Drug discovery and computational strategies in the multitarget drugs era

Jéssika de Oliveira Viana,Mayara dos Santos Maia,Marcus Tullius Scotti,Mayara Barbalho Félix,Vanessa de Lima Serafim,Luciana Scotti

doi:10.1590/s2175-97902018000001010

Jéssika de Oliveira Viana, Mayara dos Santos Maia + Show 4 more

Open Access

https://doi.org/10.1590/s2175-97902018000001010

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Abstract

The pharmaceutical industry is increasingly joining chemoinformatics in the search for the development of new drugs to be used in the treatment of diseases. These computational studies have the advantage of being less expensive and optimize the study time, and thus the interest in this area is increasing. Among the techniques used is the development of multitarget directed ligands (MTDLs), which has become an ascending technique, mainly due to the improvement in the quality of treatment involving several drugs. Multitarget therapy is more effective than traditional drug therapy that emphasizes maximum selectivity for a single target. In this review a multitarget drug survey was carried out as a promising strategy in several important diseases: neglected diseases, neurodegenerative diseases, AIDS, and cancer. In addition, we discuss Computer-Aided Drug Design (CADD) techniques as a tool in the projection of multitarget compounds against these diseases.

Highlights

According to the definition of Richard Morphy, the multitarget drugs are defined as compounds that are designed to modulate multiple targets of relevance to a disease, with the overall goal of enhancing efficacy and/ or improving safety (Morphy, Rankovic, 2005).The multitarget drug is a key that can open multiple locks
We presented a way to identify and even design inhibitors that couple to multiple targets in an efficient way, which determines the importance of this study, since the drugs used in the therapy concentrate, in the majority, on the inhibition of only a single target
We present the structure-based virtual screening (SBVS) using GLIDE (Friesner et al, 2004, Halgren et al, 2004, Friesner et al, 2006) and ligand-based virtual classification through quantitative structure-activity relationship (QSAR) 4D that accurately describes and quantifies important structural aspects involved in mutant drug interactions (Paul et al, 2016)

Summary

Introduction

According to the definition of Richard Morphy, the multitarget drugs are defined as compounds that are designed to modulate multiple targets of relevance to a disease, with the overall goal of enhancing efficacy and/ or improving safety (Morphy, Rankovic, 2005).The multitarget drug is a key that can open multiple locks. It should be noted that only one part of the molecule can interact with each of the proposed targets, and the other part may become an obstacle to the binding event, reducing binding action due to enteric and entropybased approaches In this way, to include some degree of flexibility in the molecule can help the pharmacological characteristics, taking care that there is not an excess of flexibility, interfering negatively in the binding affinity (due to the unfavorable entropic loss associated with the binding event) or the bioavailability of the drug (Jayaraman et al, 2013), being these critical factors to be reflected in the planning of these compounds (Decker, 2007; Ramsay et al, 2018)

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