Computational Bioactivity Analysis and Bioisosteric Investigation of the Approved Breast Cancer Drugs Proposed New Design Drug Compounds: Increased Bioactivity Coming with Silicon and Boron

Author(s): Esma Eryilmaz Dogan*

Journal Name: Letters in Drug Design & Discovery

Volume 18 , Issue 6 , 2021

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Graphical Abstract:


Background: The breast cancer takes the first place among women cancer diagnosed worldwide.

Objective: Based on the preferential multi-targeted approach to cancer therapy, we, in this study, aimed to design in silico drug candidates possessing multi-targeted bioactivity to cope with multidrug resistance using the known drug structures, molecular modeling, and ADME parameters.

Materials and Methods: We first evaluated the bioactivity score of the approved breast cancer drugs across the top-three drug targets GPCR, kinase, and nuclear receptors and calculated their physicochemical properties to see their drug-likeness profiles. Among 29 approved drugs, Aromasin and Capecitabine showed the broadest bioactivity across the targets listed. By using molecular modeling and bioisosteric modifications, and applying two filtering approaches, we investigated thirty-one analogues of Aromasin and Capecitabine.

Results: Software prediction resulted in that the compounds A14, C4, and C13 replaced with B(OH)2 and/or Si(CH3)3 showed a broader spectrum of biological activity with a multi-targeted manner than even the approved analogs.

Conclusion: The interesting point of these new design molecules is to have either silicon and/or boron incorporation. The increased bioactivity effect of Silicon and Boron incorporation is also seen in the recently approved drug list of FDA and in clinical trials ongoing. Our new design boron and silicon-based molecules appeared to be promising candidates for breast cancer treatment to be tested in vitro, in vivo, and in the clinic for further pharmacological investigations.

Keywords: Breast cancer, drug design, computational bioactivity, silicon, boron, computer aided drug design, molecular modeling.

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Article Details

Year: 2021
Published on: 13 January, 2021
Page: [551 - 561]
Pages: 11
DOI: 10.2174/1570180818666210114115415
Price: $65

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