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Journals / Adıyaman Üniversitesi Fen Bilimleri Dergisi / 2019 / 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

Adamu UZAIRU
Shola Elijah ADENIJI
Sani UBA
Pages
77–98
Publication Date
2022-10-12
DOI
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AI Summary & Key Takeaways

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

The externalvalidation set used for confirming the predictive power of the model has R2pred of 0.7482.Conclusion: Reliability, stability and robustness of the model obtained by thevalidation 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 forpredicting the activity of 1,2,4-Triazole derivatives as anti-tubercular antagonist.Methods: Genetic function approximation (GFA) was employed on a dataset of1,2,4-Triazole derivatives to investigate their activities behavior on Mycobacteriumtuberculosis.
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Key Findings & Data:This approach led to selection of the optimum descriptors and to generate thecorrelation QSAR model that relate their activities values against Mycobacteriumtuberculosis with the molecular structures of the inhibitors.Results: The built model was validated and was found to have squared correlationcoefficient (R2) of 0.9134, adjusted squared correlation coefficient (Radj) of 0.8753 andLeave one out (LOO) cross validation coefficient (𝐐𝐜𝐯𝟐 ) value of 0.8231.
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Conclusion & Impact:The externalvalidation set used for confirming the predictive power of the model has R2pred of 0.7482.Conclusion: Reliability, stability and robustness of the model obtained by thevalidation 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:Domain Parameters

Abstract

Objectives: The research aimed to develop a theoretical (QSAR) model forpredicting the activity of 1,2,4-Triazole derivatives as anti-tubercular antagonist.Methods: Genetic function approximation (GFA) was employed on a dataset of1,2,4-Triazole derivatives to investigate their activities behavior on Mycobacteriumtuberculosis. This approach led to selection of the optimum descriptors and to generate thecorrelation QSAR model that relate their activities values against Mycobacteriumtuberculosis with the molecular structures of the inhibitors.Results: The built model was validated and was found to have squared correlationcoefficient (R2) of 0.9134, adjusted squared correlation coefficient (Radj) of 0.8753 andLeave one out (LOO) cross validation coefficient (𝐐𝐜𝐯𝟐 ) value of 0.8231. The externalvalidation set used for confirming the predictive power of the model has R2pred of 0.7482.Conclusion: Reliability, stability and robustness of the model obtained by thevalidation 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 (R2 ) 0.9134, düzeltilmiş korelasyon katsayısının karesi (Radj) 0.8753 ve tek-çıkışlı (LOO) çapraz doğrulama katsayı (Qୡ୴ ଶ ) değeri 0.8231 olarak bulunmuştur. Modelin öngörücü gücünü doğrulamak için kullanılan harici doğrulama seti, 0.7482 R୮୰ୣୢ ଶ '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

UZAIRU, A., ADENIJI, S. E., UBA, S. (2022). 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/428489

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