Drug discovery and computational strategies in the multitarget drugs era

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.

New Roadmaps for Non-muscle-invasive Bladder Cancer With Unfavorable Prognosis

“…A multitarget drug can be considered as a key drug that opens multiple locks, able to inhibit multiple molecules within cascade signaling or within crosstalk pathways (de Oliveira Viana et al, 2018). Among multitarget modulators, epi-enzymes, histone deacetylases (HDACs), and DNA methyltransferase (DNMT) families represent the most studied drug targets for several cancer types (Benedetti et al, 2015;Lu et al, 2018).…”

Evaluation of the interaction between potent small molecules against the Nipah virus Glycoprotein in Malaysia and Bangladesh strains, accompanied by the human Ephrin-B2 and Ephrin-B3 receptors; a simulation approach

“…However, at the beginning of the 2000s, the concept of multi-target drugs made rapid and spectacular progress so nowadays multi-target drugs are already available on the market [ 24 ]. In the three mentioned articles, several Computer-Aided Drug Design (CADD) strategies including molecular docking, machine learning, molecular dynamic simulation, pharmacophore-based, structure–activity relationship (SAR), quantitative structure–activity relationship (QSAR), and combination methods were developed to facilitate the screening of new compounds with one-compound-multiple-target characteristics [ 25 , 26 , 27 ].…”

Computational Identification of Potential Multitarget Inhibitors of Nipah Virus by Molecular Docking and Molecular Dynamics

“…Multitarget drug discovery has raised considerable interest in the last decade [14][15][16][17]. Most drugs aim at a single biological molecule, widely known as the "one target, one drug" strategy, whereas a multitarget drug has the potential to modulate the effect of multiple targets.…”

“…Multitarget drugs have even been approved for clinical use [18], and many complex diseases, including neurodegenerative diseases, cardiovascular diseases, and cancers, are often treated with multidrug therapy or a "cocktail" of drugs [19]. Many computational approaches have been developed to address polypharmacology-guided drug discovery [16,20]; these approaches, including virtual screening, molecular docking, and molecular dynamics, have been widely implemented in modern drug discovery and are capable of screening new compounds with multitarget characteristics. For example, docking simulations have identified a series of novel multitarget compounds (e.g., donepezilindolyl hybrid, donepezil-pyridyl hybrid, donepezil hybrid, etc.)…”