Literature DB >> 31491446

Screening of different drug design tools to predict the mode of action of steroidal derivatives as anti-cancer agents.

Mohamed S Nafie1, Mohamed A Tantawy2, Gamal A Elmgeed3.   

Abstract

There is a pressing need to discover and develop novel drugs against cancer. With the new era of bioinformatics, which integrates different aspects, drug development has been tremendously improved. Recently, extensive research was directed towards the rational modification of steroid molecules against different disease especially cancer. Moreover, heterocyclic steroid derivatives have shown a lot of different biological activities such as antimicrobial, anti-inflammatory, and anti-cancer activities. Molecular docking methods can be used to explore how the steroid derivatives conformations can adopt within the binding sites of specific macromolecular targets involved in cancer progression. We conducted this study to investigate the accuracy of different molecular docking calculations using different steroidal molecular targets, and to define the most accurate one to study the mode of action of steroid derivatives as potential anti-cancer drugs. Our results revealed that the Dock6, PLANTS, AutoDock, GLIDE (SP and XP), and GOLD (ASP, Chemscore, and PLP) software were able to maintain the binding mode of the co-crystallized ligands inside their proteins by achieving RMSD values lower than two. Moreover, molecular docking study revealed that compound 4, and 5 are promising steroidal derivatives as anti-cancer drugs. Further on, the cytotoxic activity of the selected steroidal derivatives were tested against leukemia cell line using MTT assay. The results revealed that compound 4, and 5 were potential cytotoxic agents against THP-1 cells (IC50s were 44.67 µM, and 46.77 µM, respectively), these results are in agreement with the molecular docking study.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Anti-cancer; Drug design; Heterocyclic; Leukemia; Molecular docking; Steroid derivatives

Mesh:

Substances:

Year:  2019        PMID: 31491446     DOI: 10.1016/j.steroids.2019.108485

Source DB:  PubMed          Journal:  Steroids        ISSN: 0039-128X            Impact factor:   2.668


  14 in total

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Authors:  Reda F A Abdelhameed; Mohamed S Nafie; Ahmed K Ibrahim; Koji Yamada; Maged S Abdel-Kader; Amany K Ibrahim; Safwat A Ahmed; Jihan M Badr; Eman S Habib
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Journal:  RSC Adv       Date:  2020-06-24       Impact factor: 4.036

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Journal:  Antioxidants (Basel)       Date:  2021-12-22
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