Araştırma Makalesi

Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents

Cilt: 27 Sayı: 1 25 Nisan 2023
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Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents

Öz

Targeting the interaction between tumor suppressor p53 and murine double minute 2(MDM2) has been an attractive therapeutic strategy of recent cancer research. There are a few number of MDM2-targeted anticancer drug molecules undergoing clinical trials, yet none of them have been approved so far. In this study, a new approach is employed in which dynamics of MDM2 obtained by elastic network models are used as a guide in the generation of the ligand-based pharmacophore model prior to virtual screening. Hit molecules exhibiting high affinity to MDM2 were captured and tested by rigid and induced-fit molecular docking. The knowledge of the binding mechanism was used while creating the induced-fit docking criteria. Application of Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) method provided an accurate prediction of the binding free energy values. Two leading hit molecules which have shown better docking scores, binding free energy values and drug-like molecular properties were identified. These hits exhibited extra intermolecular interactions with MDM2, indicating a stable complex formation and hence would be further tested in vitro. Finally, the combined computational strategy employed in this study can be a promising tool in drug design for the discovery of potential new hits.

Anahtar Kelimeler

Kaynakça

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Ayrıntılar

Birincil Dil

İngilizce

Konular

Mühendislik

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

25 Nisan 2023

Gönderilme Tarihi

25 Mayıs 2022

Kabul Tarihi

7 Kasım 2022

Yayımlandığı Sayı

Yıl 2023 Cilt: 27 Sayı: 1

Kaynak Göster

APA
Çarşıbaşı, N. (2023). Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 27(1), 51-63. https://doi.org/10.19113/sdufenbed.1121167
AMA
1.Çarşıbaşı N. Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents. Süleyman Demirel Üniv. Fen Bilim. Enst. Derg. 2023;27(1):51-63. doi:10.19113/sdufenbed.1121167
Chicago
Çarşıbaşı, Nigar. 2023. “Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 27 (1): 51-63. https://doi.org/10.19113/sdufenbed.1121167.
EndNote
Çarşıbaşı N (01 Nisan 2023) Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 27 1 51–63.
IEEE
[1]N. Çarşıbaşı, “Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents”, Süleyman Demirel Üniv. Fen Bilim. Enst. Derg., c. 27, sy 1, ss. 51–63, Nis. 2023, doi: 10.19113/sdufenbed.1121167.
ISNAD
Çarşıbaşı, Nigar. “Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 27/1 (01 Nisan 2023): 51-63. https://doi.org/10.19113/sdufenbed.1121167.
JAMA
1.Çarşıbaşı N. Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents. Süleyman Demirel Üniv. Fen Bilim. Enst. Derg. 2023;27:51–63.
MLA
Çarşıbaşı, Nigar. “Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 27, sy 1, Nisan 2023, ss. 51-63, doi:10.19113/sdufenbed.1121167.
Vancouver
1.Nigar Çarşıbaşı. Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents. Süleyman Demirel Üniv. Fen Bilim. Enst. Derg. 01 Nisan 2023;27(1):51-63. doi:10.19113/sdufenbed.1121167

Cited By

e-ISSN :1308-6529
Linking ISSN (ISSN-L): 1300-7688

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