TB Research

Similarity-based Virtual Screening to Find Antituberculosis Agents based on Novel Scaffolds

Ángela García-García, Jesus Vicente de Julián‐Ortiz, Jorge Gálvez, David García Font, Carles Ayats, María del Remedio Guna Serrano, Carlos Muñoz-Collado, Rafael Borrás, et al. (9 authors)

Preprints.org · 2022-09

Abstract

A method is developed to identify molecular scaffolds potentially active against the Mycobacterium tuberculosis complex (MTBC). A structurally heterogeneous set of compounds active against MTBC was used to obtain a structural pattern model based on structural invariants. This model was statistically validated through a Leave-n-Out test. It successfully discriminated between active or inactive compounds over 86% in database sets and was also able to select new active chemical structures in external databases. The selection of new substituted pyrimidines, pyrimidones and triazolo[1,5-a]pyrimidines was particularly interesting because these structures could provide new scaffolds in this field. The seven selected candidates were synthesized and six of them showed activity in vitro.

MeSH terms

  • Virtual screening
  • Selection (genetic algorithm)
  • Mycobacterium tuberculosis
  • Computational biology
  • Similarity (geometry)
  • Set (abstract data type)
  • Computer science
  • Combinatorial chemistry
  • Chemistry
  • Database
  • Tuberculosis
  • Stereochemistry