Protein kinase inhibitors' classification using K-Nearest neighbor algorithm.

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 Chem

authors

Arian R,Hariri A,Mehridehnavi A,Fassihi A,Ghasemi F

doi

10.1016/j.compbiolchem.2020.107269

subject

Has Abstract

pub_date

2020-06-01 00:00:00

pages

107269

eissn

1476-9271

issn

1476-928X

pii

S1476-9271(19)30705-4

journal_volume

86

pub_type

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