Journal: BMC Pharmacology & Toxicology

Article Title: Computational-experimental repurposing reveals synergistic sorafenib/hydroxychloroquine response in KRAS-mutant breast cancer

doi: 10.1186/s40360-026-01122-2

Figure Lengend Snippet: Molecular dynamics simulation analysis for Raf–Sorafenib complex. ( a ) the RMSD of ligand (Sorafenib) and protein backbone (Raf) across a 100 ns simulation period. ( b ) A plot of Cα atoms’ RMSF against residue index. ( c ) The complex’s gyration radius over time. ( d ) The amount of the intermolecular hydrogen bonds formed between Raf and Sorafenib during the course of the simulation

Article Snippet: Fig. 2 Molecular dynamics simulation analysis for Raf–Sorafenib complex. ( a ) the RMSD of ligand (Sorafenib) and protein backbone (Raf) across a 100 ns simulation period. ( b ) A plot of Cα atoms’ RMSF against residue index. ( c ) The complex’s gyration radius over time. ( d ) The amount of the intermolecular hydrogen bonds formed between Raf and Sorafenib during the course of the simulation We analyzed intermolecular hydrogen bonding patterns, root mean square fluctuation (RMSF), root mean square deviation (RMSD), and radius of gyration to evaluate the stability and conformational behavior of the Raf kinase in complex with sorafenib during 100 ns molecular dynamics simulations.

Techniques: Residue

Journal: BMC Pharmacology & Toxicology

Article Title: Computational-experimental repurposing reveals synergistic sorafenib/hydroxychloroquine response in KRAS-mutant breast cancer

doi: 10.1186/s40360-026-01122-2

Figure Lengend Snippet: Molecular dynamics descriptors of the sorafenib–RAF complex: ( a ) center-of-mass distance, ( b ) total solvent-accessible surface area (SASA), and ( c ) contact frequency of significant RAF residues cooperating with sorafenib

Article Snippet: Fig. 2 Molecular dynamics simulation analysis for Raf–Sorafenib complex. ( a ) the RMSD of ligand (Sorafenib) and protein backbone (Raf) across a 100 ns simulation period. ( b ) A plot of Cα atoms’ RMSF against residue index. ( c ) The complex’s gyration radius over time. ( d ) The amount of the intermolecular hydrogen bonds formed between Raf and Sorafenib during the course of the simulation We analyzed intermolecular hydrogen bonding patterns, root mean square fluctuation (RMSF), root mean square deviation (RMSD), and radius of gyration to evaluate the stability and conformational behavior of the Raf kinase in complex with sorafenib during 100 ns molecular dynamics simulations.

Techniques: Solvent

Journal: BMC Pharmacology & Toxicology

Article Title: Computational-experimental repurposing reveals synergistic sorafenib/hydroxychloroquine response in KRAS-mutant breast cancer

doi: 10.1186/s40360-026-01122-2

Figure Lengend Snippet: Dose–response MTT cytotoxicity assay of Sorafenib (SN) and Hydroxychloroquine (HQ) following 48 h treatment in ( a ) normal gingival fibroblasts, ( b ) MDA-MB-231 breast cancer cells, and ( c ) A549 lung cancer cells. Data were normalized to untreated controls ( n = 5), and the fraction affected (Fa) was calculated as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Fa = {{\% \>{\rm{Cell}}\>{\rm{Viability}}} \over {100}}$$\end{document} . IC₅₀ values (µM) for SN were 23.1 (fibroblasts), 9.4 (MDA-MB-231), and 12 (A549), while HQ IC₅₀ values were 86.2, 23.6, and 62.4, respectively

Article Snippet: Fig. 2 Molecular dynamics simulation analysis for Raf–Sorafenib complex. ( a ) the RMSD of ligand (Sorafenib) and protein backbone (Raf) across a 100 ns simulation period. ( b ) A plot of Cα atoms’ RMSF against residue index. ( c ) The complex’s gyration radius over time. ( d ) The amount of the intermolecular hydrogen bonds formed between Raf and Sorafenib during the course of the simulation We analyzed intermolecular hydrogen bonding patterns, root mean square fluctuation (RMSF), root mean square deviation (RMSD), and radius of gyration to evaluate the stability and conformational behavior of the Raf kinase in complex with sorafenib during 100 ns molecular dynamics simulations.

