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هشتمین سمینار دوسالانه کمومتریکس ایران
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Comparing the performance of PLS, GA-PLS, and OSC-GA-PLS models for QSAR Study of Inhibitory Activity of Pyrazolone Derivatives and Design of New Compounds Using Image Processing |
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| چکیده انگلیسی مقاله |
Nowadaya,Pyrazolone and its derivatives have gained a lot of attention due to their biological and medicinal applications. These compounds have antimicrobial, antifungal and anticancer properties. Therefore, using simple methods to prepare these compounds is of importance. Pyrazolone is one of the inhibitors of kinase domain containing receptor KDR or VEGFR-2. In this study, quantitative structure-activity relationship (QSAR) analysis was used to predict the inhibitory activity of new pyrazolone derivatives. Bi-dimensional images were used to calculate pixels for QSAR modeling. Furthermore, the partial least squares (PLS) was used to establish a relationship between IC50 dependent variables and independent variables, i.e., pixels or hidden variables. In addition, genetic algorithm (GA) was used in PLS method (GA-PLS) to select the descriptors. In this method, the variables selected to form the calibration model had negligible errors with acceptable characteristics. Pre-processing methods such as orthogonal signal correction (OSC) were also used to provide a suitable input for modeling as well as to improve the results of the GA (OSC-GA-PLS). Finally, root mean squared error of prediction (RMSEP) was used to assess the performance of the models for predicting the pIC50 of the studied compounds, the value of which was obtained equal to 0.3, 0.22, and 0.19 for PLS, GA-PLS and OSC-GA-PLS models, respectively. Furthermore, the proposed QSAR model was developed with the OSC-GA-PLS method to predict the inhibitory activity of the new compounds. |
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| کلیدواژه‌های انگلیسی مقاله |
Quantitative structure-activity relationship، Orthogonal signal correction ، Genetic Algorithms، Partial least squares، Pyrazolone. |
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| نویسندگان مقاله |
| mitra mirshafiei
| Ail Niazi
تهران مرکز
| Ateesa یزدانی پور
تهران مرکز
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| نشانی اینترنتی |
http://chemo2021.modares.ac.ir/browse.php?a_code=A-10-187-1&slc_lang=fa&sid=1 |
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| زبان مقاله منتشر شده |
fa |
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