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Tubulin Inhibitors: A Chemoinformatic Analysis Using Cell-Based Data.

Edgar López-López1,2, Carlos M Cerda-García-Rojas1, José L Medina-Franco2

  • 1Departamento de Química y Programa de Posgrado en Farmacología, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Apartado 14-740, Mexico City 07000, Mexico.

Molecules (Basel, Switzerland)
|April 30, 2021
PubMed
Summary
This summary is machine-generated.

This study analyzes 851 tubulin-microtubules (Tub-Mts) inhibitors, revealing a need for novel chemical scaffolds. Constellation plots identified promising new Tub-Mts inhibitor series for cancer treatment.

Keywords:
activity landscapeanalog seriescell-based assayschemical spacechemoinformaticsconstellation plotsdrug discoverymicrotubulesscaffoldstructure–property relationships

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Area of Science:

  • Medicinal Chemistry
  • Cancer Biology
  • Drug Discovery

Background:

  • Targeting the tubulin-microtubules (Tub-Mts) system is a validated strategy for cancer therapy.
  • Existing Tub-Mts inhibitors often rely on limited chemical scaffolds, hindering innovation.

Purpose of the Study:

  • To perform the first activity landscape and scaffold content analysis of Tub-Mts inhibitors.
  • To explore structure-bioactivity relationships using novel methodologies.

Main Methods:

  • Assembled and curated a cell-based database of 851 Tub-Mts inhibitors.
  • Utilized constellation plots for quantitative assessment of analog series.
  • Analyzed inhibitor activity against five cancer cell lines and the Tub-Mts system.

Main Results:

  • Characterized the activity landscape and scaffold diversity of Tub-Mts inhibitors.
  • Identified promising analog series with high average biological activity.
  • Constellation plots enabled rapid assessment of structure-bioactivity relationships.

Conclusions:

  • The study highlights limitations in current Tub-Mts inhibitor scaffolds.
  • Identified novel starting points for developing more potent anti-cancer agents.
  • The methodology provides a rapid quantitative assessment for drug discovery.