, derivatives such as A6 and A7 showed selective potency in endothelial cells, whereas A1, A5, and A7 were effective in A549 cells, indicating cell-specific activity. Collectively, this integrated computational and experimental study identifies A5 as the lead compound and highlights dihydropyridine-sulfonyl scaffolds as promising autophagy modulators and potential anticancer candidates for further preclinical development.

Investigating the olfactory function of microplusin-like proteins in Rhipicephalus microplus through molecular docking and dynamics simulations.

Ticks are responsible for transmitting infectious pathogens of public health and veterinary importance worldwide. Chemosensory perception in ticks constitutes a fundamental pathway in host location and disease transmission. This study aims to analyze the function of the Rhipicephalus microplus microplusin-like protein (MLP) in the perception of volatile organic compounds. To obtain the results, AlphaFold2, Swiss Model, and AlphaFold3 were utilized for protein prediction. UCSF Chimera, AutoDock Vina in Linux, and Discovery Studio Visualizer were employed for docking analyses and interaction visualizations. The GROMACS software in a virtual Linux environment was used for molecular dynamics simulations. Out of 46 volatile molecules selected based on literature and used for docking, the four top compounds were evaluated for their interaction, including squalene with a binding energy of -5.183 kcal/mol, uric acid with -5.169 kcal/mol, beta-ionone with -5.037 kcal/mol, and 2,4-Di-tert-butylphenol with -5.035 kcal/mol. The stability of MLP with the top two compounds, squalene and uric acid, was evaluated through molecular dynamics simulations. The uric acid complex was more stable. It showed lower and more stable root-mean-square deviation (∼2 nm), as well as hydrogen bonding (2-4 bonds), smoother solvent-accessible surface area, and gyration radius profiles. In contrast, the squalene complex showed greater conformational variability, lacking hydrogen bonding. The Gibbs free energy landscape and principal component analysis revealed that squalene had stabilization at the start of the simulation. In contrast, uric acid showed stronger long-term conformational convergence and stabilization by the end of the simulation. This study demonstrated the potential role of microplusin-like protein in recognizing volatile organic compounds. It provides insights into the potential to develop new tick-control strategies.

From sweetener to risk factor: Network toxicology, molecular docking and molecular dynamics reveal the mechanism of aspartame in promoting coronary heart disease.

Aspartame, a widely used non-nutritive sweetener, has been epidemiologically linked to coronary heart disease (CHD), although the underlying mechanisms remain unclear. This study employed an integrative computational strategy combining network toxicology, molecular docking, and molecular dynamics to decode aspartame’s CHD-promoting mechanisms. Initially, the toxicity profile of aspartame was predicted using ProTox 3.0 and ADMETlab 3.0, which highlighted significant cardiotoxicity. Through multi-source target screening of aspartame (PharmMapper, SEA, etc.) and CHD (GeneCards, OMIM), 216 shared targets were identified. Protein-protein interaction network analysis revealed 10 hub targets (INS, PPARGC1A, TNF, AKT1, IL6, MMP9, IGF1, PTGS2, SIRT1, PPARG). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed significant enrichment in lipid metabolism, inflammatory responses, insulin resistance, and atherosclerosis-related pathways. Molecular docking and molecular dynamics simulations (MDS) demonstrated high-affinity binding of aspartame to three core targets (PTGS2, TNF, and PPARGC1A), with a binding energy ≤ -7.0 kcal/mol, and confirmed high binding stability. This study reveals that aspartame may promote the pathogenesis of CHD by disrupting cardiovascular homeostasis through multi-target interactions, including inflammatory response, metabolic dysregulation, and vascular remodeling. These findings provide molecular evidence for re-evaluating the safety profile of aspartame and establish a computational framework to guide experimental validation and preventive strategies.

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⚡ Quick Reads

Combining network pharmacology, machine learning, molecular docking, molecular simulation dynamics and experimental validation to explore the mechanism of Zhenwu decoction in treating major depression through TNF-α pathways.

