Topoisomerase plays essential roles in cellular reproduction
and DNA organization by facilitating the cleavage of single and double stranded
DNA to relax supercoils, unwind catenanes, and condense chromosomes in
eukaryotic cells. These complexes are cytotoxic agents because the unrepaired
single and double stranded DNA breaks they produce may cause apoptosis and cell
death.
This work employs multiple linear regression, principal
component regression, and partial least squares to investigate the quantitative
structure-activity relationship (QSAR) of 28 compounds derived from
phosphorus-substituted quinoline. Evidence for the modeling was found in the
correlation between the anti-proliferative activity and several electronic and
structural properties of the molecules, including EHOMO (energy of the highest
occupied molecular orbital) and ELUMO (energy of the lowest unoccupied
molecular orbital).
These electronic properties were calculated using the
Density Functional Theory (DFT) approach at the B3LYP/6-31G (d, p) level of
theory. Principal Component Analysis (PCA) was utilized to test for
collinearity between the descriptors. Actually, using different counts of 2D
and 3D descriptors, three alternative prediction models were constructed, and
each one was evaluated using the statistical metrics of root mean square error
(RMSE) and coefficient of determination (R2). With an R2 of 0.865 and an RMSE
of 0.316, respectively, an MLR model demonstrated the highest predictive
performance of all the models that were built.
By using crystal structure modeling, three proteins (6G77,
2NS2, and 5K47) for lung, ovarian, and kidney cancers demonstrated strong
binding affinities via hydrophobic interactions and H-bonds with the relevant
chemicals. The compounds with the highest binding energies for lung, kidney,
and ovarian cancer were C11, C19, and C26, in that order. The molecular docking
results from previous studies, which showed that inhibitors were stable in the
active sites of the chosen proteins for 10 ns, were supported by the results of
the molecular dynamic MD simulation diagram. This suggests that these compounds
might be a useful model for creating and synthesizing novel, potent anticancer
compounds.
Author(s) Details:
Mouad Lahyaoui,
Faculty of Science and Technology, Laboratory of Applied Organic
Chemistry, Sidi Mohamed Ben Abdellah University, USMBA, P.O. Box 2626, Fez,
Morocco.
Riham
Sghyar,
Faculty
of Science and Technology, Laboratory of Applied Organic Chemistry, Sidi
Mohamed Ben Abdellah University, USMBA, P.O. Box 2626, Fez, Morocco.
Yousra Seqqat,
Faculty of Science and Technology, Laboratory of Applied Organic
Chemistry, Sidi Mohamed Ben Abdellah University, USMBA, P.O. Box 2626, Fez,
Morocco.
Mohamed El Yaqoubi,
Faculty of Science and Technology, Laboratory of Applied Organic
Chemistry, Sidi Mohamed Ben Abdellah University, USMBA, P.O. Box 2626, Fez,
Morocco.
Ahmed Mazzah,
University
of Lille, CNRS, USR 3290, MSAP, Miniaturization for Synthesis, Analysis and
Proteomics, Lille, France.
Amal
Haoudi,
Faculty
of Science and Technology, Laboratory of Applied Organic Chemistry, Sidi
Mohamed Ben Abdellah University, USMBA, P.O. Box 2626, Fez, Morocco.
Taoufiq Saffaj,
Faculty of Science and Technology, Laboratory of Applied Organic
Chemistry, Sidi Mohamed Ben Abdellah University, USMBA, P.O. Box 2626, Fez,
Morocco.
Youssef Kandri Rodi,
Faculty of Science and Technology, Laboratory of Applied Organic
Chemistry, Sidi Mohamed Ben Abdellah University, USMBA, P.O. Box 2626, Fez,
Morocco.
Please see the link here: https://stm.bookpi.org/CICMS-V8/article/view/14094