Techniques: Cytotoxicity Assay

Journal: BMC Pharmacology & Toxicology

Article Title: Computational-experimental repurposing reveals synergistic sorafenib/hydroxychloroquine response in KRAS-mutant breast cancer

doi: 10.1186/s40360-026-01122-2

Figure Lengend Snippet: Dose–effect curves of Sorafenib (SN) and Hydroxychloroquine (HQ) combinations in ( a ) MDA-MB-231 and ( b ) A549 cells after 48 h treatment. Cytotoxicity was assessed by MTT assay, and the fraction affected (Fa) was calculated as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Fa = {{\% \>{\rm{Cell}}\>{\rm{Viability}}} \over {100}}$$\end{document} . Combination index (CI) analysis indicated strong synergy in MDA-MB-231 cells for SN:2HQ (CI = 0.32) and SN: HQ (CI = 0.66), whereas 2SN: HQ was antagonistic (CI = 3.7). In A549 cells, SN:2HQ was nearly additive (CI = 1.03), while SN: HQ (CI = 1.5) and 2SN: HQ (CI = 1.7) showed antagonism

Article Snippet: Fig. 2 Molecular dynamics simulation analysis for Raf–Sorafenib complex. ( a ) the RMSD of ligand (Sorafenib) and protein backbone (Raf) across a 100 ns simulation period. ( b ) A plot of Cα atoms’ RMSF against residue index. ( c ) The complex’s gyration radius over time. ( d ) The amount of the intermolecular hydrogen bonds formed between Raf and Sorafenib during the course of the simulation We analyzed intermolecular hydrogen bonding patterns, root mean square fluctuation (RMSF), root mean square deviation (RMSD), and radius of gyration to evaluate the stability and conformational behavior of the Raf kinase in complex with sorafenib during 100 ns molecular dynamics simulations.

Techniques: MTT Assay

Journal: BMC Pharmacology & Toxicology

Article Title: Computational-experimental repurposing reveals synergistic sorafenib/hydroxychloroquine response in KRAS-mutant breast cancer

doi: 10.1186/s40360-026-01122-2

Figure Lengend Snippet: Combination index (CI) and dose reduction index (DRI) analyses of Sorafenib (SN) and Hydroxychloroquine (HQ) after 48 h treatment. ( a ) A549 and ( b ) MDA-MB-231 CI–Fa plots for fixed ratios (2SN:1HQ, 1SN:1HQ, 1SN:2HQ), where \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Fa = {{\% \>{\rm{Cell}}\>{\rm{Viability}}} \over {100}}$$\end{document} . In MDA-MB-231 cells, 1SN:2HQ (CI = 0.32) and 1SN:1HQ (CI = 0.66) showed synergism, whereas 2SN:1HQ was antagonistic (CI = 3.78). All ratios were antagonistic in A549 cells (CI > 1). ( c ) DRI–Fa plot for the selective 2HQ:1SN ratio in MDA-MB-231 cells; at Fa = 0.5, DRI values were 4.68 (HQ) and 9.36 (SN), indicating marked dose-reduction potential

Article Snippet: Fig. 2 Molecular dynamics simulation analysis for Raf–Sorafenib complex. ( a ) the RMSD of ligand (Sorafenib) and protein backbone (Raf) across a 100 ns simulation period. ( b ) A plot of Cα atoms’ RMSF against residue index. ( c ) The complex’s gyration radius over time. ( d ) The amount of the intermolecular hydrogen bonds formed between Raf and Sorafenib during the course of the simulation We analyzed intermolecular hydrogen bonding patterns, root mean square fluctuation (RMSF), root mean square deviation (RMSD), and radius of gyration to evaluate the stability and conformational behavior of the Raf kinase in complex with sorafenib during 100 ns molecular dynamics simulations.