Background Major depressive disorder (MDD) is a severe psychophysiological condition characterized by cognitive decline, low energy, weight loss, insomnia, and increased suicide risk, posing a significant burden on global health. Zhenwu decoction (ZWD), a traditional Chinese medicine, has shown therapeutic potential in alleviating MDD symptoms. However, its complex composition has limited the understanding of its underlying pharmacological mechanisms. This study aimed to explore the antidepressant mechanisms of ZWD in the treatment of MDD. Methods Active compounds and potential targets of ZWD were identified through database screening and network pharmacology analysis. These targets were intersected with MDD-related genes to construct a protein-protein interaction network. Core targets were further refined using random forest algorithms. Molecular docking and molecular dynamics simulations were employed to evaluate the binding affinity and stability between key compounds and core targets. Experimental validation was conducted in a lipopolysaccharide (LPS)-induced mouse model of depression using behavioral testing, measurement of inflammatory cytokines, and gene expression analysis. Results Network pharmacology and machine learning identified TNF-α signaling as key pathways in the antidepressant effects of ZWD. Enrichment analysis highlighted the involvement of Lipid and atherosclerosis, the IL-17 signaling pathway. Core targets, including PPARG, F10, AR, TNF, PIK3CG, ADH1C, and GABRA6, were predicted to mediate its effects. Molecular docking and dynamics simulations confirmed strong binding of ZWD components, especially kaempferol, to TNF-α, inhibiting its expression. In vivo, ZWD improved anxiety/depressive-like behaviors in LPS-treated mice, evidenced by better performance in the behavioral tests. ZWD also reduced neuroinflammation, with decreased Tnf-α levels, and reduced IBA-1 and GFAP staining, indicating reduced microglial and astrocyte activation. These results suggest that ZWD alleviates depression through modulation of TNF-α-mediated inflammation. Conclusions These findings suggest that ZWD exerts antidepressant effects primarily by modulating TNF-α-mediated inflammatory pathways, providing a comprehensive molecular and experimental framework supporting its clinical potential in MDD treatment.

UPLC-Q-TOF/MS-based Spectrum-effect Correlation Combined with Chemometrics and Molecular Docking for Quality Assessment and Screening of Bioactive Components with Hemostatic, Antinociceptive, and Anti-Inflammatory Activities in Liparis nervosa.

Ethnopharmacological relevance Liparis nervosa (LN) occurs in Southwest China and is traditionally used as a hemostatic and detoxifying agent; however, the pharmacodynamic basis for its medicinal properties is unclear; this impedes the quality standardization and clinical application of this herb. Aim of the study This study aimed to establish an integrated quality assessment system for LN by combining comprehensive chemical profiling with pharmacological evaluation to identify bioactive components and quality markers. Materials and methods Chemical profiling of ten regional LN specimens via UPLC-Q-TOF/MS revealed 53 shared components and characteristic fingerprints. Concurrently, systematic evaluation of hemostatic, antinociceptive, and anti-inflammatory activities was used to identify bioactive fractions. Using spectrum-effect modeling, which integrates techniques such as gray relational analysis, partial least squares regression, and bivariate correlation linked chromatographic features to bioactivities, these pharmacological effects were correlated with specific chemical components. Molecular docking was performed to validate target interactions. Orthogonal design coupled with spectrum-effect relationship analysis was used to pinpoint potential quality markers. Results As the first comprehensive study to systematically identify bioactive fractions and quality markers of LN, this work developed a tripartite evaluation framework integrating chemical profiling, pharmacological verification, and molecular docking-based target validation. Conclusions This methodology advances the standardization of LN, supports the interpretation of its pharmacological mechanisms of action, and facilitates the development of multi-target phytotherapeutic agents using LN bioactives.

