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Complementary Quantitative Structure?Activity Relationship Models for the Antitrypanosomal Activity of Sesquiterpene Lactones.

ABSTRACT: Three complementary quantitative structure?activity relationship (QSAR) methodologies, namely, regression modeling based on (i) "classical" molecular descriptors, (ii) 3D pharmacophore features, and (iii) 2D molecular holograms (HQSAR) were employed on the antitrypanosomal activity of sesquiterpene lactones (STLs) toward Trypanosoma brucei rhodesiense (Tbr), the causative agent of the East African form of human African trypanosomiasis. In this study, an extension of a previous QSAR study on 69 STLs, models for a much larger and more diverse set of such natural products, now comprising 130 STLs of various structural subclasses, were established. The extended data set comprises a variety of STLs isolated and tested for antitrypanosomal activity within our group and is furthermore enhanced by 12 compounds obtained from literature, which have been tested in the same laboratory under identical conditions. Detailed QSAR analyses yielded models with comparable and good internal and external predictive ability. For a set of compounds as chemically diverse as the one under study, the models exhibited good coefficients of determination (R²) ranging from 0.71 to 0.85, as well as internal (leave-one-out Q² values ranging from 0.62 to 0.72) and external validation coefficients (P² values ranging from 0.54 to 0.73). The contributions of the various tested descriptors to the generated models are in good agreement with the results of previous QSAR studies and corroborate the fact that the antitrypanosomal activity of STLs is very much dependent on the presence and relative position of reactive enone groups within the molecular structure but is influenced by their hydrophilic/hydrophobic properties and molecular shape.

SUBMITTER: Kimani NM

PROVIDER: S-EPMC6321053 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Complementary Quantitative Structure⁻Activity Relationship Models for the Antitrypanosomal Activity of Sesquiterpene Lactones.

Kimani Njogu M NM Matasyoh Josphat C JC Kaiser Marcel M Nogueira Mauro S MS Trossini Gustavo H G GHG Schmidt Thomas J TJ

International journal of molecular sciences 20181122 12

Three complementary quantitative structure⁻activity relationship (QSAR) methodologies, namely, regression modeling based on (i) "classical" molecular descriptors, (ii) 3D pharmacophore features, and (iii) 2D molecular holograms (HQSAR) were employed on the antitrypanosomal activity of sesquiterpene lactones (STLs) toward <i>Trypanosoma brucei rhodesiense (Tbr)</i>, the causative agent of the East African form of human African trypanosomiasis. In this study, an extension of a previous QSAR study ...[more]

PMID: 30467296

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Project description:Human African trypanosomiasis (HAT), also commonly known as sleeping sickness, is a neglected tropical disease affecting millions of people in poorly developed regions in sub-Saharan Africa. There is no satisfactory treatment for this infection. The investment necessary to bring new drugs to the market is a big deterrent to drug development, considering that the affected communities form a non-lucrative sector. However, natural products and many sesquiterpene lactones (STLs) in particular are very strong trypanocides. Research and applications of nano-drug delivery systems such as nanoparticles (NPs) have undergone unprecedented growth in the recent past. This is mainly due to the advantages offered by these systems, such as targeted delivery of the drug to the place of action (cell, parasite, etc), sustained release of the drug, increased bioavailability, reduced drug dosage, and reduction of undesired side effects, among others. In this study, the STLs α-santonin, arglabin, schkuhrin II, vernolepin, and eucannabinolide, all trypanocides, were loaded into polylactic acid (PLA) NPs through an emulsification-diffusion method. The NPs were stable, homogenous, and spherical in shape with a rounded knotty depression like a navel orange. The average particle sizes were 202.3, 220.3, 219.5, 216.9, and 226.4 nm for α-santonin, arglabin, schkuhrin II, vernolepin, and eucannabinolide, respectively. The NPs had encapsulation efficiencies of 94.6, 78.1, 76.8, 60.7, and 78.9% for α-santonin, arglabin, schkuhrin II, vernolepin, and eucannabinolide, respectively. The NPs loaded with arglabin, vernolepin, and eucannabinolide exhibited considerable antitrypanosomal activity against Trypanosoma brucei rhodesiense (Tbr) with free drug equivalent IC50 values of 3.67, 1.11 and 3.32 µM, respectively. None of the NP formulations displayed cytotoxicity towards mammalian cells (rat skeletal myoblast cell line L6). These results provide new insights into the possibility of incorporating STLs into nanoparticles, which may provide new options for their formulation in order to develop new drugs against HAT.

Project description:BackgroundAlthough substantial concerns about the inflammatory effects of engineered nanomaterial (ENM) have been raised, experimentally assessing toxicity of various ENMs is challenging and time-consuming. Alternatively, quantitative structure-activity relationship (QSAR) models have been employed to assess nanosafety. However, no previous attempt has been made to predict the inflammatory potential of ENMs.ObjectivesBy employing metal oxide nanoparticles (MeONPs) as a model ENM, we aimed to develop QSAR models for prediction of the inflammatory potential by their physicochemical properties.MethodsWe built a comprehensive data set of 30 MeONPs to screen a proinflammatory cytokine interleukin (IL)-1 beta (IL-1β) release in THP-1 cell line. The in vitro hazard ranking was validated in mouse lungs by oropharyngeal instillation of six randomly selected MeONPs. We established QSAR models for prediction of MeONP-induced inflammatory potential via machine learning. The models were further validated against seven new MeONPs. Density functional theory (DFT) computations were exploited to decipher the key mechanisms driving inflammatory responses of MeONPs.ResultsSeventeen out of 30 MeONPs induced excess IL-1β production in THP-1 cells. In vivo disease outcomes were highly relevant to the in vitro data. QSAR models were developed for inflammatory potential, with predictive accuracy (ACC) exceeding 90%. The models were further validated experimentally against seven independent MeONPs (ACC=86%). DFT computations and experimental results further revealed the underlying mechanisms: MeONPs with metal electronegativity lower than 1.55 and positive ζ-potential were more likely to cause lysosomal damage and inflammation.ConclusionsIL-1β released in THP-1 cells can be an index to rank the inflammatory potential of MeONPs. QSAR models based on IL-1β were able to predict the inflammatory potential of MeONPs. Our approach overcame the challenge of time- and labor-consuming biological experiments and allowed for computational assessment of MeONP inflammatory potential by characterization of their physicochemical properties. https://doi.org/10.1289/EHP6508.

Dataset Information

Complementary Quantitative Structure?Activity Relationship Models for the Antitrypanosomal Activity of Sesquiterpene Lactones.

Publications

Complementary Quantitative Structure⁻Activity Relationship Models for the Antitrypanosomal Activity of Sesquiterpene Lactones.

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