Issue #7: 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.

Signal of the Day

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.

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

Also Worth Reading

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.

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.

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From the Industry

Quiet day in the industry — nothing material to report.

Quick Reads

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.

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

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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. Read more →

A screening strategy for bioactive components from Amaranth: An integrated approach of network pharmacology, molecular docking and molecular dynamics simulation.

Amaranth is a traditional medicinal and forage plant with promising anti-inflammatory properties. Read more →

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. Read more →

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. Read more →

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. Read more →

Genome-wide analysis, expression profiling and molecular docking of tomato (Solanum lycopersicum) calmodulin (SlCaM) proteins in cadmium stress adaptation.

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Pipeline Tip

Normalise thermal B-factors when comparing different crystal structures.

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