ArticleJournal, genetic engineering & biotechnology2020
In silico design and molecular docking study of CDK2 inhibitors with potent cytotoxic activity against HCT116 colorectal cancer cell line.
Article in Journal, genetic engineering & biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 36 citations in OpenAlex.
- Cannabis as a source of novel therapeutics: A computational study combining LBDD and structure-based docking/dynamics to identify novel drug-like compounds for colorectal cancer.Journal, genetic engineering & biotechnology · 2026Article
- New predicted dual CDK-2/CDK-1 inhibitors from Aspergillus unguis isolate SP51-EGY with relative selectivity for colorectal cancer cells: a computational and experimental approach.Scientific reports · 2026Article
- Quantum and molecular modelling of abrocitinib as a potential disruptor of cell polarity in colorectal cancer.Scientific reports · 2025Article
- Naringenin and its structural analogues inhibit CDK2: a combined MD-MMGBSA and protein-ligand interaction study for colon cancer.In silico pharmacology · 2025Article
- Molecular interaction and MD-simulations: investigation of Sizofiran as a promising anti-cancer agent targeting eIF4E in colorectal cancer.In silico pharmacology · 2024Article
- Computational Exploration of Anti-cancer Potential of Flavonoids against Cyclin-Dependent Kinase 8: AnACS omega · 2023Article
- Computational identification of potential inhibitors targetingFrontiers in chemistry · 2023Article
- KUALA: a machine learning-driven framework for kinase inhibitors repositioning.Scientific reports · 2022Article
- Synthesis and Evaluation of Some New 4Pharmaceuticals (Basel, Switzerland) · 2022Article
- Evaluation of Potential Anti-Hepatitis A Virus 3C Protease Inhibitors Using Molecular Docking.International journal of molecular sciences · 2022Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColorectal cancer is common to both sexes; third in terms of morbidity and second in terms of mortality, accounting for 10% and 9.2% of cancer cases in men and women globally. Although drugs such as bevacizumab, Camptosar, and cetuximab are being used to manage colorectal cancer, the efficacy of the drugs has been reported to vary from patient to patient. These drugs have also been reported to have varying degrees of side effects; thus, the need for novel drug therapies with better efficacy and lesser side effects. In silico drugs design methods provide a faster and cost-effect method for lead identification and optimization. The aim of this study, therefore, was to design novel imidazol-5-ones via in silico design methods.
resultsA QSAR model was built using the genetic function algorithm method to model the cytotoxicity of the compounds against the HCT116 colorectal cancer cell line. The built model had statistical parameters; R
conclusionThe QSAR model built was stable, robust, and had a good predicting ability. Thus, predictions made by the model were reliably employed in further in silico studies. The compounds designed were more active than the template and showed better inhibition of the CDK2 enzyme compared to the standard drugs sorafenib and kenpaullone.
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