Jul 2026· International Journal of Molecular Sciences· Vol 27· 0 citations· 193 references
Medicine
TL;DR
Multiscale quantum-classical in silico predictions of Phyllanthus niruri phytochemicals as non-covalent EGFR T790M binders warranting experimental validation as T790M-directed agents in HCC are presented.
Abstract
Epidermal growth factor receptor (EGFR) mutations drive hepatocellular carcinoma (HCC) progression, and the T790M gatekeeper substitution is the predominant mechanism of acquired resistance to EGFR-targeted therapies. Herein, we present multiscale quantum-classical in silico predictions of Phyllanthus niruri phytochemicals as non-covalent EGFR T790M binders, employing molecular docking, 100 ns molecular dynamics, MM-PBSA/MM-GBSA, per-residue decomposition, PCA/LDA, DFT at B3LYP-D3(BJ)/def2-TZVP, and comparative wild-type EGFR simulations. Five phytochemicals exhibited computationally predicted binding affinities against EGFR T790M exceeding the non-covalent binding component of osimertinib (−25.74 kcal/mol): corilagin (−53.71 ± 5.05 kcal/mol), eriodictyol-7-rhamnopyranoside (−44.35 ± 4.51 kcal/mol), isoquercetin (−44.23 ± 2.92 kcal/mol), rutin (−42.15 ± 4.50 kcal/mol), and kaempferol-4-rhamnoside (−41.68 ± 3.69 kcal/mol). Wild-type EGFR simulations (PDB 1M17) yielded a selectivity index (IS) of 2.76 for corilagin (ΔΔGbind = +34.22 kcal/mol), indicating T790M-preferential binding. Osimertinib reproduced its clinically established T790M selectivity under identical conditions (IS = 1.43; ΔΔGbind = +7.74 kcal/mol), providing internal methodological validation. DFT at B3LYP-D3(BJ)/def2-TZVP established the quantum-mechanical basis for corilagin’s electrostatic affinity: its molecular electrostatic potential (MEP) surface minimum (Vs,min = −46.92 kcal/mol) directly predicts the largest MM-PBSA electrostatic term (ΔEele = −52.48 kcal/mol), establishing quantum-classical coherence. Supervised PCA/LDA of 7416 MM-PBSA trajectory frames identified solvation energy (ΔGSOLV) as the primary pharmacological class discriminant, with the first discriminant function (LD1) capturing 93.1% of inter-class binding variance. Collectively, corilagin (hydrolyzable tannin), eriodictyol-7-rhamnopyranoside (flavonoid glycoside), and phyltetralin (lignan) constitute diverse computational leads from P. niruri warranting experimental validation as T790M-directed agents in HCC.
The results proposed that isobonducellin from Artemisia annua L. plant shows potential as a colorectal cancer therapeutic by modulating multiple signaling pathways and targeting AKT1 protein as a strong AKT1-targeting drug candidate.
Md Maruf Khan, Md. Arju Hossain, Md Shahadat Hossain et al.· Computers in Biology and Med...· 0 citations
Hydxymycotrienin A is identified as a promising, bioavailable ‘privileged scaffold’ that offers a non-covalent therapeutic strategy for NSCLC, characterizing Hydroxymycotrienin A as a promising, bioavailable ‘privileged scaffold’ that offers a non-covalent therapeutic strategy.
Adeline Celina Rufus, Sidharth Kumar N, M. Ramasamy et al.· Frontiers in Bioinformatics· 0 citations
Breast cancer remains one of the leading causes of cancer-related mortality among women worldwide, necessitating the development of safer and more targeted therapeutic strategies. This study computationally extends our previous experimental investigation of a peptide derived from
Lacticaseibacillus casei
by evaluating its interactions with two clinically relevant breast cancer targets, estrogen receptor alpha (ERα; PDB ID: 3ERT) and human epidermal growth factor receptor 2 (HER2; PDB ID: 1N8Z).
The peptide structure was predicted using PEP-FOLD and its stereochemical quality was assessed using a Ramachandran plot. Molecular docking was performed against ERα and HER2, followed by molecular dynamics simulations to evaluate structural stability. Binding free energy, binding affinity, dissociation constant, principal component analysis (PCA), free energy landscape (FEL), molecular mechanics (MM)/Poisson–Boltzmann surface area (PBSA) calculations, and
in silico
ADMET and toxicity predictions were performed to comprehensively characterise peptide–protein interactions.
