Journals / Adıyaman Üniversitesi Fen Bilimleri Dergisi / 2026 / Cilt: 9 Sayı: 1

Activity Modeling of Some Potent Inhibitors Against Mycobacterium tuberculosis Using Genetic Function Approximation Approach

Genetik Fonksiyon Tahmin Yaklaşımı Kullanılarak Mycobacterium tuberculosis’e Karşı Bazı Etkili İnhibitörlerin Aktivite Modellemelerinin Yapılması

Pages
77–98
Publication Date
2019-06-28
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Conclusion: Reliability, stability and robustness of the model obtained by the validation test indicate that the model can be used to design and synthesis other 1,2,4-Triazole derivatives with improved anti-tubercular activities.

📌 3 Key Takeaways

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Objective & Hypothesis:Objectives: The research aimed to develop a theoretical (QSAR) model for predicting the activity of 1,2,4-Triazole derivatives as anti- tubercular antagonist .
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Key Findings & Data:Methods: Genetic function approximation (GFA) was employed on a dataset of 1,2,4-Triazole derivatives to investigate their activities behavior on mycobacterium tuberculosis .
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Conclusion & Impact:Conclusion: Reliability, stability and robustness of the model obtained by the validation test indicate that the model can be used to design and synthesis other 1,2,4-Triazole derivatives with improved anti-tubercular activities.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Uygulanabilirlik etki alanı · Genetik fonksiyon yaklaşımı · QSAR

Abstract

Objectives: The research aimed to develop a theoretical (QSAR) model for predicting the activity of 1,2,4-Triazole derivatives as anti- tubercular antagonist . Methods: Genetic function approximation (GFA) was employed on a dataset of 1,2,4-Triazole derivatives to investigate their activities behavior on mycobacterium tuberculosis . This approach led to selection of the optimum descriptors and to generate the correlation QSAR model that relate their activities values against mycobacterium tuberculosis with the molecular structures of the inhibitors. Results: The built model was validated and was found to have squared correlation coefficient ( R 2 ) of 0.9134 , adjusted squared correlation coefficient (R adj ) of 0.8753 and Leave one out (LOO) cross validation coefficient ( ) value of 0.8231. The external validation set used for confirming the predictive power of the model has R 2 pred of 0.7482. Conclusion: Reliability, stability and robustness of the model obtained by the validation test indicate that the model can be used to design and synthesis other 1,2,4-Triazole derivatives with improved anti-tubercular activities.

Özet

Amaç : Araştırma, anti-tüberküler antagonisti olarak 1,2,4-Triazol türevlerinin aktivitesini tahmin etmeye yönelik teorik (QSAR) bir model geliştirmeyi amaçlamıştır. Yöntem : Genetik fonksiyon yaklaşımı (GFA), 1,2,4-Triazol türevlerinin Mycobacterium tuberculosis üzerine etki tarzlarını araştırmak amacıyla kullanılmıştır. Bu yaklaşım, optimum tanımlayıcıların seçimine ve Mycobacterium tuberculosis üzerine etki değerlerini inhibitörlerin moleküler yapılarıyla ilişkilendiren korelasyon QSAR modelinin oluşturulmasına imkân vermiştir. Sonuç : Oluşturulan model doğrulanmış ve korelasyon katsayısının karesi (R 2 ) 0.9134, düzeltilmiş korelasyon katsayısının karesi (R adj ) 0.8753 ve tek-çıkışlı (LOO) çapraz doğrulama katsayı ( ) değeri 0.8231 olarak bulunmuştur. Modelin öngörücü gücünü doğrulamak için kullanılan harici doğrulama seti, 0.7482 'ye sahiptir. Tartışma : Doğrulama testi ile elde edilen modelin güvenilirliği, kararlılığı ve sağlamlığı, modelin, gelişmiş anti-füberküler aktivitesine sahip diğer 1,2,4-Triazol türevlerini tasarlamak ve sentezlemek için kullanılabileceğini göstermektedir.

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Cite This Article

Adenıjı, S. E., Uba, S., Uzaıru, A. (2019). Activity Modeling of Some Potent Inhibitors Against Mycobacterium tuberculosis Using Genetic Function Approximation Approach. Adıyaman Üniversitesi Fen Bilimleri Dergisi, Cilt: 9 Sayı: 1, 77–98. https://ajindex.com/articles/1352305

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