Similarity-Based Virtual Screening to Find Antituberculosis Agents Based on Novel Scaffolds: Design, Syntheses and Pharmacological Assays

Abstract

A method to identify molecular scaffolds potentially active against the Mycobacterium tuberculosis complex (MTBC) is developed. A set of structurally heterogeneous agents against MTBC was used to obtain a mathematical model based on topological descriptors. This model was statistically validated through a Leave-n-Out test. It successfully discriminated between active or inactive compounds over 86% in database sets. It was also useful to select new potential antituberculosis compounds 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.

Keywords: MTBC; antimicrobial drugs; drug design; linear discriminant analysis; pharmacological activity distribution diagrams; topological indices; virtual screening.

Scheme 1

Cyclocondensation of α-acetylenic ketones A with 3-amino-5-benzylsulfanyl-1,2,4-triazole.

Figure 1

Proposed virtual screening procedure.

Figure 2

PDD in the training set, obtained by DF equation. E, expectancy of activity or inactivity; black line, active group; grey line, inactive group.

Figure 3

Structures of the selected compounds.

Scheme 2

Synthesis of protected 1,2,4-triazolo[1,5-a]pyrimidine derivatives 6.

Scheme 3

Deprotection of 6b to give 7.

Scheme 4

O-alkylation of 2-alkylsulfanylpyrimidinones 8.

Scheme 5

Oxidation of 9 to the corresponding sulfone 10, nucleophilic displacement to produce the corresponding pyrimidines 11, and displacement of the 4-isopropoxy group of 11a to yield 2-aryloxypyrimidinone 12.

Scheme 6

Petasis reaction of the amine 9e to give α-phenyl glycine derivative 13.

Scheme 7

Reduction of 9d to obtain the hydroxy derivative 14.