Computer-aided anticancer drug design: In vitro and in silico studies of new iminocoumarin derivative

Kecel‐Gunduz, Serda; Budama‐Kilinc, Yasemin; Gök, Bahar; Bıçak, Bilge; Akman, Gizem; Arvas, Büşra; Aydoğan, Feray; Yolaçan, Çiğdem

doi:10.1016/j.molstruc.2021.130539

Cited by 9 publications

(5 citation statements)

References 88 publications

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“…We verified their resistance power against some cancer-related PTM sites (succinylation, ubiquitination, and phosphorylation) of hub proteins by molecular docking analysis and found their significant binding affinities. The literature review also supported our proposed ligands Suramin [171], Rifaximin [172], Telmisartan [173], Phenylpropan [174], Tukysa Tucatinib [175,176] Lynparza Olaparib [177], and TG.02 [14,178] as the candidate drug molecules for the treatment against BC. Therefore, the findings of this study might be promising and useful resources to wet-lab researchers and clinicians for further investigation to develop an early treatment plan against BC.…”

Section: Discussionsupporting

confidence: 66%

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Tuly,

Hossen,

Islam

et al. 2023

Medicina

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Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study’s findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.

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Section: Discussionsupporting

confidence: 66%

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Tuly,

Hossen,

Islam

et al. 2023

Medicina

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“…UV-Vis absorption spectrophotometry is a useful technique to investigate the interaction between anticancer drug molecules and DNA [ 23 , 24 , 25 ]. Therefore, we investigated the potential of LNEO as an anticancer drug molecule using UV-Vis absorption spectrophotometry.…”

Section: Resultsmentioning

confidence: 99%

“…DNA is the primary pharmacological target of anticancer drugs. Therefore, it is very important to determine the interactions between the new anticancer drug molecule and DNA [ 25 ]. Therefore, in this study, we demonstrated the potential of LNEO as a potential anticancer molecule by evaluating its interaction with DNA.…”

Section: Discussionmentioning

confidence: 99%

“…The hypochromic effect and redshift are typical of the binding of the anticancer molecule to DNA in the intercalation mode [ 63 ]. Molecules that intercalatively bind to DNA are used in cancer treatment because they inhibit DNA replication in cancer cells [ 25 , 64 ]. Our results showed that LNEO could be an effective anticancer agent for cancer treatment.…”

Section: Discussionmentioning

confidence: 99%

“…Calf Thymus DNA (CT-DNA) was used for the determination of the interaction of the LNEO with DNA [ 25 ]. The CT-DNA solution in Tris-HCl/NaCl (pH 7.2) buffer gave a UV absorbance ratio of 1.9 at A 260 /A 280 at 260 and 280 nm wavelengths.…”

Section: Methodsmentioning

confidence: 99%

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Laurus nobilis L. Essential Oil-Loaded PLGA as a Nanoformulation Candidate for Cancer Treatment

et al. 2022

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The aim of this study was to obtain essential oil (LNEO) from the Laurus nobilis L. plant, and to prepare LNEO-loaded poly lactic-co-glycolic acid (PLGA) nanoparticles (NPs) as an approach in cancer treatment. The components of the obtained LNEO were analyzed using GC-MS. The LNEO-NPs were synthesized by the single-emulsion method. The LNEO-NPs were characterized using UV-Vis spectrometry, Dynamic Light Scattering (DLS), Scanning Electron Microscopy (SEM), and a DNA binding assay, which was performed via the UV-Vis titration method. According to the results, the LNEO-NPs had a 211.4 ± 4.031 nm average particle size, 0.068 ± 0.016 PdI, and −7.87 ± 1.15 mV zeta potential. The encapsulation efficiency and loading capacity were calculated as 59.25% and 25.65%, respectively, and the in vitro drug release study showed an LNEO release of 93.97 ± 3.78% over the 72 h period. Moreover, the LNEO was intercalatively bound to CT-DNA. In addition, the mechanism of action of LNEO on a dual PI3K/mTOR inhibitor was predicted, and its antiproliferative activity and mechanism were determined using molecular docking analysis. It was concluded that LNEO-loaded PLGA NPs may be used for cancer treatment as a novel phytotherapeutic agent-based controlled-release system.

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Synthesis, In Vitro α-Amylase Inhibition Activity and Molecular Docking of some Coumarin Derivatives

Chaabouni,

Dhouib,

Khdhiri

et al. 2024

Chemistry Africa

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Computer-aided anticancer drug design: In vitro and in silico studies of new iminocoumarin derivative

Cited by 9 publications

References 88 publications

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Laurus nobilis L. Essential Oil-Loaded PLGA as a Nanoformulation Candidate for Cancer Treatment

Synthesis, In Vitro α-Amylase Inhibition Activity and Molecular Docking of some Coumarin Derivatives

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