The predicted peptide model exhibited 84.8% of residues located in the most favoured regions, while 15.2% were located in additionally allowed regions of the Ramachandran plot, indicating satisfactory stereochemical quality. Molecular docking demonstrated favourable interactions with both ERα and HER2, with HER2 showing a marginally more favourable docking score. Molecular dynamics simulations indicated stable peptide–protein complexes throughout the simulation period, as supported by root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), and hydrogen-bond analyses. MM/PBSA calculations predicted stronger binding for the HER2 (1N8Z) complex (ΔG = −28.83 kJ/mol) than for the ERα (3ERT) complex (ΔG = −11.65 kJ/mol), highlighting the complementary nature of docking and dynamic free-energy estimation, which produced different receptor rankings. PCA and FEL analyses further demonstrated stable conformational sampling for both complexes. ADMET predictions suggested favourable peptide-like physicochemical properties while identifying pharmacokinetic and toxicity parameters that require further experimental validation.
This computational study suggests that the
L. casei
-derived peptide exhibits favourable predicted interactions with ERα and HER2 and forms structurally stable peptide–protein complexes under simulated physiological conditions. These findings provide a computational framework for prioritising this probiotic-derived peptide for subsequent experimental validation and further investigation as a potential peptide-based therapeutic candidate for breast cancer.
G. R. Shree Kumari, M. Vaithilingam· Frontiers in Bioinformatics· 0 citations
Lung cancer remains the leading cause of cancer-related mortality worldwide, with Epidermal Growth Factor Receptor (EGFR) mutations, particularly L858R, driving the progression and drug resistance of non-small cell lung cancer (NSCLC). Ficus minahassae (Langusei), an endemic species of North Sulawesi, contains diverse bioactive metabolites whose anticancer potential has not been explored. This study evaluated the potential of Langusei fruit metabolites as EGFR L858R inhibitors through an integrative in silico approach. Metabolites were identified via gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–high-resolution mass spectrometry (LC–HRMS). Target prediction was conducted using SwissTargetPrediction (probability > 0.5) and the Similarity Ensemble Approach (SEA) (MaxTC > 0.5), while NSCLC-related targets were retrieved from OMIM, GeneCards, Genpia2, DisGeNET, and cBioPortal. Network pharmacology and CytoHubba topology analyses were used to identify hub proteins, followed by ADMET profiling and molecular docking to assess binding affinity toward EGFR wild type and L858R mutant. A total of 170 metabolites were identified, dominated by fatty acyls, prenol lipids, and steroid derivatives. Integration of target prediction and disease databases revealed 355 overlapping proteins, among which seven hub proteins, including EGFR, STAT3, EP300, HSP90AA1, JUN, HIF1A, and ESR1, were identified as key regulators of oncogenic pathways. Molecular docking demonstrated that (Z)-1-(1,3-benzodioxol-5-yl)-3-methoxy-3-(2,4,6-trimethoxyphenyl)prop-2-en-1-one exhibited strong binding affinities to both EGFR wild type and L858R mutant and possessed a favorable ADMET profile comparable to Gefitinib and Osimertinib. These findings highlight Langusei fruit as a promising natural source of safe, multi-target EGFR inhibitors with potential therapeutic relevance for NSCLC. Further in vitro and in vivo validation is warranted to confirm efficacy and selectivity.
R. V. Worotikan, F. Mantiri, T. Tallei· Jurnal bios logos· 0 citations
This study identifies structurally tractable TQ analogs with improved predicted potency and establishes a robust computational framework for neuroprotective discovery as redox‐modulating agents in ALS.
Jabir C Nalicho, P. Mabeyo, Andrew S. Paluch et al.· ChemistryOpen· 0 citations
Findings highlight Withaferin A as a promising natural inhibitor of UBE2J1 and provide a foundation for future experimental validation aimed at developing targeted therapies against ovarian cancer.
Zujaja Rehman, Ejaz Rasul, Wisha Asif et al.· In Silico Pharmacology· 0 citations