• Shola Elijah Adeniji Ahmadu Bello University, Zaria, Nigeria
  • Momohjimoh Idris Ovaku
  • Tukur Saidu
  • Ahanonu Saviour Ugochukwu
  • Gideon Shallangwa
  • Adamu Uzairu



Ciprofloxacin, Descriptor, Genetic Function Approximation, Lung Cancer, QSAR.


A Quantitative Structure Activity Relationship (QSAR) study has been attempted on ciprofloxacin derivatives as potent anti-lung cancer. QSAR models were derived with the aid of multi-linear regression (MLR) approach using topological, molecular shape, electronic and structural descriptors. The predictive ability of the QSAR models generated  were validated and the best model selected has squared correlation coefficient (R2) of 0.954801, adjusted squared correlation coefficient (Radj) of 0.939265, Leave one out (LOO) cross validation coefficient () value of 0.907523. The external validation set used for confirming the predictive power of the model has its R2pred of 0.8387. The QSAR models point out that AATSC2m, VR3_Dzp and BIC2 are the important descriptors effectively describing the bioactivity of these compounds.


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Author Biographies

Shola Elijah Adeniji, Ahmadu Bello University, Zaria, Nigeria

Shola Elijah Adeniji (corresponding author)

Ahamadu Bello University, Zaria

Lecturer (reader)

Tukur Saidu

Tukur Saidu

Ahamadu Bello University, Zaria


Ahanonu Saviour Ugochukwu

Ahanonu Saviour Ugochukwu

Ahamadu Bello University, Zaria


Gideon Shallangwa

Gideon Shallangwa

Ahamadu Bello University, Zaria

Lecturer ( reader)

Adamu Uzairu

Adamu Uzairu

Ahamadu Bello University, Zaria



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How to Cite

Adeniji, S. E., Ovaku, M. I., Saidu, T., Ugochukwu, A. S., Shallangwa, G., & Uzairu, A. (2019). THEORETICAL MODELLING FOR INVESTIGATING SOME ACTIVE COMPOUNDS AS POTENT INHIBITORS AGAINST LUNG CANCER: A MULTI-LINEAR REGRESSION APPROACH. The Journal of Engineering and Exact Sciences, 5(1), 0125–0136.



Physical Chemistry

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