Literature DB >> 33736292

Identification of novel αβ-tubulin modulators with antiproliferative activity directed to cancer therapy using ligand and structure-based virtual screening.

Leonardo Bruno Federico1, Guilherme Martins Silva2, Amanda de Fraga Dias3, Fabrício Figueiró4, Ana Maria Oliveira Battastini3, Cleydson Breno Rodrigues Dos Santos5, Luciano T Costa6, Joaquín Maria Carmpos Rosa7, Carlos Henrique Tomich de Paula da Silva8.   

Abstract

Among several strategies related to cancer therapy targeting the modulation of αβ-tubulin has shown encouraging findings, more specifically when this is achieved by inhibitors located at the colchicine binding site. In this work, we aim to fish new αβ-tubulin modulators through a diverse and rational VS study, and thus, exhibiting the development of two VS pipelines. This allowed us to identify two compounds 5 and 9 that showed IC50 values of 19.69 and 21.97 μM, respectively, towards possible modulation of αβ-tubulin, such as assessed by in vitro assays in C6 glioma and HEPG2 cell lines. We also evaluated possible mechanisms of action of obtained hits towards the colchicine binding site of αβ-tubulin by using docking approaches. In addition, assessment of the stability of the active (5 and 9) and inactive compounds (3 and 13) within the colchicine binding site was carried out by molecular dynamics (MD) simulations, highlighting the solvent effect and revealing the compound 5 as the most stable in the complex. At last, deep analysis of these results provided some valuable insights on the importance of using mixed ligand- and structure-based strategies in VS campaigns, in order to achieve higher chemical diversity and biological effect as well.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  ADME/Tox; Antiproliferative activity; Cancer; Docking; Ligand-based drug design; Tubulin modulators; Virtual screening

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Year:  2020        PMID: 33736292     DOI: 10.1016/j.ijbiomac.2020.10.136

Source DB:  PubMed          Journal:  Int J Biol Macromol        ISSN: 0141-8130            Impact factor:   6.953


  1 in total

1.  A two-layer mono-objective algorithm based on guided optimization to reduce the computational cost in virtual screening.

Authors:  Miriam R Ferrández; Savíns Puertas-Martín; Juana L Redondo; Horacio Pérez-Sánchez; Pilar M Ortigosa
Journal:  Sci Rep       Date:  2022-07-27       Impact factor: 4.996

  1 in total

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