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Daily Signal May 18, 2026 · 11 min read

Issue #110: 3D-QSAR, Molecular Docking, Molecular Dynamics Simulation, and Pharmacokinetic Prediction of 1H-Pyrazolo[3,4-d]pyrimidine Derivatives as PI3Kδ Inhibitors.

Protein Design Digest #110: 3D-QSAR, Molecular Docking, Molecular Dynamics Simulation, and Pharmacok…

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3D-QSAR, Molecular Docking, Molecular Dynamics Simulation, and Pharmacokinetic Prediction of 1H-Pyrazolo[3,4-d]pyrimidine Derivatives as PI3Kδ Inhibitors.

Introduction The inhibition of cellular inflammatory factor secretion by phosphatidylinositol- 3-kinase δ (PI3Kδ) makes it a novel target for acute lung injury therapy. This study aimed to elucidate the structure-activity relationship of 1H pyrazolo [3, 4-d] pyrimidine derivatives as PI3Kδ inhibitors for novel drug design. Methods In this study, a three-dimensional quantitative conformational relationship (3DQSAR) model was constructed using COMFA and CoMSIA techniques with Sybyl X-2.0 software. In-silico ADME and toxicity predictions were also evaluated using SwissADME and pkCSM tools. Molecular docking and molecular dynamics (MD) simulations (100 ns) were conducted to confirm the interaction of the compounds with the target protein using the GROMACS 2021 software package. Results Good predictability was assessed using the CoMFA model (Qcv² = 0.547; Rncv² = 0.991; Rpred² = 0.996) and the best CoMSIA model (Qcv² = 0.58; Rncv² = 0.992; Rpred² = 0.994). The A, B, and C rings were the basic skeleton for the potency of the inhibitors. The hydrogen bond acceptor field, electrostatic field, and hydrophobic field significantly influenced activity. The newly designed T03 showed stable RMSD/RMSF during 100 ns MD simulations and low predicted toxicity (LD50: 1579.4 mg/kg). Molecular docking revealed that T03 formed six hydrogen bonds with PI3Kδ, exhibiting a high binding affinity of -11.6 kcal/mol. Discussion The structural features of 1H pyrazolo [3, 4-d] pyrimidine derivatives through 3D-QSAR modelling established a relationship between functional groups and their biological activity. Based on the constructed 3D-QSAR model, five novel 1H pyrazolo [3, 4- d] pyrimidine derivatives targeting PI3Kδ were designed with improved predicted activities. Furthermore, molecular docking and MD simulations demonstrated stability and revealed ligand-receptor interactions. These novel potent inhibitors were assessed for their ADMET properties. Conclusion The 3D-QSAR model exhibits great reliability and predictive power through ADMET, molecular docking, and molecular dynamic approaches. These results would provide a valuable insight into lead optimization for new drug discovery.

Why this matters: Critical for improving fold accuracy and reducing structural uncertainty in de novo design.

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Exploring the mechanism of saffron in treating viral myocarditis using network pharmacology and molecular docking.

Viral myocarditis (VM) is a cardiovascular disorder that can lead to heart failure and cardiogenic shock. Saffron, a traditional Chinese medicinal herb, has shown therapeutic potential against VM in numerous studies. However, the mechanisms through which saffron exerts its effects on VM remain poorly understood. Thus, this study aimed to elucidate the active compounds, molecular targets, and signaling pathways involved in saffron’s therapeutic action against VM by employing network pharmacology and molecular docking approaches. The active compounds and corresponding targets of saffron were retrieved from the Traditional Chinese Medicine Systems Pharmacology database. VM-associated targets were sourced from the GeneCards database. Overlapping targets between saffron and VM were then identified. Protein-protein interaction networks were established and analyzed utilizing the STRING platform and Cytoscape software to determine core targets. Furthermore, gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were carried out utilizing Bioconductor in R to explore the potential biological activities and signaling pathways through which saffron may act against VM. Finally, molecular docking and model visualization were carried out using AutoDock Tools and PyMOL open-source software. From the database, we identified 4 active compounds in saffron with potential effects against VM: crocetin, isorhamnetin, kaempferol, and quercetin. A total of 60 corresponding targets were observed, with TNF, IL-6, IL-1β, CXCL8, and JUN emerging as core targets. Kyoto encyclopedia of genes and genomes enrichment analysis revealed 155 regulatory signaling pathways, among which the TNF, AGE-RAGE, and IL-17 signaling pathways, lipid metabolism, and atherosclerosis were the most prominent. Molecular docking results indicated that quercetin showed the strongest binding affinity toward IL-1β and CXCL8. The therapeutic effect of saffron against VM is not driven by a single factor, but rather involves multiple active compounds, targets, and signaling pathways.

Unraveling the anti-neuroinflammatory mechanisms of Cervus cucumis polypeptide injection in Alzheimer’s disease: insights from network pharmacology, molecular docking, molecular dynamics simulation, and experimental validation.

