Combined 3D-QSAR, molecular docking and dynamics simulations studies to model and design TTK inhibitors

Noureen Ashraf; Asnuzilawati Asari; Numan Yousaf; Matloob Ahmad; Mahmood Ahmed; Amir Faisal; Muhammad Saleem; Muhammad Muddassar

doi:10.3389/fchem.2022.1003816

Combined 3D-QSAR, molecular docking and dynamics simulations studies to model and design TTK inhibitors

Front Chem. 2022 Nov 2:10:1003816. doi: 10.3389/fchem.2022.1003816. eCollection 2022.

Authors

Noureen Ashraf¹, Asnuzilawati Asari², Numan Yousaf¹, Matloob Ahmad³, Mahmood Ahmed⁴, Amir Faisal⁵, Muhammad Saleem⁶, Muhammad Muddassar¹

Affiliations

¹ Department of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan.
² Faculty of Science and Marine Environment, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia.
³ Department of Chemistry, Government College University, Faisalabad, Pakistan.
⁴ Department of Chemistry, Division of Science and Technology, University of Education, Lahore, Pakistan.
⁵ Department of Biology, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, Pakistan.
⁶ School of Biological Sciences, University of the Punjab, Lahore, Pakistan.

Abstract

Tyrosine threonine kinase (TTK) is the key component of the spindle assembly checkpoint (SAC) that ensures correct attachment of chromosomes to the mitotic spindle and thereby their precise segregation into daughter cells by phosphorylating specific substrate proteins. The overexpression of TTK has been associated with various human malignancies, including breast, colorectal and thyroid carcinomas. TTK has been validated as a target for drug development, and several TTK inhibitors have been discovered. In this study, ligand and structure-based alignment as well as various partial charge models were used to perform 3D-QSAR modelling on 1H-Pyrrolo[3,2-c] pyridine core containing reported inhibitors of TTK protein using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches to design better active compounds. Different statistical methods i.e., correlation coefficient of non-cross validation (r²), correlation coefficient of leave-one-out cross-validation (q²), Fisher's test (F) and bootstrapping were used to validate the developed models. Out of several charge models and alignment-based approaches, Merck Molecular Force Field (MMFF94) charges using structure-based alignment yielded highly predictive CoMFA (q² = 0.583, Predr² = 0.751) and CoMSIA (q² = 0.690, Predr² = 0.767) models. The models exhibited that electrostatic, steric, HBA, HBD, and hydrophobic fields play a key role in structure activity relationship of these compounds. Using the contour maps information of the best predictive model, new compounds were designed and docked at the TTK active site to predict their plausible binding modes. The structural stability of the TTK complexes with new compounds was confirmed using MD simulations. The simulation studies revealed that all compounds formed stable complexes. Similarly, MM/PBSA method based free energy calculations showed that these compounds bind with reasonably good affinity to the TTK protein. Overall molecular modelling results suggest that newly designed compounds can act as lead compounds for the optimization of TTK inhibitors.

Keywords: 3D-QSAR; MD simulations; MMPBSA; TTK inhibitors; molecular docking.