Research Article
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Interpretable QSAR Modelling and QSAR-Based Virtual Screening of Novel 3H-Thiazolo[4,5-b]pyridin-2-one Derivatives as Potential Antioxidant Drug Candidates

Year 2023, Volume: 48 Issue: 3, 411 - 430, 18.10.2023
https://doi.org/10.55262/fabadeczacilik.1309814

Abstract

Quantitative structure-activity relationship (QSAR) study has been carried out for 32 N3 substituted 3H-thiazolo[4,5-b]pyridin-2-one derivatives as potential antioxidant drug candidates. The genetic algorithm (GA) and multiple linear regression analysis (MLRA) were used as appropriate techniques for descriptors selection and correlation models generation. The four best regressions for the prediction of the ability to scavenge the DPPH radical were generated as three-parameter QSAR models with the highest statistical characteristics and predictive ability. Based on the validation parameters of the generated models, it may be stated that they all satisfy the statistical requirements for their goodness-of-fitting with no current overfitting. The predictive ability of the constructed models was assessed with both internal and external validation approach and estimated with the leave-one-out and leave-group-out cross-validation coefficients (Q2LOO and Q2LGO). The values of Q2LOO (0.7060  0.7480) and Q2LGO (0.6647  0.7711) are reasonable, showing that the models are significant and robust to predict the free radical scavenging activity of the compounds from both training and validation sets. Applicability domain defining technique was employed to the obtained models and it was indicated that most structures were adequately represented by the chemical space of the models.

Supporting Institution

Danylo Halytsky Lviv National Medical University, Lviv, Ukraine, The Ministry of Health of Ukraine

Project Number

state registration number 0121U109330

Thanks

O. K. thanks Universidad San Pablo CEU, Madrid, Spain, for a Postdoctoral Contract for Ukrainian Researchers, she is exceedingly grateful to Prof. Beatriz de Pascual-Teresa Fernández, all the Group members, for their solidarity with Ukraine and their support aimed to assist the Ukrainian University community.

References

  • Chaban, T. I., Panchuk, R. R., Klenina, O. V., Skorokhyd, N. R., Ogurtsov, V. V., & Chaban, I. G. (2012). Synthesis and evaluation of antitumor activity of some thiazolo(4,5-b) pyridines. Вiopolymers and Cell.
  • Chaban, T. I., Ogurtsov, V. V., Chaban, I. G., Klenina, O. V., & Komarytsia, J. D. (2013). Synthesis and antioxidant activity evaluation of novel 5, 7-dimethyl- 3 H-thiazolo(4,5-b)pyridines. Phosphorus, Sulfur, and Silicon and the Related Elements, 188(11), 1611-1620.

Potansiyel Antioksidan İlaç Adayları Olarak Yeni 3H-Tiazolo[4,5-b]piridin-2-on Türevlerinin Yorumlanabilir QSAR Modellemesi ve QSAR Tabanlı Sanal Taraması

Year 2023, Volume: 48 Issue: 3, 411 - 430, 18.10.2023
https://doi.org/10.55262/fabadeczacilik.1309814

Abstract

Potansiyel antioksidan ilaç adayları olarak 32 N3 ikameli 3H-tiazolo[4,5-b]piridin-2-on türevleri için kantitatif yapı-aktivite ilişkisi (QSAR) çalışması yapılmıştır. Tanımlayıcı seçimi ve korelasyon modelleri oluşturmak için uygun teknikler olarak genetik algoritma (GA) ve çoklu doğrusal regresyon analizi (MLRA) kullanıldı. DPPH radikalini temizleme yeteneğinin tahmini için en iyi dört regresyon, en yüksek istatistiksel özelliklere ve öngörü yeteneğine sahip üç parametreli QSAR modelleri olarak üretildi. Oluşturulan modellerin doğrulama parametrelerine dayanarak, bunların hepsinin, mevcut aşırı uyum olmadan uyumun iyiliği için istatistiksel gereklilikleri karşıladığı söylenebilir. Oluşturulan modellerin tahmin yeteneği, hem iç hem de dış doğrulama yaklaşımıyla değerlendirildi ve birini dışarıda bırak ve grubu dışarıda bırak çapraz doğrulama katsayıları (Q2LOO ve Q2LGO) ile tahmin edildi. Q2LOO (0.7060  0.7480) ve Q2LGO (0.6647  0.7711) değerleri makul olup, modellerin hem eğitim hem de doğrulama setlerinden bileşiklerin serbest radikal yakalama aktivitesini tahmin etmek için önemli ve sağlam olduğunu göstermektedir. Elde edilen modellere uygulanabilirlik alanı tanımlama tekniği uygulandı ve çoğu yapının modellerin kimyasal uzayı tarafından yeterince temsil edildiği belirtildi.

Project Number

state registration number 0121U109330

References

  • Chaban, T. I., Panchuk, R. R., Klenina, O. V., Skorokhyd, N. R., Ogurtsov, V. V., & Chaban, I. G. (2012). Synthesis and evaluation of antitumor activity of some thiazolo(4,5-b) pyridines. Вiopolymers and Cell.
  • Chaban, T. I., Ogurtsov, V. V., Chaban, I. G., Klenina, O. V., & Komarytsia, J. D. (2013). Synthesis and antioxidant activity evaluation of novel 5, 7-dimethyl- 3 H-thiazolo(4,5-b)pyridines. Phosphorus, Sulfur, and Silicon and the Related Elements, 188(11), 1611-1620.
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Details

Primary Language English
Subjects Pharmaceutical Chemistry
Journal Section Research Article
Authors

Olena Klenina 0000-0002-8946-3698

Project Number state registration number 0121U109330
Publication Date October 18, 2023
Submission Date June 5, 2023
Published in Issue Year 2023 Volume: 48 Issue: 3

Cite

APA Klenina, O. (2023). Interpretable QSAR Modelling and QSAR-Based Virtual Screening of Novel 3H-Thiazolo[4,5-b]pyridin-2-one Derivatives as Potential Antioxidant Drug Candidates. Fabad Eczacılık Bilimler Dergisi, 48(3), 411-430. https://doi.org/10.55262/fabadeczacilik.1309814