Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent  Anticancer Agents

Nigar Çarşıbaşı

Makale detayları

Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents

Yazarlar:

Nigar Çarşıbaşı

Yayıncı:

Süleyman Demirel University

Ana Başlıklar:

Mühendislik

Dergi:

Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.27 Issue 1, pp.51-63

Belge Tipi:

Makale

Yayın Tarihi:

4/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001287796

pISSN:

1308-6529

Anahtar kelimeler:

Özet:

 Targeting the interaction between tumor suppressor p53 and murine double minute 2MDM2 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.

 Targeting the interaction between tumor suppressor p53 and murine double minute 2MDM2 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.

 Targeting the interaction between tumor suppressor p53 and murine double minute 2MDM2 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.

 Tümör baskılayıcı p53 ile Murine Double Minute 2 MDM2 proteinleri arasındaki etkileşimi hedeflemek, son kanser araştırmalarında öne çıkan bir terapötik strateji olmuştur. Şu anda klinik deneylerde çalışılan birkaç MDM2 hedefli antikanser ilaç molekülü bulunmakla beraber hiçbiri henüz onay alamamıştır. Bu çalışmada, elastik ağ modelleri ile elde edilen MDM2 dinamiklerinin, ligand bazlı farmakofor modelinin oluşturulmasında ardından sanal tarama yürütülerek yeni MDM2 inhibitörlerinin araştırılmasında kılavuz olarak kullanıldığı bir yaklaşım yürütülmüştür. Sanal tarama sonucu elde edilen öncü moleküllerin MDM2ye afiniteleri sabit ve uyarılmış-uyumlu moleküler yerleştirme induced-fit docking metodları ile test edilmiştir. İndüklenmiş yerleştirme kriterleri oluşturulurken bağlanma mekanizması bilgisi kullanılmıştır. Bağlanma serbest enerji değerlerinin doğru tahminini sağlayan Moleküler Mekanik Generalized Born-Surface Area MM-GBSA yönteminin uygulanması ile, yüksek yerleştirme puanları, bağlanma serbest enerjileri ve ilaca benzer fizikokimyasal özelliklere sahip iki adet lider molekül belirlenmiştir. Bu lider moleküller, MDM2 ile ekstra etkileşimler sergilerken kararlı kompleks oluşturmaktadırlar ve sonraki aşamada in vitro çalışmalarda inceleneceklerdir. Sonuç olarak, burada uygulanan kombine bilgisayar destekli strateji, yeni ilaç adaylarının keşfinde başarılı bir yöntem olarak uygulanabilir.

Makale detayları

Pharmacophore Modeling Guided by Conformational Dynamics Reveals Potent Anticancer Agents

Yazarlar:

Nigar Çarşıbaşı

Yayıncı:

Süleyman Demirel University

Ana Başlıklar:

Mühendislik

Dergi:

Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.27 Issue 1, pp.51-63

Belge Tipi:

Makale

Yayın Tarihi:

4/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001287796

pISSN:

1308-6529

elastic network model

drug repurposing

induced-fit docking

MDM2

p53elastik ağ modeli

ilaç yeniden konumlandırma

uyarılmış-uyumlu moleküler yerleştirme

MDM2

p53

Sayı

Makale detayları

Yazarlar: Nigar Çarşıbaşı

Yayıncı: Süleyman Demirel University

Ana Başlıklar: Mühendislik

Dergi: Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.27 Issue 1, pp.51-63

Belge Tipi: Makale

Yayın Tarihi: 4/2023

Belge Dili: İngilizce

Document ID (Org No.): 2001287796

pISSN: 1308-6529

Sayı

Yazarlar:

Nigar Çarşıbaşı

Yayıncı:

Süleyman Demirel University

Ana Başlıklar:

Mühendislik

Dergi:

Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.27 Issue 1, pp.51-63

Belge Tipi:

Makale

Yayın Tarihi:

4/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001287796

pISSN:

1308-6529