Year 2019, Volume 3, Issue 1, Pages 38 - 46 2019-06-15

MULTIVARIANT QSAR MODEL FOR SOME POTENT COMPOUNDS AS POTENTIAL ANTI-TUMOR INHIBITORS: A COMPUTATIONAL APPROACH

SHOLA ELIJAH [1] , Sani UBA [2] , Adamu UZAIRU [3]

47 91

ABSTRACT

A computational approach was employed to develop multivariate QSAR model to correlate the chemical structures of the ciprofloxacin analogues with their observed activities using a theoretical approach. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were used to select the descriptors and to generate the correlation QSAR models that relate the activity values against tumor with the molecular structures of the active molecules. The models were validated and the best model selected has squared correlation coefficient (R2) of 0.990531, adjusted squared correlation coefficient (Radj) of 0.95962 and Leave one out (LOO) cross validation coefficient () value of 0.942963. The external validation set used for confirming the predictive power of the model has its R2pred of 0.8486. Stability and robustness of the model obtained by the validation test indicate that the model can be used to design and synthesis other ciprofloxacin derivatives with improved anti-tumor activity.

Keywords: Ciprofloxacin, Descriptors, Genetic Function Algorithm, tumor
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Primary Language en
Journal Section Research Article
Authors

Author: SHOLA ELIJAH (Primary Author)
Country: Turkey


Author: Sani UBA

Author: Adamu UZAIRU

Dates

Publication Date: June 15, 2019

Bibtex @research article { tcandtc458664, journal = {Turkish Computational and Theoretical Chemistry}, issn = {2587-1722}, eissn = {2602-3237}, address = {Koray SAYIN}, year = {2019}, volume = {3}, pages = {38 - 46}, doi = {10.33435/tcandtc.458664}, title = {MULTIVARIANT QSAR MODEL FOR SOME POTENT COMPOUNDS AS POTENTIAL ANTI-TUMOR INHIBITORS: A COMPUTATIONAL APPROACH}, key = {cite}, author = {ELIJAH, SHOLA and UBA, Sani and UZAIRU, Adamu} }
APA ELIJAH, S , UBA, S , UZAIRU, A . (2019). MULTIVARIANT QSAR MODEL FOR SOME POTENT COMPOUNDS AS POTENTIAL ANTI-TUMOR INHIBITORS: A COMPUTATIONAL APPROACH. Turkish Computational and Theoretical Chemistry, 3 (1), 38-46. DOI: 10.33435/tcandtc.458664
MLA ELIJAH, S , UBA, S , UZAIRU, A . "MULTIVARIANT QSAR MODEL FOR SOME POTENT COMPOUNDS AS POTENTIAL ANTI-TUMOR INHIBITORS: A COMPUTATIONAL APPROACH". Turkish Computational and Theoretical Chemistry 3 (2019): 38-46 <http://dergipark.org.tr/tcandtc/issue/42698/458664>
Chicago ELIJAH, S , UBA, S , UZAIRU, A . "MULTIVARIANT QSAR MODEL FOR SOME POTENT COMPOUNDS AS POTENTIAL ANTI-TUMOR INHIBITORS: A COMPUTATIONAL APPROACH". Turkish Computational and Theoretical Chemistry 3 (2019): 38-46
RIS TY - JOUR T1 - MULTIVARIANT QSAR MODEL FOR SOME POTENT COMPOUNDS AS POTENTIAL ANTI-TUMOR INHIBITORS: A COMPUTATIONAL APPROACH AU - SHOLA ELIJAH , Sani UBA , Adamu UZAIRU Y1 - 2019 PY - 2019 N1 - doi: 10.33435/tcandtc.458664 DO - 10.33435/tcandtc.458664 T2 - Turkish Computational and Theoretical Chemistry JF - Journal JO - JOR SP - 38 EP - 46 VL - 3 IS - 1 SN - 2587-1722-2602-3237 M3 - doi: 10.33435/tcandtc.458664 UR - https://doi.org/10.33435/tcandtc.458664 Y2 - 2018 ER -
EndNote %0 Turkish Computational and Theoretical Chemistry MULTIVARIANT QSAR MODEL FOR SOME POTENT COMPOUNDS AS POTENTIAL ANTI-TUMOR INHIBITORS: A COMPUTATIONAL APPROACH %A SHOLA ELIJAH , Sani UBA , Adamu UZAIRU %T MULTIVARIANT QSAR MODEL FOR SOME POTENT COMPOUNDS AS POTENTIAL ANTI-TUMOR INHIBITORS: A COMPUTATIONAL APPROACH %D 2019 %J Turkish Computational and Theoretical Chemistry %P 2587-1722-2602-3237 %V 3 %N 1 %R doi: 10.33435/tcandtc.458664 %U 10.33435/tcandtc.458664
ISNAD ELIJAH, SHOLA , UBA, Sani , UZAIRU, Adamu . "MULTIVARIANT QSAR MODEL FOR SOME POTENT COMPOUNDS AS POTENTIAL ANTI-TUMOR INHIBITORS: A COMPUTATIONAL APPROACH". Turkish Computational and Theoretical Chemistry 3 / 1 (June 2019): 38-46. https://doi.org/10.33435/tcandtc.458664
AMA ELIJAH S , UBA S , UZAIRU A . MULTIVARIANT QSAR MODEL FOR SOME POTENT COMPOUNDS AS POTENTIAL ANTI-TUMOR INHIBITORS: A COMPUTATIONAL APPROACH. Turkish Comp Theo Chem (TC&TC). 2019; 3(1): 38-46.
Vancouver ELIJAH S , UBA S , UZAIRU A . MULTIVARIANT QSAR MODEL FOR SOME POTENT COMPOUNDS AS POTENTIAL ANTI-TUMOR INHIBITORS: A COMPUTATIONAL APPROACH. Turkish Computational and Theoretical Chemistry. 2019; 3(1): 46-38.