Literature DB >> 28582669

QSAR-driven design, synthesis and discovery of potent chalcone derivatives with antitubercular activity.

Marcelo N Gomes1, Rodolpho C Braga1, Edyta M Grzelak2, Bruno J Neves3, Eugene Muratov4, Rui Ma2, Larry L Klein2, Sanghyun Cho2, Guilherme R Oliveira5, Scott G Franzblau6, Carolina Horta Andrade7.   

Abstract

New anti-tuberculosis (anti-TB) drugs are urgently needed to battle drug-resistant Mycobacterium tuberculosis strains and to shorten the current 6-12-month treatment regimen. In this work, we have continued the efforts to develop chalcone-based anti-TB compounds by using an in silico design and QSAR-driven approach. Initially, we developed SAR rules and binary QSAR models using literature data for targeted design of new heteroaryl chalcone compounds with anti-TB activity. Using these models, we prioritized 33 compounds for synthesis and biological evaluation. As a result, 10 heteroaryl chalcone compounds (4, 8, 9, 11, 13, 17-20, and 23) were found to exhibit nanomolar activity against replicating mycobacteria, low micromolar activity against nonreplicating bacteria, and nanomolar and micromolar against rifampin (RMP) and isoniazid (INH) monoresistant strains (rRMP and rINH) (<1 μM and <10 μM, respectively). The series also show low activity against commensal bacteria and generally show good selectivity toward M. tuberculosis, with very low cytotoxicity against Vero cells (SI = 11-545). Our results suggest that our designed heteroaryl chalcone compounds, due to their high potency and selectivity, are promising anti-TB agents.
Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Anti-TB agents; Chalcone; In silico design; Nitroaromatic compounds; QSAR; Tuberculosis

Mesh:

Substances:

Year:  2017        PMID: 28582669      PMCID: PMC6031314          DOI: 10.1016/j.ejmech.2017.05.026

Source DB:  PubMed          Journal:  Eur J Med Chem        ISSN: 0223-5234            Impact factor:   6.514


  70 in total

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Journal:  Biol Pharm Bull       Date:  2007-01       Impact factor: 2.233

2.  New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays.

Authors:  Jonathan B Baell; Georgina A Holloway
Journal:  J Med Chem       Date:  2010-04-08       Impact factor: 7.446

Review 3.  New tuberculosis drugs on the horizon.

Authors:  Stewart T Cole; Giovanna Riccardi
Journal:  Curr Opin Microbiol       Date:  2011-08-05       Impact factor: 7.934

4.  In silico machine learning methods in drug development.

Authors:  Dimitar A Dobchev; Girinath G Pillai; Mati Karelson
Journal:  Curr Top Med Chem       Date:  2014       Impact factor: 3.295

Review 5.  Virtual screening strategies in medicinal chemistry: the state of the art and current challenges.

Authors:  Rodolpho C Braga; Vinicius M Alves; Arthur C Silva; Marilia N Nascimento; Flavia C Silva; Luciano M Liao; Carolina H Andrade
Journal:  Curr Top Med Chem       Date:  2014       Impact factor: 3.295

6.  In vitro and in vivo activities of macrolide derivatives against Mycobacterium tuberculosis.

Authors:  Kanakeshwari Falzari; Zhaohai Zhu; Dahua Pan; Huiwen Liu; Poonpilas Hongmanee; Scott G Franzblau
Journal:  Antimicrob Agents Chemother       Date:  2005-04       Impact factor: 5.191

7.  Synthesis, antitubercular evaluation and 3D-QSAR study of N-phenyl-3-(4-fluorophenyl)-4-substituted pyrazole derivatives.

Authors:  R C Khunt; V M Khedkar; R S Chawda; N A Chauhan; A R Parikh; E C Coutinho
Journal:  Bioorg Med Chem Lett       Date:  2011-10-30       Impact factor: 2.823

8.  Rational design of 5-phenyl-3-isoxazolecarboxylic acid ethyl esters as growth inhibitors of Mycobacterium tuberculosis. a potent and selective series for further drug development.

Authors:  Annamaria Lilienkampf; Marco Pieroni; Baojie Wan; Yuehong Wang; Scott G Franzblau; Alan P Kozikowski
Journal:  J Med Chem       Date:  2010-01-28       Impact factor: 7.446

9.  Evaluation of chalcones--a flavonoid subclass, for, their anxiolytic effects in rats using elevated plus maze and open field behaviour tests.

Authors:  Huma Jamal; Wajid Hussain Ansari; Shamim Jahan Rizvi
Journal:  Fundam Clin Pharmacol       Date:  2008-12       Impact factor: 2.748

10.  Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.

