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Search for: general-structure-activity-relationships
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    Navigating drug-like chemical space of anticancer molecules using genetic algorithms and counterpropagation artificial neural networks

    , Article Molecular Informatics ; Volume 31, Issue 1 , JAN , 2012 , Pages 63-74 ; 18681743 (ISSN) Jalali Heravi, M ; Mani Varnosfaderani, A ; Sharif University of Technology
    2012
    Abstract
    A total of 6289 drug-like anticancer molecules were collected from Binding database and were analyzed by using the classification techniques. The collected molecules were encoded to a diverse set of descriptors, spanning different physical and chemical properties of the molecules. A combination of genetic algorithms and counterpropagation artificial neural networks was used for navigating the generated drug-like chemical space and selecting the most relevant molecular descriptors. The proposed method was used for the classification of the molecules according to their therapeutic targets and activities. The selected molecular descriptors in this work define discrete areas in chemical space,... 

    Classification of anti-HIV compounds using counterpropagation artificial neural networks and decision trees

    , Article SAR and QSAR in Environmental Research ; Volume 22, Issue 7-8 , Oct , 2011 , Pages 639-660 ; 1062936X (ISSN) Jalali Heravi, M ; Mani Varnosfaderani, A ; Eftekhar Jahromi, P ; Mohsen Mahmoodi, M ; Taherinia, D ; Sharif University of Technology
    2011
    Abstract
    The main aim of the present work was to collect and categorize anti-HIV molecules in order to identify general structure-activity relationships. In this respect, a total of 5580 drugs and drug-like molecules was collected from 256 different articles published between 1992 and 2010. An algorithm called genetic algorithm-pattern search counterpropagation artificial neural networks (GPS-CPANN) was proposed for the classification of compounds. In addition, the CART (classification and regression trees) method was used for construction of decision trees and finding the best molecular descriptors. The results revealed that the developed CPANN models and decision tree can correctly classify the...