Planta Med 2013; 79 - PG7
DOI: 10.1055/s-0033-1352077

Fast virtual screening of sesquiterpene lactones from Asteraceae with potential antileishmanial activity

MT Scotti 1, MS da Silva 2, IR Pitta 3, A Speck-Planche 4, L Scotti 1
  • 1Departamento de Engenharia e Meio Ambiente, Universidade Federal da Paraíba, Campus IV, 58297 – 000, Rio Tinto, PB, Brazil.
  • 2Laboratório de Tecnologia Farmacêutica, Universidade Federal da Paraíba, Campus I, 50740 – 540, João Pessoa, PB, Brazil
  • 3Departamento de Antibióticos, Universidade Federal de Pernambuco, 50670 – 910, Recife, PE, Brazil
  • 4Deparment of Chemistry and Biochemistry, University of Porto, 4169 – 007 Porto, Portugal.

Leishmanioses is a human tropical parasitic disease that causes approximately 50,000 death cases annually. Secondary metabolites play an important role to propose new active lead structures, and studies highlights antiprotozoal activities of sesquiterpene lactones (SLs)1. In view of this, we performed a virtual screening (VS) in an in-house databank of 1328 SLs of Asteraceae, corresponding to 2323 botanical occurrences (B.O. – number of times that a compound appears in different species) using fragment descriptors and Randon Forest (RF). We select from CHEMBL database a diversity set of 269 compounds, which were screened against L. donovani amastigotes (MHOM/ET/67/L82) to generate a RF model and were classified using -logIC50 (mol/L)= pIC50 values, being active (> 5) and inactive (< 4.5) and, between 4.5 and 5 were excluded to reduce border effect between both classes. DRAGON v. 6.0 generated descriptors, which with constant and near constant values, standard deviation < 10-4, and pair correlation ≥0.90 were excluded. The 148 remaining descriptors and class variable were exported to Knime 2.7.2 that was used to perform all analysis process described hereinafter. Data were divided in train and test set and only 7 variables were selected by backward feature elimination method. RFs were generated using WEKA nodes. Table 1 summarizes match rates of RF of 269 compounds of CHEMBL database. RF selected 476 SLs (658 B.O.) with potential activity which are present mainly in Senecioneae and Eupatorieae tribes. The VS, that is part of the activities of ResNetNPND (http://www.uni-muenster.de/ResNetNPND/), is rapid and can be applied to larger natural products databases.

Tab. 1: Summary of match rates.

Train

Validation a

Test

Samples

Match

%Match

Match

%Match

Samples

Match

%Match

Active

97

95

97.8

78

80.4

24

22

91.7

Inactive

118

116

98.3

101

85.6

30

23

76.7

Overall

215

211

98.1

179

83.3

54

45

83.3

a – cross-validation (10 stratified groups)

References:

[1] Schmidt J, et al. Curr. Top. Med., 2012, 19, 2128 – 2175.