Objective Alzheimer’s disease (AD) is a progressive neurodegenerative disorder with increasing global prevalence, in which neuroinflammation serves as a critical pathological driver exacerbating cognitive decline. While current therapies offer limited symptomatic relief, multi-target strategies are urgently needed. Cervus cucumis polypeptide injection (CCPI), a traditional Chinese medicine (TCM) formulation, has demonstrated anti-inflammatory properties; however, its mechanisms of action against AD remain unclear. This study aimed to elucidate the anti-AD potential mechanisms of CCPI using an integrated approach combining network pharmacology, molecular docking, molecular dynamics (MD) simulation, and experimental validation. Methods Active components and corresponding targets of CCPI were retrieved from the TCMSP database, while AD-related targets were collected from Genecards, OMIM, and DrugBank. Potential therapeutic targets were identified by intersecting drug and disease targets, followed by protein-protein interaction (PPI) network construction, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Molecular docking and MD simulations were performed to evaluate interactions between potential active components and key targets. In vitro experiments were conducted on Aβ 25-35 -induced BV2 microglial cells to assess cell viability (CCK-8 assay), inflammatory cytokine levels (ELISA), and protein expression (Western blot) related to the neuroinflammation pathway and microglial polarization. Results A total of 28 active components and 50 common targets of CCPI for AD treatment were identified. Linoleic acid (LA) was determined to be a potential active component, with IL-6 as the key target based on PPI network topology. Molecular docking and MD simulation confirmed a stable binding affinity between LA and IL-6. KEGG analysis revealed significant enrichment in the HIF-1 signaling pathway, particularly the IL-6/STAT3/VEGF signaling pathway. In vitro , CCPI treatment significantly enhanced cell viability and attenuated the pro-inflammatory response, as evidenced by reduced levels of IL-6, IL-1β, and TNF-α, decreased the expression of the pro-inflammatory marker iNOS. Concurrently, it elevated the expression of the anti-inflammatory/repair-associated marker CD206. Western blot analysis further verified that CCPI suppressed IL-6/STAT3 activation while upregulating VEGF expression. Additionally, LA alone significantly reduced IL-6 levels and STAT3 phosphorylation, decreased the expression of iNOS, and increased the expression of CD206, with therapeutic efficacy comparable to CCPI. Conclusion CCPI exerts neuroprotective effects in AD models by regulating the IL-6/STAT3/VEGF pathway, downregulating the expression of the inflammation-related iNOS protein, upregulating the expression of the CD206 protein associated with anti-inflammatory and reparative functions, remodeling the functional state of microglia, inhibiting their pro-inflammatory responses, and enhancing their reparative functions. Its potential active component, LA, likely mediates this effect by stably binding to and inhibiting IL-6, thus suppressing the downstream STAT3 phosphorylation that drives inflammatory activation.

Molecular docking, DFT analysis, pharmacokinetic profiling and MD simulation of Ilex aquifolium L. flavonoids as potential α-glucosidase predicted inhibitors for diabetes.

The growing diabetes trend worldwide demands the identification of new α-glucosidase inhibitors for delaying postprandial hyperglycemia. However, the use of existing drugs is often limited by adverse effects, which has increased interest in natural products as safer alternative sources of α-glucosidase inhibitors. I. aquifolium was selected based on reports of flavonoid-rich phytochemistry, leading to the hypothesis that its major flavonoids could act as potential α-glucosidase inhibitors for the management of diabetes. Herein, the virtual α-glucosidase inhibitory potential of eight flavonoid-based phytochemicals of I. aquifolium extracts was investigated through an integrated in silico workflow, which includes molecular docking, DFT analysis, and ADMET profiling. Docking analysis identified IA- 2 (Rutin) and IA- 5 (Kaempferol-3-O-rhamnoglucoside) as the most potent ligands with binding affinities of - 9.59 kcal/mol and - 9.18 kcal/mol, respectively, closely approaching the standard acarbose (-10.96 kcal/mol). The re-docking RMSD of 2.1375 Å fell within the acceptable validation benchmark, supporting the reliability of the docking protocol. The second and third positions were occupied by IA- 1 (Quercetin) and IA- 3 (Quercetin-3-O-hexoside) as potential inhibitors, as they formed hydrogen bonds with hydrophobic contacts. DFT study suggested that all the flavonoids exhibited moderate to high dipole moments (4.88-7.36 Debye) along with the high HOMO-LUMO gaps. Additionally, IA- 7 (Apigenin) showed the highest electrophilicity (3.313) among all the phytochemicals. The pharmacokinetic evaluation of ligands by SwissADME and PkCSM suggested IA- 1 as the most potential hit, and it occupied the main drug-likeness parameters with a bioavailability score of 0.55, whereas low bioavailability scores (0.17) for IA- 2 and IA- 5 indicated their poor permeability through the membrane. The potential toxicity of the ligands through SwissADME predicted that all the ligands have renal and respiratory issues, but IA- 1 showed the highest potential of acute dermal toxicity. MD simulations supported the docking results by showing protein backbone RMSD stabilization at 2.0-2.4 Å and revealing that IA-2 and IA-5 form the most dynamically stable complexes (lowest ligand RMSD, compact Rg, persistent H bonds), while IA-3 and IA-1 display greater ligand flexibility, thereby prioritizing these compounds for experimental validation in a hypothesis-generating context. However, these computational findings do not replace experimental validation and should be interpreted as hypothesis-generating predictions. Overall, the study provides a hypothesis-generating framework, prioritizing IA-2 and IA-5 as potential α-glucosidase inhibitory candidates, with IA-1 emerging as a top-ranked ligand through pharmacokinetic parameters, required further experimental validation.

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