Exploring the Mechanism of Platycladi Cacumen in Intervening Androgenetic Alopecia Based on Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

Abstract As a traditional hair-growth-promoting herb, Platycladi Cacumen(PC) has a long history of folk application in the field of hair loss improvement. Preliminary modern pharmacological studies have suggested that its active components may exert potential effects by regulating hair follicle-related signaling pathways; however, for androgenetic alopecia (AGA), the exact targets and specific regulatory mechanisms of PC remain unelucidated, which provides a direction for research on natural drug-based intervention in AGA. In this study, network pharmacology was employed to predict the active components and core targets of PC. Targets associated with AGA were collected, and the intersection targets between PC and AGA were identified. Subsequently, protein-protein interaction (PPI) analysis, Gene Ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the intersection targets to screen out the core targets. Thereafter, molecular docking and molecular dynamics simulation were conducted to validate the interactions between key active components and core targets. The component-target network diagram included 1044 interaction relationships between 32 components and 439 targets, among which quercetin, apigenin, myricetin, and hinokinin were identified as key components. The disease-target network diagram summarized 410 targets associated with AGA. Through PPI network analysis, key targets such as ESR1, BCL2, INS, AR, and STAT3 were screened out. The results of GO enrichment analysis and KEGG pathway analysis revealed that PC may exert its effects by regulating the EGFR receptor molecule and pathways including the HIF-1 signaling pathway. Molecular docking results showed that the binding energies of all complexes were less than -6.4 kcal/mol, indicating favorable binding effects. Molecular dynamics simulation results showed that the root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), two-dimensional free energy landscape (FEL-2D), and FEL-3D of the simulation system all remained in an equilibrium state with small fluctuation amplitudes. This result indicated that the molecular system had a stable overall conformation, restricted local residue movement, a compact spatial structure, and stable internal chemical bonds—collectively confirming that the quercetin-STAT3, apigenin-AR, myricetin-STAT3, and hinokinin-AR complexes exhibited extremely strong binding stability. Collectively, Overall, this study systematically investigated the mechanism of action and potential value of PC leaves in intervening in AGA, providing a solid theoretical basis for the intervention of AGA with PC.

Unraveling the mechanism of curcumin in coronary slow flow phenomenon through network pharmacology and molecular docking.

The coronary slow flow phenomenon (CSFP) is associated with an increased risk of adverse cardiovascular events, yet standardized treatment is lacking. Curcumin, a natural compound, has shown potential in alleviating angina and improving metabolic risk factors in CSFP, but its underlying molecular mechanisms remain unclear. This study employed an integrated computational strategy. Network pharmacology was used to identify potential targets of curcumin and CSFP from public databases, and common targets were identified. Functional enrichment analysis was performed on the common targets, and a protein-protein interaction network was constructed. Core targets were identified using MCODE and CytoHubba plugins in Cytoscape. Molecular docking evaluated the binding modes and affinities of curcumin with the core targets, while molecular dynamics simulations and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculations validated the stability and binding free energies of the complexes. A total of 120 predicted targets of curcumin and 435 CSFP-related targets were identified, yielding 19 common targets. Functional enrichment analysis revealed that curcumin may treat CSFP by modulating inflammatory response, vascular function, cell migration, proliferation, apoptosis, and oxidative stress. These targets were associated with key signaling pathways, including NF-κB, TNF, and HIF-1. Network analysis and topological algorithms identified five core targets: EGFR, ICAM1, NFKB1, PTGS2, and STAT3. Molecular docking results demonstrated that curcumin exhibited excellent binding affinity with all core targets. Molecular dynamics simulations confirmed that the curcumin-core target complexes remained structurally stable during the 100 ns simulation, and MM/GBSA calculations indicated significantly negative binding free energies, suggesting strong binding driving forces. Curcumin may exert therapeutic effects on CSFP through a multi-target mechanism, primarily by interacting with key proteins including EGFR, ICAM1, NFKB1, PTGS2, and STAT3, thereby regulating the NF-κB, TNF, and HIF-1 signaling pathways. This study provides a theoretical foundation for the application of curcumin in CSFP treatment, though further experimental validation is required.

