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QSAR-МОДЕЛИРОВАНИЕ СВЯЗИ "СТРУКТУРА - АНТИОКИСЛИТЕЛЬНАЯ АКТИВНОСТЬ" В РЯДУ НЕКОТОРЫХ ПРОИЗВОДНЫХ БЕНЗОПИРАНА И БЕНЗОФУРАНА

МАРТЫНОВА, Ю.З., ХАЙРУЛЛИНА, В.Р., ГАРИФУЛЛИНА, Г.Г., МИЦУКОВА, Д.С., ЗАРУДИЙ, Ф.С., МУСТАФИН, А.Г.

Дата публикации: 2019

DOI: 10.33184/bulletin-bsu-2019.3.6

Аннотация:

С использованием программы GUSAR 2013 выполнен количественный анализ взаимосвязи между структурой и антиокислительной активностью 64 производных бензопирана и бензофурана в интервале значений lgk7= 0.00 ÷ 7.06. Построено девять статистически значимых валидных консенсус-моделей, характеризующихся высокой точностью прогноза параметра lgk7 для структур обучающих и тестовых выборок.

ключевые слова:
АНТИОКИСЛИТЕЛЬНАЯ АКТИВНОСТЬ, АНТИОКСИДАНТЫ, МОДЕЛИРОВАНИЕ QSAR, ПРОГРАММА GUSAR 2013, MNA- И QNA-ДЕСКРИПТОРЫ, ВАК

Издатель: Башкирский государственный университет

Тип: Article

УДК: 544.165



QSAR-MODELING OF THE RELATIONSHIP "STRUCTURE - ANTIOXIDATIVE ACTIVITY" IN A SERIES OF SOME BENZOPIRANE AND BENZOFURANE DERIVATIVES

Martynova, Yu. Z., Khairullina, V.R., Garifullina, G.G., Mitsukova, D.S., Zarudiy, F.S., Mustafin, A.G.

Publication date: 2019

DOI: 10.33184/bulletin-bsu-2019.3.6

Abstract:

Using the computer program GUSAR 2013 (General Unrestricted Structure Activity Relationships), the quantitative relationship “structure - antioxidant activity (AOA)” was studied in a series of 64 benzopyran and benzofuran derivatives with the general structural formulas I - II. Nine statistically significant valid consensus models characterized by high prediction accuracy of the lgk7 parameter for the structures of training and test samples were constructed. AOA of the modeled compounds was in the range of values lgk7 = 0.00 ÷ 7.06. The descriptive and predictive ability of these models was evaluated on the structures of three training and two test samples with sliding controls with 20 times randomized exception of 20% of compounds. As statistical criteria for assessing the validity of the models M1-M9, the coefficients of determination (R20, Q2(F1), Q2(F2), , ССС) and the mean absolute error (MAE) were used. For their calculation, the XternalValidationPlus 1.2 program was used. This program showed the absence of a systematic error in the construction of all the regression dependencies M1-M9, which indicates the universality of the descriptors embedded n the GUSAR 2013 program, as well as the correctness of the regression models based on them. Thus, QSAR M1-M9 models can be successfully used for virtual screening of libraries and various databases in order to rationally search for potential antioxidants in them.

Keywords:
ANTIOXIDANT ACTIVITY, ANTIOXIDANTS, QSAR MODELING, GUSAR 2013 PROGRAM, MNA AND QNA DESCRIPTORS

Издатель: Башкирский государственный университет

Тип: Article

УДК: 544.165



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