Techniques:

Journal: BMC Pharmacology & Toxicology

Article Title: Computational-experimental repurposing reveals synergistic sorafenib/hydroxychloroquine response in KRAS-mutant breast cancer

doi: 10.1186/s40360-026-01122-2

Figure Lengend Snippet: Apoptosis investigation via flow cytometry. Cells were stained with Annexin V-FITC and propidium iodide (PI) to distinguish viable (lower left), early apoptotic (lower right), late apoptotic (upper right), and necrotic (upper left) populations. Representative dot plots are shown for: ( a ) untreated control; ( b ) hydroxychloroquine (23.6 µM); ( c ) sorafenib (9.4 µM); and ( d ) their combination (5 µM HCQ + 1 µM Sorafenib). ( e ) Quantitative summary of cell populations across treatment groups. Hydroxychloroquine treatment significantly reduced viable cells (from 88.09% to 8.52%, **** p < 0.000001) and significantly increased early apoptosis (2.43% to 5.54%, **** p < 0.000001), late apoptosis (1.75% to 34.87%, **** p < 0.000001), and necrosis (2.23% to 49.40%, **** p < 0.000001) compared to control

Article Snippet: Fig. 2 Molecular dynamics simulation analysis for Raf–Sorafenib complex. ( a ) the RMSD of ligand (Sorafenib) and protein backbone (Raf) across a 100 ns simulation period. ( b ) A plot of Cα atoms’ RMSF against residue index. ( c ) The complex’s gyration radius over time. ( d ) The amount of the intermolecular hydrogen bonds formed between Raf and Sorafenib during the course of the simulation We analyzed intermolecular hydrogen bonding patterns, root mean square fluctuation (RMSF), root mean square deviation (RMSD), and radius of gyration to evaluate the stability and conformational behavior of the Raf kinase in complex with sorafenib during 100 ns molecular dynamics simulations.

Techniques: Flow Cytometry, Staining, Control

Journal: BMC Pharmacology & Toxicology

Article Title: Computational-experimental repurposing reveals synergistic sorafenib/hydroxychloroquine response in KRAS-mutant breast cancer

doi: 10.1186/s40360-026-01122-2

Figure Lengend Snippet: Flow Cytometry Investigation of cell cycle distribution in Normal Gingival Fibroblast cells. Cells were stained with PI to assess DNA content. Representative histograms show cell cycle distribution (G0/G1, M1; S, M2; G2/M, M3) for: ( a ) untreated control; ( b ) hydroxychloroquine (23.6 µM); ( c ) sorafenib (9.4 µM); and ( d ) combination treatment (5 µM HCQ + 1 µM Sorafenib). ( e ) Quantitative bar graph of phase distribution across groups. Two-way ANOVA demonstrated significant treatment effects (**** P < 0.0001), phase effects ( P < 0.0001), and interaction ( P < 0.0001), indicating differential cell cycle alterations by treatments. Data are mean ± SD ( n = 3)

Article Snippet: Fig. 2 Molecular dynamics simulation analysis for Raf–Sorafenib complex. ( a ) the RMSD of ligand (Sorafenib) and protein backbone (Raf) across a 100 ns simulation period. ( b ) A plot of Cα atoms’ RMSF against residue index. ( c ) The complex’s gyration radius over time. ( d ) The amount of the intermolecular hydrogen bonds formed between Raf and Sorafenib during the course of the simulation We analyzed intermolecular hydrogen bonding patterns, root mean square fluctuation (RMSF), root mean square deviation (RMSD), and radius of gyration to evaluate the stability and conformational behavior of the Raf kinase in complex with sorafenib during 100 ns molecular dynamics simulations.

Techniques: Flow Cytometry, Staining, Control