Molecular docking and molecular dynamics study of PUFAs from <i>Navicula salinicola</i>: prospective antiviral strategies targeting the SARS-CoV-2 spike protein.

The emergence of novel viral infections, such as SARS-CoV-2, H5N2, and H7N9, among recently identified viruses, has highlighted the urgent need for new antiviral therapeutics. The SARS-CoV-2 virus binds to ACE2 on host cell surfaces, reducing ACE2 expression, increasing Angiotensin II, and activating the RAAS system. On the other sides, marine organisms like Navicula salinicola are a significant unexplored source of bioactive compounds with potential antiviral activity. However, investigation on marine-derived poly-unsaturated fatty acids (PUFAs) as antiviral agents for SARS-CoV-2 is a priority, as they have shown promising antiviral properties. This exploration highlights the ongoing efforts to explore natural compounds for their therapeutic potential against viral infections, including COVID-19. This study aims to investigate the antiviral potential of PUFAs from N. salinicola against SARS-CoV-2 using molecular docking and molecular dynamics simulations. A total of 14 PUFAs from N. salinicola were subjected to molecular docking with the SARS-CoV-2 spike protein, and the three best-ranked ligands, DHA (- 7.56 kcal/mol), AA (- 6.61 kcal/mol), and EPA (- 6.5 kcal/mol), were further analyzed by molecular dynamics. Our study identified all PUFAs with promising binding affinities toward the SARS-CoV-2 spike protein, suggesting their potential as effective inhibitors of viral entry or replication mechanisms. Molecular dynamics simulations revealed that the ligands docosahexaenoic acid (DHA), arachidonic acid (AA), and eicosapentaenoic acid (EPA) exhibited ∆ETotal values of - 46.45, - 48.31, and - 43.65 kcal/mol, respectively, indicating a relatively stable interaction with ACE2. AA, the most potent marine-derived PUFA from N. salinicola , has been identified as the lead compound for SARS-CoV-2 inhibitors, requiring further research for in vitro or in vivo experiments.

Computational insights into Ru(II)-coumarin complexes as potential anticancer agents: a DFT, QTAIM, NCI-RDG, molecular docking and molecular dynamics approach.

Ru(II) complexes have been explored as promising candidates for novel anticancer agents, due to their significant bioactivity, selective cytotoxicity, and ability to induce apoptosis via multiple signalling pathways, with coumarin derivatives serving as effective ligands to enhance their therapeutic efficacy. DFT calculations are highly useful in comprehensively analyzing the electronic structures, and physicochemical and thermodynamic properties of these metal complexes. For example, MEP maps are used to visualize the molecular charge distribution, while NBO analysis is employed to investigate the charge transfer interactions. The donor-acceptor behaviour of the metal-ligand complexes is also examined to gain deeper insights into their electronic properties and potential reactivity. QTAIM analysis confirms that weak H-bonding and vdW interactions significantly stabilize the studied adducts, particularly [RuCl 2 (yc4) 2 (DMSO) 2 ]·2H 2 O and AT/GC base pair complexes. Molecular docking is further employed to investigate the DNA-binding affinity and interaction mechanisms of these complexes, with a specific focus on AT/GC nucleobases. The molecular docking results provide insights into the stability of the adducts and reveal their preferred binding sites within DNA nucleobases. Finally, molecular dynamics simulation calculations were employed to complement DFT and docking analyses. Again, MM/PBSA free energy and H-bond analyses indicate stronger thermodynamic interactions of the [RuCl 2 (yc4) 2 (DMSO) 2 ]·2H 2 O complex with AT-rich regions. Hence, this in silico study on Ru(II)-coumarin complexes offers valuable insights for the rational design of metal-based anticancer therapeutics.

Targeting myeloid cell leukemia-1 protein to identify potential compounds for chronic myeloid leukemia treatment: Molecular docking and molecular dynamics simulation approaches.