Authors:  Cristina Ventura; Diogo A R S Latino; Filomena Martins
Journal:  Eur J Med Chem       Date:  2013-10-23       Impact factor: 6.514

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  19 in total

1.  Chalcones as a basis for computer-aided drug design: innovative approaches to tackle malaria.

Authors:  Marilia Nn Lima; Bruno J Neves; Gustavo C Cassiano; Marcelo N Gomes; Kaira Cp Tomaz; Leticia T Ferreira; Tatyana A Tavella; Juliana Calit; Daniel Y Bargieri; Eugene N Muratov; Fabio Tm Costa; Carolina Horta Andrade
Journal:  Future Med Chem       Date:  2019-09-26       Impact factor: 3.808

2.  Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.

Authors:  Thomas Lane; Daniel P Russo; Kimberley M Zorn; Alex M Clark; Alexandru Korotcov; Valery Tkachenko; Robert C Reynolds; Alexander L Perryman; Joel S Freundlich; Sean Ekins
Journal:  Mol Pharm       Date:  2018-04-26       Impact factor: 4.939

3.  Sensitive fluorescent chemosensor for Hg(II) in aqueous solution using 4'-dimethylaminochalcone.

Authors:  Marco Mellado; Nicole Roldán; Rodrigo Miranda; Luis F Aguilar; Manuel A Bravo; Waldo Quiroz
Journal:  J Fluoresc       Date:  2022-04-20       Impact factor: 2.525

4.  Computer-aided discovery of two novel chalcone-like compounds active and selective against Leishmania infantum.

Authors:  Marcelo N Gomes; Laura M Alcântara; Bruno J Neves; Cleber C Melo-Filho; Lucio H Freitas-Junior; Carolina B Moraes; Rui Ma; Scott G Franzblau; Eugene Muratov; Carolina Horta Andrade
Journal:  Bioorg Med Chem Lett       Date:  2017-04-04       Impact factor: 2.823

5.  QSAR-Based Virtual Screening: Advances and Applications in Drug Discovery.

Authors:  Bruno J Neves; Rodolpho C Braga; Cleber C Melo-Filho; José Teófilo Moreira-Filho; Eugene N Muratov; Carolina Horta Andrade
Journal:  Front Pharmacol       Date:  2018-11-13       Impact factor: 5.810

Review 6.  Chalcone Derivatives: Promising Starting Points for Drug Design.

Authors:  Marcelo N Gomes; Eugene N Muratov; Maristela Pereira; Josana C Peixoto; Lucimar P Rosseto; Pedro V L Cravo; Carolina H Andrade; Bruno J Neves
Journal:  Molecules       Date:  2017-07-25       Impact factor: 4.411

7.  Pre-clinical evaluation of quinoxaline-derived chalcones in tuberculosis.

Authors:  Thaís C Muradás; Bruno L Abbadi; Anne D Villela; Fernanda S Macchi; Pedro F Bergo; Talita F de Freitas; Nathalia D M Sperotto; Luis F S M Timmers; Osmar Norberto de Souza; Jaqueline N Picada; Jean Fachini; Juliana Bondan da Silva; Nayara C P de Albuquerque; Maísa D Habenschus; Daniel B Carrão; Bruno A Rocha; Fernando Barbosa Junior; Anderson R M de Oliveira; Alessandra Mascarello; Patrícia Neuenfeldf; Ricardo J Nunes; Héctor R Morbidoni; Maria M Campos; Luiz A Basso; Valnês S Rodrigues-Junior
Journal:  PLoS One       Date:  2018-08-16       Impact factor: 3.240

8.  QSAR-Driven Design and Discovery of Novel Compounds With Antiplasmodial and Transmission Blocking Activities.

Authors:  Marilia N N Lima; Cleber C Melo-Filho; Gustavo C Cassiano; Bruno J Neves; Vinicius M Alves; Rodolpho C Braga; Pedro V L Cravo; Eugene N Muratov; Juliana Calit; Daniel Y Bargieri; Fabio T M Costa; Carolina H Andrade
Journal:  Front Pharmacol       Date:  2018-03-06       Impact factor: 5.810

9.  Network-based piecewise linear regression for QSAR modelling.

Authors:  Jonathan Cardoso-Silva; Lazaros G Papageorgiou; Sophia Tsoka
Journal:  J Comput Aided Mol Des       Date:  2019-10-18       Impact factor: 3.686

10.  Deep Learning-driven research for drug discovery: Tackling Malaria.

Authors:  Bruno J Neves; Rodolpho C Braga; Vinicius M Alves; Marília N N Lima; Gustavo C Cassiano; Eugene N Muratov; Fabio T M Costa; Carolina Horta Andrade
Journal:  PLoS Comput Biol       Date:  2020-02-18       Impact factor: 4.475

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