Assessment of inhibitory potentiality of natural compounds against worrisome rice blast fungus DOI
Anik Banik,

Tanjin Barketullah Robin,

Riaz-ul Islam Al-Amin

et al.

Journal of Biomolecular Structure and Dynamics, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 17

Published: Dec. 16, 2024

Rice blast, a severe fungal disease, is substantial threat to global food security, particularly in rice-oriented areas. The Magnaporthe oryzae fungus increasingly resistant and fast developing nature. However, chemical fungicides are not only detrimental the environment but eventually also lose their efficiency. To Tackle this issue, we used an silico based strategy identify plant metabolites as bio-fungicides combat rice blast. Therefore, screened total of 56 antifungal natural compounds for ability inhibit development through targeted inhibition essential proteins blast pathogen. Molecular docking analysis identified curcumin, myricetin, sterigmatocystin, versicolorin B promising candidates with superior binding affinities compared conventional like strobilurin, azoxystrobin, tricyclazole. Notably, myricetin showed score SD protein −233.20, whereas demonstrated highest affinity −234.23. Among control fungicides, azoxystrobin displayed lowest −177.53. docked complexes were found be stable on molecular dynamics simulations results; free energies SD-Versicolorin (−156.018 ± 24.881 kJ/mol) SD-Myricetin (−137.526 19.977 favorable. Taking everything considered, these naturally occurring substances strong fungicidal effects against causative agent while remaining non-toxic, providing encouraging substitutes traditional fungicides. In conclusion, non-toxic exhibited action suggesting alternatives

Language: Английский

QSAR, ADMET, molecular docking, and dynamics studies of 1,2,4-triazine-3(2H)-one derivatives as tubulin inhibitors for breast cancer therapy DOI Creative Commons
Mohamed Moussaoui, Soukayna Baammi, Hatim Soufi

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: July 16, 2024

Abstract Breast cancer remains a leading cause of cancer-related deaths among women globally, necessitating the development more effective therapeutic agents with minimal side effects. This study explores novel 1,2,4-triazine-3(2H)-one derivatives as potential inhibitors Tubulin, pivotal protein in cell division, highlighting targeted approach therapy. Using an integrated computational approach, we combined quantitative structure–activity relationship (QSAR) modeling, ADMET profiling, molecular docking, and dynamics simulations to evaluate predict efficacy stability these compounds. Our QSAR models, developed through rigorous statistical analysis, revealed that descriptors such absolute electronegativity water solubility significantly influence inhibitory activity, achieving predictive accuracy (R 2 ) 0.849. Molecular docking studies identified compounds high binding affinities, particularly Pred28, which exhibited best score − 9.6 kcal/mol. conducted over 100 ns provided further insights into interactions. Pred28 demonstrated notable stability, lowest root mean square deviation (RMSD) 0.29 nm fluctuation (RMSF) values indicative tightly bound conformation Tubulin. The novelty this work lies its methodological rigor integration multiple advanced techniques pinpoint promising potential. findings advance current understanding Tubulin open avenues for synthesis experimental validation compounds, aiming offer new solutions breast treatment.

Language: Английский

Citations

11
Discovery of A Novel Series of Quinazoline–Thiazole Hybrids as Potential Antiproliferative and Anti-Angiogenic Agents DOI Creative Commons
Alexandru Șandor, Ionel Fizeșan,

Ioana Ionuţ

et al.

Biomolecules, Journal Year: 2024, Volume and Issue: 14(2), P. 218 - 218

Published: Feb. 12, 2024

Considering the pivotal role of angiogenesis in solid tumor progression, we developed a novel series quinazoline–thiazole hybrids (SA01–SA07) as antiproliferative and anti-angiogenic agents. Four out seven compounds displayed superior activity (IC50 =1.83-4.24 µM) on HepG2 cells compared to sorafenib = 6.28 µM). The affinity towards VEGFR2 kinase domain was assessed through silico prediction by molecular docking, dynamics studies, MM-PBSA. high degree similarity regarding binding pose within active site VEGFR2, with different orientation 4-substituted-thiazole moieties allosteric pocket. Molecular MM-PBSA evaluations identified SA05 hybrid forming most stable complex sorafenib. impact vascular cell proliferation EA.hy926 cells. Six (SA01–SA05, SA07) anti-proliferative 0.79–5.85 6.62 toxicity evaluated BJ Further studies effect promising compounds, SA04 SA05, assessment EA.hy296 motility using wound healing assay ovo potential CAM sorafenib, led confirmation potential.

