Molecular docking-based classification and systematic QSAR analysis of indoles as Pim kinase inhibitors

ABSTRACT

Pim kinase enzyme has an essential role in the treatment of prostate, colon and acute myeloid leukaemia cancers. The indoles inhibitors were docked in the enzyme’s active pocket in order to survey the inhibition mechanism and extract the ligands’ conformations. The docking outcome shows that the active inhibitors have strong van der Waals interactions with residues of Ile185, Leu44, Leu120 and Leu174, hydrogen bonds with residues of Asp128, Arg122 and Glu171 and π-π interaction with the residue of Phe49. The sum of these interactions is ~80 kcal mol⁻¹ contributing ~90% of total binding free energies. Using docking-based molecular descriptors, the unsupervised and supervised classifications were successfully carried out with the accuracy of 0.82 and 0.95, respectively, to categorize the active/inactive Pim kinase inhibitors. The vigorous quantitative assessment was performed using different machine learning techniques. The constructed QSAR model [(r²_cal, r²_p, r²_m and Q²_LOO) > 0.80 and (SE_cal, SE_p and SE_LOO) < 0.22] indicates that the molecular descriptors of nN, RDF20v and E1v can describe both the inhibition activities and the inhibition mechanism. The adequate evaluations of the molecular docking, classifications and QSAR analysis show that the current approaches can be used as valuable tools to design more effective new Pim kinase inhibitors for cancer treatment.

KEYWORDS:

• Pim kinase enzyme
• QSAR
• docking based descriptors
• adaptive neuro fuzzy inference system
• discriminant analysis

Acknowledgements

We are grateful for the support from the Research Council of Babol Noshirvani University of Technology.

Disclosure statement

The authors confirm that this article content has no conflict of interest.