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      Chalcone Derivatives: Promising Starting Points for Drug Design

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          Abstract

          Medicinal chemists continue to be fascinated by chalcone derivatives because of their simple chemistry, ease of hydrogen atom manipulation, straightforward synthesis, and a variety of promising biological activities. However, chalcones have still not garnered deserved attention, especially considering their high potential as chemical sources for designing and developing new effective drugs. In this review, we summarize current methodological developments towards the design and synthesis of new chalcone derivatives and state-of-the-art medicinal chemistry strategies (bioisosterism, molecular hybridization, and pro-drug design). We also highlight the applicability of computer-assisted drug design approaches to chalcones and address how this may contribute to optimizing research outputs and lead to more successful and cost-effective drug discovery endeavors. Lastly, we present successful examples of the use of chalcones and suggest possible solutions to existing limitations.

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          Most cited references139

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          The Chemscore function was implemented as a scoring function for the protein-ligand docking program GOLD, and its performance compared to the original Goldscore function and two consensus docking protocols, "Goldscore-CS" and "Chemscore-GS," in terms of docking accuracy, prediction of binding affinities, and speed. In the "Goldscore-CS" protocol, dockings produced with the Goldscore function are scored and ranked with the Chemscore function; in the "Chemscore-GS" protocol, dockings produced with the Chemscore function are scored and ranked with the Goldscore function. Comparisons were made for a "clean" set of 224 protein-ligand complexes, and for two subsets of this set, one for which the ligands are "drug-like," the other for which they are "fragment-like." For "drug-like" and "fragment-like" ligands, the docking accuracies obtained with Chemscore and Goldscore functions are similar. For larger ligands, Goldscore gives superior results. Docking with the Chemscore function is up to three times faster than docking with the Goldscore function. Both combined docking protocols give significant improvements in docking accuracy over the use of the Goldscore or Chemscore function alone. "Goldscore-CS" gives success rates of up to 81% (top-ranked GOLD solution within 2.0 A of the experimental binding mode) for the "clean list," but at the cost of long search times. For most virtual screening applications, "Chemscore-GS" seems optimal; search settings that give docking speeds of around 0.25-1.3 min/compound have success rates of about 78% for "drug-like" compounds and 85% for "fragment-like" compounds. In terms of producing binding energy estimates, the Goldscore function appears to perform better than the Chemscore function and the two consensus protocols, particularly for faster search settings. Even at docking speeds of around 1-2 min/compound, the Goldscore function predicts binding energies with a standard deviation of approximately 10.5 kJ/mol. Copyright 2003 Wiley-Liss, Inc.
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                Author and article information

                Journal
                Molecules
                Molecules
                molecules
                Molecules : A Journal of Synthetic Chemistry and Natural Product Chemistry
                MDPI
                1420-3049
                25 July 2017
                August 2017
                : 22
                : 8
                : 1210
                Affiliations
                [1 ]Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Universidade Federal de Goiás, Setor Leste Universitário, Goiânia 74605-510, Brazil; marcelo13farma@ 123456yahoo.com.br (M.N.G.); andradech@ 123456yahoo.com (C.H.A.)
                [2 ]Laboratory for Molecular Modeling, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27955-7568, USA; murik@ 123456email.unc.edu
                [3 ]Laboratório de Biologia Molecular, Instituto de Ciências Biológicas, Universidade Federal de Goiás, Goiânia 74001-970, Brazil; maristelaufg@ 123456gmail.com
                [4 ]Programa de Pós-Graduação em Sociedade, Tecnologia e Meio Ambiente, Centro Universitário de Anápolis—UniEVANGÉLICA, Anápolis 75083-515, Brazil; josana.peixoto@ 123456gmail.com (J.C.P.); lucimar.pinheiro@ 123456yahoo.com.br (L.P.R.); pedrovcravo@ 123456gmail.com (P.V.L.C.)
                [5 ]GHTM/Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, 1349-008 Lisboa, Portugal
                Author notes
                Article
                molecules-22-01210
                10.3390/molecules22081210
                6152227
                28757583
                1cf8a789-d0a6-4ba3-bb1a-0993fa5f202b
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 June 2017
                : 14 July 2017
                Categories
                Review

                natural products,chalcone derivatives,chalcone synthesis,molecular modification strategies,computer-assisted drug design

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