THEORETICAL MODELLING FOR INVESTIGATING SOME ACTIVE COMPOUNDS AS POTENT INHIBITORS AGAINST LUNG CANCER: A MULTI-LINEAR REGRESSION APPROACH

Autores

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

DOI:

https://doi.org/10.18540/jcecvl5iss1pp0125-0136

Palavras-chave:

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

Resumo

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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Biografia do Autor

Shola Elijah Adeniji, Ahmadu Bello University, Zaria, Nigeria

Shola Elijah Adeniji (corresponding author)

shola4343@gmail.com

Ahamadu Bello University, Zaria

Lecturer (reader)

Tukur Saidu

Tukur Saidu

saidutukur@gmail.com

Ahamadu Bello University, Zaria

Student

Ahanonu Saviour Ugochukwu

Ahanonu Saviour Ugochukwu

favour_saviour@yahoo.com

Ahamadu Bello University, Zaria

Student

Gideon Shallangwa

Gideon Shallangwa

shallangwa@gmail.com

Ahamadu Bello University, Zaria

Lecturer ( reader)

Adamu Uzairu

Adamu Uzairu 

adamuuzairu@yahoo.com

Ahamadu Bello University, Zaria

Professor

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Publicado

2019-03-08

Como Citar

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. https://doi.org/10.18540/jcecvl5iss1pp0125-0136

Edição

Seção

Physical Chemistry

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