Atom based QSAR approach for the design of novel purine analogues for the inhibition of serine threonine kinases

An approach towards design of novel antiproliferative agents

Venkatesh Kamath, Aravinda Pai

Research output: Contribution to journalArticle

Abstract

A robust and reliable 3D QSAR model which is pharmacophore based has been developed in the present study, based on reported sequence of purine analogues for the inhibition of serine threonine class of cancer drug target. The present model showed statistical significance with regression coefficient value of r2 = 0.98 and cross validation coefficient values of q2 = 0.7725. The model was validated by allocating the compounds under two sets, namely, test and training set. The latter was made use to build model of QSAR whereas, the test was to endorse the QSAR model that was developed. Also the model showed a huge F value 654.7 and Pearson coefficient value of 0.8812, suggesting the accuracy of the model. The developed model could be utilized to develop selective inhibitors which are also novel, for serine threonine class of cancer drug targets.

Original languageEnglish
Pages (from-to)2086-2091
Number of pages6
JournalLatin American Journal of Pharmacy
Volume37
Issue number10
Publication statusPublished - 01-01-2018

Fingerprint

Quantitative Structure-Activity Relationship
Protein-Serine-Threonine Kinases
Threonine
Serine
Statistical Models
Pharmaceutical Preparations
Neoplasms
purine

All Science Journal Classification (ASJC) codes

  • Pharmaceutical Science
  • Drug Discovery

Cite this

@article{6719cba7fbc84ba7ac2b5442a37d85fe,
title = "Atom based QSAR approach for the design of novel purine analogues for the inhibition of serine threonine kinases: An approach towards design of novel antiproliferative agents",
abstract = "A robust and reliable 3D QSAR model which is pharmacophore based has been developed in the present study, based on reported sequence of purine analogues for the inhibition of serine threonine class of cancer drug target. The present model showed statistical significance with regression coefficient value of r2 = 0.98 and cross validation coefficient values of q2 = 0.7725. The model was validated by allocating the compounds under two sets, namely, test and training set. The latter was made use to build model of QSAR whereas, the test was to endorse the QSAR model that was developed. Also the model showed a huge F value 654.7 and Pearson coefficient value of 0.8812, suggesting the accuracy of the model. The developed model could be utilized to develop selective inhibitors which are also novel, for serine threonine class of cancer drug targets.",
author = "Venkatesh Kamath and Aravinda Pai",
year = "2018",
month = "1",
day = "1",
language = "English",
volume = "37",
pages = "2086--2091",
journal = "Latin American Journal of Pharmacy",
issn = "0326-2383",
publisher = "Colegio de Farmaceuticos de la Provincia de Buenos Aires",
number = "10",

}

TY - JOUR

T1 - Atom based QSAR approach for the design of novel purine analogues for the inhibition of serine threonine kinases

T2 - An approach towards design of novel antiproliferative agents

AU - Kamath, Venkatesh

AU - Pai, Aravinda

PY - 2018/1/1

Y1 - 2018/1/1

N2 - A robust and reliable 3D QSAR model which is pharmacophore based has been developed in the present study, based on reported sequence of purine analogues for the inhibition of serine threonine class of cancer drug target. The present model showed statistical significance with regression coefficient value of r2 = 0.98 and cross validation coefficient values of q2 = 0.7725. The model was validated by allocating the compounds under two sets, namely, test and training set. The latter was made use to build model of QSAR whereas, the test was to endorse the QSAR model that was developed. Also the model showed a huge F value 654.7 and Pearson coefficient value of 0.8812, suggesting the accuracy of the model. The developed model could be utilized to develop selective inhibitors which are also novel, for serine threonine class of cancer drug targets.

AB - A robust and reliable 3D QSAR model which is pharmacophore based has been developed in the present study, based on reported sequence of purine analogues for the inhibition of serine threonine class of cancer drug target. The present model showed statistical significance with regression coefficient value of r2 = 0.98 and cross validation coefficient values of q2 = 0.7725. The model was validated by allocating the compounds under two sets, namely, test and training set. The latter was made use to build model of QSAR whereas, the test was to endorse the QSAR model that was developed. Also the model showed a huge F value 654.7 and Pearson coefficient value of 0.8812, suggesting the accuracy of the model. The developed model could be utilized to develop selective inhibitors which are also novel, for serine threonine class of cancer drug targets.

UR - http://www.scopus.com/inward/record.url?scp=85055573163&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85055573163&partnerID=8YFLogxK

M3 - Article

VL - 37

SP - 2086

EP - 2091

JO - Latin American Journal of Pharmacy

JF - Latin American Journal of Pharmacy

SN - 0326-2383

IS - 10

ER -