Rational Computational Study for New Kinase Inhibitors

Joao Eustaquio Antunes,Michelle Bueno De Moura Pereira

doi:10.11648/j.jddmc.20190503.12

Abstract

The development of new drugs can present several problems, it is a important obstacle the ability to adapt a molecule that is a potent pharmacological inhibitor and that is also possible to execute its synthesis. Quinazolines are known to be capable of inhibiting kinases. Thus, a detailed study was carried out to propose new quinazolines with already known synthetic routes, and that were promising for the ability to inhibit kinases. A drug candidate molecule shall be proposed to have a good absorption, an extensive distribution so it’s capable of reaching the desired therapeutic targets. Lipinski's Rule of 5 in computational studies has been applied to select more promising molecules. In this study, the molecules proposed for the synthesis were systematically designed in appropriate computational programs to test several substituents of the quinazoline nucleus on the capacity of these molecules to be considered inhibitors of kinases. Six molecules were selected with the best results to inhibit kinases. In the study to evaluate the variation of substituents, the result obtained for the 8-position of the quinazoline ring and with the -Cl substituent at that ring position presented 60% of the 10 best molecules capable of inhibiting kinases. The molecular docking study confirmed that the two most promising molecules to inhibit kinase also obtained the best results to inhibit AKT kinase. Therefore, through this study it was possible to select six more promising molecules to be synthesized and available in large screening tests for several therapeutic targets known as High-Throughput Screening.

Highlights

In the development of new drugs it’s possible to find several problems, and an important obstacle is to adapt a molecule that is potent, that is, capable of inhibiting a certain target and that it is capable of having known synthetic routes and possibility of execution [1]
Computational studies can help if drug candidate molecules have good pharmacokinetic parameters [4]
Molecular docking studies allow us to evaluate if certain molecules have the capacity to inhibit their molecular targets [5], so, this computational tool corroborates the selection of more promising molecules

Summary

Introduction

In the development of new drugs it’s possible to find several problems, and an important obstacle is to adapt a molecule that is potent, that is, capable of inhibiting a certain target and that it is capable of having known synthetic routes and possibility of execution [1]. A drug candidate molecule must be proposed to have a good absorption, an extensive distribution, so it’s capable of reaching the desired target and so it’s not toxic [2]. These molecules must be able to have their synthesis executed. Previous computational studies can be performed to select molecules with good pharmacokinetic parameters [3], high biological activity and have a possibility of being synthesized. In this context, computational studies can help if drug candidate molecules have good pharmacokinetic parameters [4]. Kinases are promising targets for various types of cancer and other diseases [6], some molecules capable of inhibiting kinases may be considered promising in studies for the discovery and development of new drugs

Methods

Results

Conclusion