Language: Английский

Citations

7
Computational Identification of Bioactive Molecules from Caralluma stalagmifera L. as Potential VEGFR2 Inhibitors for Endometriosis Treatment DOI Creative Commons
Jesudass Joseph Sahayarayan, Balasubramanian Sivaprakasam, Soundar Rajan Kulanthaivel

et al.

Journal of Pharmaceutical Innovation, Journal Year: 2025, Volume and Issue: 20(1)

Published: Jan. 17, 2025

Language: Английский

Citations

0
Designing Novel Potent Oxindole Derivatives as VEGFR2 Inhibitors for Cancer Therapy: Computational Insights from Molecular Docking, Drug-likeness, DFT, and Structural Dynamics Studies DOI

Sowmiya Perinbaraj,

Manikandan Jayaraman,

Jeyaraman Jeyakanthan

et al.

Journal of Molecular Graphics and Modelling, Journal Year: 2025, Volume and Issue: unknown, P. 109049 - 109049

Published: April 1, 2025

Language: Английский

Citations

0
In Silico Structural Study, Design and Efficacy Evaluation of Fluoro Isoxazolidine Derivatives as Potential Antibacterial Agents DOI
Rachid Boutiddar, Khalid Abbiche, Soukayna Baammi

et al.

Journal of Fluorescence, Journal Year: 2025, Volume and Issue: unknown

Published: April 24, 2025

Language: Английский

Citations

0
Design and Optimization of Quinazoline Derivatives as Potent EGFR Inhibitors for Lung Cancer Treatment: A Comprehensive QSAR, ADMET, and Molecular Modeling Investigation DOI Creative Commons
Mohamed Moussaoui, Soukayna Baammi, Hatim Soufi

et al.

ACS Omega, Journal Year: 2024, Volume and Issue: 9(46), P. 45842 - 45857

Published: Nov. 8, 2024

The epidermal growth factor receptor (EGFR) is part of a protein family that controls cell and development. Due to its importance, EGFR has been identified as suitable target for creating novel drugs. For this research, we conducted 2D-QSAR analysis on set 31 molecules derived from quinazoline, which exhibited inhibitory activity against human lung cancer. This investigation incorporated principal component (PCA) multiple linear regression (MLR), leading the development QSAR models with strong predictive capabilities (

Language: Английский

Citations

3
In-silico screening of bioactive compounds of Moringa oleifera as potential inhibitors targeting HIF-1α/VEGF/GLUT-1 pathway against Breast Cancer DOI

Neha Masarkar,

Maynak Pal, Mithun Roy

et al.

Journal of Complementary and Integrative Medicine, Journal Year: 2024, Volume and Issue: unknown

Published: July 18, 2024

Abstract Objectives Breast cancer is among the most heterogeneous and aggressive diseases a foremost cause of death in women globally. Hypoxic activation HIF-1α breast cancers triggers transcription battery genes encoding proteins that facilitate tumor growth metastasis correlated with poor prognosis. Based on reported cytotoxic anti-cancer properties Moringa oleifera ( Mo ), this study explores inhibitory effect bioactive compounds from M. target HIF-1α, VEGF, GLUT-1 silico . Methods The X-ray crystallographic structures GLUT1 were sourced Protein Data Bank (PDB) docked 70 3D PubChem using AutoDock Vina, binding modes analyzed Discovery Studio. Five highest energies selected further drug-likeness, oral bioavailability, ADME, toxicity profiles SwissADME, ADMETSaR, ADMETlab 3.0 web server. Results Out screened compounds, top five best identified namely Apigenin, Ellagic Acid, Isorhamnetin, Luteolin, Myricetin each receptor. Molecular docking results indicated ligands interact strongly receptors through hydrogen bonds hydrophobic interactions. These showed favorable drug-like pharmacokinetic properties, possessed no substantial toxicity, fairly bioavailable. Conclusions suggested possess strong potential developing putative lead targeting are safe natural plant-based drugs against cancer.

