<i>Leishmania infantum</i>’a Karşı En İyi Bileşimin Silico Olarak Tanımlanması: Tüm FDA Onaylı İlaçların Yüksek Verimli Tarama
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P: 158-164
Aralık 2019

Leishmania infantum’a Karşı En İyi Bileşimin Silico Olarak Tanımlanması: Tüm FDA Onaylı İlaçların Yüksek Verimli Tarama

Turkiye Parazitol Derg 2019;43(4):158-164
Bilgi mevcut değil.
Bilgi mevcut değil
Alındığı Tarih: 21.01.2019
Kabul Tarihi: 15.08.2019
Yayın Tarihi: 18.12.2019
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Amaç:

Mevcut in-silico araştırması, Leishmania infantum lipofosfoglikan (LPG) ve γ-glutamilsistein sentetazına (γ-GCS) karşı umut verici ilaçlar bulmak amacıyla 20000 Gıda ve İlaç İdaresi onaylı ilaç bileşiklerinin taranması için tasarlandı ve uygulandı.

Yöntemler:

Her iki hedefin protein sekansı alındıktan sonra, 3D yapıları tahmin edildi ve doğrulandı. Moleküler yerleştirme iki varsayılan hedef (LPG ve γ-GCS) arasında yapıldı ve ligand-reseptör etkileşimlerini tahmin etmek için AutoDock 4.2 programı kullanılarak onaylanmış bileşikler seçildi.

Bulgular:

Yirmi bin ilaç bileşiği üzerinde deney yapıldıktan sonra, γ-GCS reseptörü için iki ve LPG reseptörü için beş olmak üzere toplam yedi ligand, bağlanma afiniteleri ve enerjilerine göre yeni, güçlü anti-leishmanial ilaçlar olarak belirlenmiştir. Bunlardan 5 ligand 8,5 kcal/mol’e kadar daha negatif ΔGbinding ile LPG reseptörüne iyi bağlanma kapasitesi gösteren sitotoksik ve anti-kanser özelliklere sahipti. Bunlardan 2 ligand, 7,8 kcal/mol’e kadar daha negatif ΔGbinding ile glutamil reseptörüne iyi bir bağlanma kapasitesi gösterdi.

Sonuç:

En yeni yazılım tabanlı yöntemler, yeni ilaç keşfi için organizmalarda biyolojik hedeflere özgü yeni peptid şablonlarını taramak ve tahmin etmek için güçlü araçlardır. Bununla birlikte, in vitro ve in vivo tekniklerin kullanımı, öngörülen ligandların potansiyelinin daha iyi değerlendirilmesi için bir gerekliliktir. İn-silico yaklaşımların yardımı ile daha aktif bileşiklerin moleküler düzeyde etki mekanizmasınının tanımlanması mümkün olmaktadır ve böylece en olası moleküler hedef belirlenebilmekte ve in vitro ve in vivo teknikleri kullanarak sonraki optimizasyon yapılabilmektedir.

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