DESIGN OF POTENT ANTICANCER MOLECULES COMPRISING PYRAZOLYL-THIAZOLINONE ANALOGS USING MOLECULAR MODELLING STUDIES FOR PHARMACOPHORE OPTIMIZATION

Kunal Raut; Sachin Kothawade; Vishal Pande; Sandesh Bole; SAMPADA NETANE; Kalyani Autade; Ashvini Joshi

doi:10.22159/ajpcr.2023.v16i8.47665

Authors

Kunal Raut Department of Pharmaceutical Chemistry, RSM’s N. N. Sattha College of Pharmacy, Ahmednagar, Maharashtra, India.
Sachin Kothawade Department of Pharmaceutics, RSM’s N. N. Sattha College of Pharmacy, Ahmednagar, Maharashtra, India.
Vishal Pande Department of Pharmaceutics, RSM’s N. N. Sattha College of Pharmacy, Ahmednagar, Maharashtra, India.
Sandesh Bole Department of Pharmaceutics, RSM’s N. N. Sattha College of Pharmacy, Ahmednagar, Maharashtra, India.
SAMPADA NETANE Department of Pharmaceutics, RSM’s N. N. Sattha College of Pharmacy, Ahmednagar, Maharashtra, India.
Kalyani Autade Department of Pharmacology, RSM’s N. N. Sattha College of Pharmacy, Ahmednagar, Maharashtra, India.
Ashvini Joshi Department of Pharmaceutical Chemistry, RSM’s N. N. Sattha College of Pharmacy, Ahmednagar, Maharashtra, India.

DOI:

https://doi.org/10.22159/ajpcr.2023.v16i8.47665

Keywords:

Molecular modeling, QSAR study, NCE, Docking, EGFR inhibitors, ADME

Abstract

Objectives: Numerous tiny receptor tyrosine kinase inhibitors have been reported as anticancer medications over the past 10 years. However, a lot of them lack effectiveness in vivo, selectivity, or do not last long before developing resistance.

Methods: We used molecular modeling research to improve the pharmacophore to get beyond these limitations. For the purpose of linking the chemical makeup of pyrazolyl thiazolinone analogs with their anticancer activity, quantitative structure activity relationship (QSAR) investigations in two dimensions (2D) and three dimensions (3D) were carried out. Pyrazolyl thiazolinone pharmacophore’s stearic, electronic, and hydrophobic requirements were calculated using 3D QSAR.

Results: By leveraging the findings of QSAR investigations, the pharmacophore was refined and new chemical entities (NCEs) were generated. The r2 and q2 values obtained for the best model No. 4 of 2D QSAR were 0.9244 and 0.8701, respectively. A drug-like pharmacokinetic profile was ensured by studying the binding affinities of proposed NCEs on epidermal growth factor receptor-TK using docking studies and estimating their absorption, distribution, metabolism, and excretion features.

Conclusion: When statistical significance is closely examined, predictability of the model and its residuals (actual activity minus predicted activity) is found to be close to zero, leading us to draw the conclusion that the logic behind the design of NCEs was determined to be sound.

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