Language: Английский

Citations

2
Potent VEGFR-2 inhibitors for resistant breast cancer: a comprehensive 3D-QSAR, ADMET, molecular docking and MMPBSA calculation on triazolopyrazine derivatives DOI Creative Commons
Soukayna Baammi, Achraf El Allali,

Rachid Daoud

et al.

Frontiers in Molecular Biosciences, Journal Year: 2023, Volume and Issue: 10

Published: Nov. 22, 2023

More people are being diagnosed with resistant breast cancer, increasing the urgency of developing new effective treatments. Several lines evidence suggest that blocking kinase activity VEGFR-2 reduces angiogenesis and slows tumor growth. In this study, we developed novel inhibitors based on triazolopyrazine template by using comparative molecular field analysis (CoMFA) similarity indices (CoMSIA) models for 3D-QSAR 23 triazolopyrazine-based compounds against cancer cell (MCF -7). Both CoMFA (Q2 = 0.575; R2 0.936, Rpred2 0.956) CoMSIA/SE 0.847) results demonstrate robustness stability constructed model. Six potent inhibitory were carefully designed, screening ADMET properties revealed their good oral bioavailability ability to diffuse through various biological barriers. When compared most active molecule in data set Foretinib (breast drug), docking six designed had strengthened affinity (-8.9 -10 kcal/mol) VEGFR-2. Molecular Dynamics Simulations MMPBSA calculations applied selected compound T01 highest predicted activity, confirming its pocket over 100 ns. The present provided basis chemical synthesis improved line

Language: Английский

Citations

5
Computer‐Aided Design of VEGFR‐2 Inhibitors as Anticancer Agents: A Review DOI
Abdullahi İbrahim Uba

Journal of Molecular Recognition, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 10, 2024

Due to its intricate molecular and structural characteristics, vascular endothelial growth factor receptor 2 (VEGFR-2) is essential for the development of new blood vessels in various pathological processes conditions, especially cancers. VEGFR-2 inhibitors have demonstrated significant anticancer effects by blocking many signaling pathways linked tumor growth, metastasis, angiogenesis. Several small compounds, including well-tolerated sunitinib sorafenib, been approved as inhibitors. However, widespread side these inhibitors-hypertension, epistaxis, proteinuria, upper respiratory infection-motivate researchers search with better pharmacokinetic profiles. The key interactions required interaction molecules protein target produce desired pharmacological are identified using computer-aided drug design (CADD) methods such pharmacophore QSAR modeling, structure-based virtual screening, docking, dynamics (MD) simulation coupled MM/PB(GB)SA, other computational strategies. This review discusses applications inhibitor design. Future designs may be influenced this review, which focuses on current trends multiple screening layers

Language: Английский

Citations

0
Discovery of Vascular Endothelial Growth Factor Receptor 2 Inhibitors Employing Junction Tree Variational Autoencoder with Bayesian Optimization and Gradient Ascent DOI Creative Commons
Gia-Bao Truong, Thanh-An Pham, Van-Thinh To

et al.

ACS Omega, Journal Year: 2024, Volume and Issue: 9(47), P. 47180 - 47193

Published: Nov. 12, 2024

In the development of anticancer medications, vascular endothelial growth factor receptor 2 (VEGFR-2), which belongs to protein tyrosine kinase family, emerges as one most significant targets interest. The ongoing Food and Drug Administration (FDA) approval novel therapeutic medicines toward VEGFR-2 emphasizes urgent need discover sophisticated molecular structures that are capable reliably limiting activity. Recognizing huge potential deep-learning-based model advancements, we focused our study on exploring chemical space find small molecules potentially inhibiting VEGFR-2. To achieve this goal, utilized junction tree variational autoencoder in combination with two optimization approaches latent space: local Bayesian initial data set gradient ascent nine FDA-approved drugs targeting results yielded a 493 uncharted molecules. Quantitative structure–activity relationship (QSAR) models docking were used assess generated for their inhibitory using predicted pIC50 binding affinity. QSAR constructed RDK7 fingerprints CatBoost algorithm achieved remarkable coefficients determination (R2) 0.792 ± 0.075 0.859 respect internal external validation. Molecular was implemented 4ASD complex optimistic retrospective control (the ROC-AUC value 0.710 activity threshold −7.90 kcal/mol). Newly possessing acceptable corresponding both assessments shortlisted checked interactions at site important residues, including Cys919, Asp1046, Glu885.

Language: Английский

Citations

0