Novel compounds from endophytic fungi of Ceriops decandra inhibit breast cancer cell growth through estrogen receptor alpha in in-silico study

Munshi, M. H.; Zilani, Md. Nazmul Hasan; Islam, Aminul; Biswas, Partha; Das, Avizit; Afroz, Farhana; Hasan, Md. Nazmul

doi:10.1016/j.imu.2022.101046

Cited by 16 publications

(3 citation statements)

References 44 publications

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“…These four phytochemicals’ pharmacokinetic features were determined with the help of online servers from the pkCSM pharmacokinetics and Swiss ADME organizations, as indicated in ( Table 2 ) [ 69 , 70 , 71 ]. As part of the study’s pharmacokinetic components, Lipinski’s five-rule pharmacophore properties (molecular weight, rotational bond count, logP value, hydrogen bond donors and acceptors, and degree of infringement) were evaluated for all selected ligands using Lipinski’s five-rule approach (violation level) [ 72 , 73 , 74 ]. All the selected natural bioactive phytochemicals possessed better human intestinal absorption, better BBB value, AMES toxicity, no carcinogenicity, and no hepatotoxicity for both the human and mice research model, except for the selected control compound for our research study [ 75 , 76 , 77 ].…”

Section: Discussionmentioning

confidence: 99%

Study of MDM2 as Prognostic Biomarker in Brain-LGG Cancer and Bioactive Phytochemicals Inhibit the p53-MDM2 Pathway: A Computational Drug Development Approach

Biswas¹,

Bibi

Yousafi

et al. 2023

Molecules

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An evaluation of the expression and predictive significance of the MDM2 gene in brain lower-grade glioma (LGG) cancer was carried out using onco-informatics pipelines. Several transcriptome servers were used to measure the differential expression of the targeted MDM2 gene and search mutations and copy number variations. GENT2, Gene Expression Profiling Interactive Analysis, Onco-Lnc, and PrognoScan were used to figure out the survival rate of LGG cancer patients. The protein–protein interaction networks between MDM2 gene and its co-expressed genes were constructed by Gene-MANIA tool. Identified bioactive phytochemicals were evaluated through molecular docking using Schrödinger Suite Software, with the MDM2 (PDB ID: 1RV1) target. Protein–ligand interactions were observed with key residues of the macromolecular target. A molecular dynamics simulation of the novel bioactive compounds with the targeted protein was performed. Phytochemicals targeting MDM2 protein, such as Taxifolin and (-)-Epicatechin, have been shown with more highly stable results as compared to the control drug, and hence, concluded that phytochemicals with bioactive potential might be alternative therapeutic options for the management of LGG patients. Our once informatics-based designed pipeline has indicated that the MDM2 gene may have been a predictive biomarker for LGG cancer and selected phytochemicals possessed outstanding interaction results within the macromolecular target’s active site after utilizing in silico approaches. In vitro and in vivo experiments are recommended to confirm these outcomes.

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Section: Discussionmentioning

confidence: 99%

Study of MDM2 as Prognostic Biomarker in Brain-LGG Cancer and Bioactive Phytochemicals Inhibit the p53-MDM2 Pathway: A Computational Drug Development Approach

Biswas¹,

Bibi

Yousafi

et al. 2023

Molecules

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“…To characterize the material, high-intensity electron ionization (70 eV) was deployed. The column oven was warmed to 60 °C for 1 min, escalated by 5 °C /min to 240 °C, and retained at that temperature for 4 mins while the intake temperature was held constant at 280 °C ( Munshi et al, 2022 ). The sample components might be recognized by comparing them to the National Institute of Standards and Technology (NIST) database.…”

Section: Methodsmentioning

confidence: 99%

Profiling of secondary metabolite and evaluation of anti-diabetic potency of Crotalaria quinquefolia (L): In-vitro, in-vivo, and in-silico approaches

Nahar,

Nazmul Hasan Zilani,

Biswas

et al. 2024

Saudi Pharmaceutical Journal

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“…Te 3d structure of a protein and protein-ligand complex is essential in molecular modeling for lead discovery [23][24][25]. Quantitative structure-activity relationships (QSAR), biological tests, and pharmacophore analysis can all be used to improve and create new leads [26][27][28]. Structurebased drug design assists in creating more potent and signifcant molecules during the drug development process [29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Molecular Dynamics Simulation and Pharmacoinformatic Integrated Analysis of Bioactive Phytochemicals from Azadirachta indica (Neem) to Treat Diabetes Mellitus

Abdullah¹,

Biswas²,

Sahabuddin³

et al. 2023

Journal of Chemistry

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Diabetes mellitus is a chronic hormonal and metabolic disorder in which our body cannot generate necessary insulin or does not act in response to it, accordingly, ensuing in discordantly high blood sugar (glucose) levels. Diabetes mellitus can lead to systemic dysfunction in the multiorgan system, including cardiac dysfunction, severe kidney disease, lowered quality of life, and increased mortality risk from diabetic complications. To uncover possible therapeutic targets to treat diabetes mellitus, the in silico drug design technique is widely used, which connects the ligand molecules with target proteins to construct a protein-ligand network. To identify new therapeutic targets for type 2 diabetes mellitus, Azadirachta indica is subjected to phytochemical screening using in silico molecular docking, pharmacokinetic behavior analysis, and simulation-based molecular dynamic analysis. This study has analyzed around 63 phytochemical compounds, and the initial selection of the compounds was made by analyzing their pharmacokinetic properties by comparing them with Lipinski’s rule of 5. The selected compounds were subjected to molecular docking. The top four ligand compounds were reported along with the control drug nateglinide based on their highest negative molecular binding affinity. The protein-ligand interaction of selected compounds has been analyzed to understand better how compounds interact with the targeted protein structure. The results of the in silico analysis revealed that 7-Deacetyl-7-oxogedunin had the highest negative docking score of −8.9 Kcal/mol and also demonstrated standard stability in a 100 ns molecular dynamic simulation performed with insulin receptor ectodomain. It has been found that these substances may rank among the essential supplementary antidiabetic drugs for treating type 2 diabetes mellitus. It is suggested that more in vivo and in vitro research studies be carried out to support the conclusions drawn from this in silico research strategy.

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Novel compounds from endophytic fungi of Ceriops decandra inhibit breast cancer cell growth through estrogen receptor alpha in in-silico study

Cited by 16 publications

References 44 publications

Study of MDM2 as Prognostic Biomarker in Brain-LGG Cancer and Bioactive Phytochemicals Inhibit the p53-MDM2 Pathway: A Computational Drug Development Approach

Study of MDM2 as Prognostic Biomarker in Brain-LGG Cancer and Bioactive Phytochemicals Inhibit the p53-MDM2 Pathway: A Computational Drug Development Approach

Profiling of secondary metabolite and evaluation of anti-diabetic potency of Crotalaria quinquefolia (L): In-vitro, in-vivo, and in-silico approaches

Molecular Dynamics Simulation and Pharmacoinformatic Integrated Analysis of Bioactive Phytochemicals from Azadirachta indica (Neem) to Treat Diabetes Mellitus

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