Linear Regression QSAR Models for Polo-Like Kinase-1 Inhibitors

نویسنده

  • Pablo R. Duchowicz
چکیده

A structurally diverse dataset of 530 polo-like kinase-1 (PLK1) inhibitors is compiled from the ChEMBL database and studied by means of a conformation-independent quantitative structure-activity relationship (QSAR) approach. A large number (26,761) of molecular descriptors are explored with the main intention of capturing the most relevant structural characteristics affecting the bioactivity. The structural descriptors are derived with different freeware, such as PaDEL, Mold², and QuBiLs-MAS; such descriptor software complements each other and improves the QSAR results. The best multivariable linear regression models are found with the replacement method variable subset selection technique. The balanced subsets method partitions the dataset into training, validation, and test sets. It is found that the proposed linear QSAR model improves previously reported models by leading to a simpler alternative structure-activity relationship.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

2D-QSAR and docking studies of 4-anilinoquinazoline derivatives as epidermal growth factor receptor tyrosine kinase inhibitors

Introduction: Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor derivatives play an important role in the treatment of cancer. We aim to construct 2D-QSAR models using various chemometrics using 4-anilinoquinazoline-containing EGFR TKIs. In addition, the binding profile of these compounds was evaluated using a docking study. Materials and Methods: In this study, 122 compounds of...

متن کامل

A comparative QSAR study of aryl-substituted isobenzofuran-1(3H)-ones inhibitors

A comparative workflow, including linear and non-linear QSAR models, was carried out to evaluate the predictive accuracy of models and predict the inhibition activity of a series of aryl-substituted isobenzofuran-1(3H)-ones. The data set consisted of 34 compounds was classified into the training and test sets, randomly. Molecular descriptors were selected using the genetic algorithm (GA) as a f...

متن کامل

Combined Pharmacophore Modeling, Docking, and 3D-QSAR Studies of PLK1 Inhibitors

Polo-like kinase 1, an important enzyme with diverse biological actions in cell mitosis, is a promising target for developing novel anticancer drugs. A combined molecular docking, structure-based pharmacophore modeling and three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed on a set of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as PLK1 inhibit...

متن کامل

3D-QSAR and docking analysis on a series of multi-cyclin-dependent kinase inhibitors using CoMFA, and CoMSIA

A series of 42 Pyrazolo[4,3-h]quinazoline-3-carboxamides as multi-cyclin-dependent kinaseinhibitors regarded as promising antitumor agents to complement the existing therapies, wassubjected to a three-dimensional quantitative activity relationship (3D QSAR). Different QSARmethods, comparative molecular field analysis (CoMFA), CoMFA region focusing, andcomparative molecular similarity indices an...

متن کامل

QSAR Modeling of COX-2 Inhibitory Activity of Some Dihydropyridine and Hydroquinoline Derivatives Using Multiple Linear Regression (MLR) Method

COX-2 inhibitory activities of some 1,4-dihydropyridine and 5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives were modeled by quantitative structure–activity relationship (QSAR) using stepwise-multiple linear regression (SW-MLR) method. The built model was robust and predictive with correlation coefficient (R2) of 0.972 and 0.531 for training and test groups, respectively. The quality of the mod...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 7  شماره 

صفحات  -

تاریخ انتشار 2018