4.5 Article

In silico design of novel quinazoline-based compounds as potential Mycobacterium tuberculosis PknB inhibitors through 2D and 3D-QSAR, molecular dynamics simulations combined with pharmacokinetic predictions

Journal

JOURNAL OF MOLECULAR GRAPHICS & MODELLING
Volume 115, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jmgm.2022.108231

Keywords

Tuberculosis; PknB inhibitors; HQSAR; 3D-QSAR CoMSIA; Binding energy; MD simulations

Funding

  1. Thailand Research Fund [RSA5980057]
  2. Thailand Graduate Institute of Science and Technology (TGIST) [SCA-CO-2560-4375TH]
  3. center of excellence for innovation in chemistry (PERCH-CIC), Faculty of Science, Ubon Ratchathani University, Faculty of Science, Nakhon Phanom University, Faculty of Science, Kasetsart University
  4. University of Bristol
  5. UK EPSRC [EP/M027546/1]
  6. CCP-BioSim [EP/M022609/1]
  7. National Electronics and Computer Technology Center (NECTEC)
  8. National Nanotechnology Center (NANOTEC)

Ask authors/readers for more resources

This study used quantitative structure-activity relationship methods to investigate the inhibitory effects of quinazoline derivatives on PknB. Molecular dynamics simulations and binding energy calculations revealed that the quinazoline core and overall hydrophobicity were major contributors to the affinity of PknB. Additional quinazoline derivatives were designed and evaluated, and predictive models identified sixteen compounds with superior PknB binding and other desirable properties.
Serine/threonine protein kinase B (PknB) is essential to Mycobacterium tuberculosis (M. tuberculosis) cell division and metabolism and a potential anti-tuberculosis drug target. Here we apply Hologram Quantitative Structure Activity Relationship (HQSAR) and three-dimensional QSAR (Comparative Molecular Similarity Indices Analysis (CoMSIA)) methods to investigate structural requirements for PknB inhibition by a series of previously described quinazoline derivatives. PknB binding of quinazolines was evaluated by molecular dynamics (MD) simulations of the catalytic domain and binding energies calculated by Molecular Mechanics/Poisson Boltzmann Surface Area (MM-PBSA) and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) methods. Evaluation of a training set against experimental data showed both HQSAR and CoMSIA models to reliably predict quinazoline binding to PknB, and identified the quinazoline core and overall hydrophobicity as the major contributors to affinity. Calculated binding energies also agreed with experiment, and MD simulations identified hydrogen bonds to Glu93 and Val95, and hydrophobic interactions with Gly18, Phe19, Gly20, Val25, Thr99 and Met155, as crucial to PknB binding. Based on these results, additional quinazolines were designed and evaluated in silico, with HQSAR and CoMSIA models identifying sixteen compounds, with predicted PknB binding superior to the template, whose activity spectra and physicochemical, pharmacokinetic, and anti -M. tuberculosis properties were assessed. Compound, D060, bearing additional ortho- and meta-methyl groups on its R2 substituent, was superior to template regarding PknB inhibition and % caseum fraction unbound, and equivalent in other aspects, although predictions identified hepatotoxicity as a likely issue with the quinazoline series. These data provide a structural basis for rational design of quinazoline derivatives with more potent PknB inhibitory activity as candidate antituberculosis agents.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available