Abstract:
:Protein kinases are enzymes acting as a source of phosphate through ATP to regulate protein biological activities by phosphorylating groups of specific amino acids. For that reason, inhibiting protein kinases with an active small molecule plays a significant role in cancer treatment. To achieve this aim, computational drug design, especially QSAR model, is one of the best economical approaches to reduce time and save in costs. In this respect, active inhibitors are attempted to be distinguished from inactive ones using hybrid QSAR model. Therefore, genetic algorithm and K-Nearest Neighbor method were suggested as a dimensional reduction and classification model, respectively. Finally, to evaluate the proposed model's performance, support vector machine and Naïve Bayesian algorithm were examined. The outputs of the proposed model demonstrated significant superiority to other QSAR models.
journal_name
Comput Biol Chemjournal_title
Computational biology and chemistryauthors
Arian R,Hariri A,Mehridehnavi A,Fassihi A,Ghasemi Fdoi
10.1016/j.compbiolchem.2020.107269subject
Has Abstractpub_date
2020-06-01 00:00:00pages
107269eissn
1476-9271issn
1476-928Xpii
S1476-9271(19)30705-4journal_volume
86pub_type
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