Myeloid cell leukemia-1 (Mcl-1), an anti-apoptotic member of the Bcl-2 family, is frequently overexpressed and amplified in chronic myeloid leukemia (CML) as well as in several other malignancies, contributing to tumor progression and therapeutic resistance. The present study employed a multi-step virtual screening approach to identify potential inhibitors of the Mcl-1 protein and subsequently validated their inhibitory activity through computational approaches. The 3-D structure of Mcl-1 protein was retrieved from the protein data bank and subjected to structure-based virtual screening. A series of drug-likeness and ADMET filters, including Lipinski filter, Swiss ADME, ADME-Tox, pKCSM and Protox-3 web, were applied to prioritize the compounds with favorable pharmacokinetic and toxicity profile. Further evaluated by molecular docking, with particular emphasis on -CDOCKER interaction energy, identified tolbutamide (-101.09 kcal/mol), leucodelphinidin (-89.304 kcal/mol), and gossypetin -70.49 (kcal/mol) as, most promising candidates. To assess the conformational stability and dynamic behavior of the protein-ligand complexes, molecular dynamics simulation was performed for 100ns and extended to 500 ns for the best screened compound. Trajectory analysis was conducted using multiple descriptors, including root mean square deviation, root mean square fluctuation, the radius of gyration, solvent-accessible surface area (SASA), hydrogen bonds, and free energy landscape. In vitro toxicity studies using the MTT assay on the K562 chronic myeloid leukemia cell line demonstrated a significant reduction in cell viability, indicating potent antiproliferative activity. These computational studies highlight novel compounds as potent Mcl-1 inhibitors, suggesting their potential as promising therapeutic candidates for the treatment of CML. These findings lay the foundation for further optimization and preclinical evaluation of Mcl-1 targeted compounds in cancer therapy.

Mechanistic exploration of bisphenol A in primary Sjögren’s syndrome using network toxicology, molecular docking, molecular dynamics simulations and experimental validation.

Primary Sjögren’s syndrome (pSS) is a chronic autoimmune disorder marked by exocrine gland impairment and systemic manifestations. Environmental endocrine disruptors, including bisphenol A (BPA), have been associated with immunological dysregulation; however, their involvement in pSS is not well-defined. This study integrated network toxicology, molecular docking, molecular dynamics simulation, and in vitro validation to examine the potential effects of BPA on pSS. Bioinformatics investigation revealed 25 overlapping targets between BPA-associated genes and differentially expressed genes related to pSS, with CASP3, PTGS1, and PTGS2 identified as main possibilities. Molecular docking and molecular dynamics simulations validated robust and stable interactions of BPA with these proteins. Cellular studies with human submandibular gland epithelial cells demonstrated dose-dependent cytotoxicity of BPA, accompanied by substantial overexpression of CASP3, PTGS1, and PTGS2 at 1 µM exposure. The data indicate that BPA enhances apoptosis and inflammatory signaling in salivary gland cells, potentially contributing to pSS progression. This study provides mechanistic insight into how BPA may contribute to autoimmune disease development, highlighting its potential role in pSS.

💡 Pipeline Tip

Always validate pLDDT scores before using AlphaFold models for docking.

🛠️ Resources

• Dataset: Protein Data Bank (PDB) - The single global archive for macromolecular structure data.
• Dataset: AlphaFold Structure Database - 200M+ predicted structures from DeepMind/EMBL-EBI.
• Tool: ProteinSolver - Graph-based neural network for protein sequence design. View all tools →
• Tool: RFdiffusion - State-of-the-art generative model for de novo protein design. View all tools →
• Event: Protein Design Hub (LinkedIn Group) (Ongoing)
• Event: Structural Biology Events (Open)
• Job: Mercor hiring Bioinformatics Data-Science Specialist in India - LinkedIn India at Bioinformatics Careers
• Job: Bioinformatics Professional Training/ Learning Course/ Internship /Dissertation - LinkedIn at Bioinformatics Careers

The protein structure is the language of life; design is its poetry. — Recep Adiyaman