Leukotrienes Target F-actin/Cofilin-1 to Enhance Alveolar Macrophage Anti-fungal Activity

Candida albicans is the most common opportunistic fungal pathogen and causes local and systemic disease in immunocompromised patients. Alveolar macrophages (AMs) are pivotal for the clearance of C. albicans from the lung. Activated AMs secrete 5-lipoxygenase-derived leukotrienes (LTs), which in turn enhance phagocytosis and microbicidal activity against a diverse array of pathogens. Our aim was to investigate the role of LTB(4) and LTD(4) in AM antimicrobial functions against C. albicans and the signaling pathways involved. Pharmacologic and genetic inhibition of LT biosynthesis as well as receptor antagonism reduced phagocytosis of C. albicans when compared with untreated or WT controls. Conversely, exogenous LTs of both classes augmented base-line C. albicans phagocytosis by AMs. Although LTB(4) enhanced mainly mannose receptor-dependent fungal ingestion, LTD(4) enhanced mainly dectin-1 receptor-mediated phagocytosis. LT enhancement of yeast ingestion was dependent on protein kinase C-delta (PKC delta) and PI3K but not PKC alpha and MAPK activation. Both LTs reduced activation of cofilin-1, whereas they enhanced total cellular F-actin; however, LTB(4) accomplished this through the activation of LIM kinases (LIMKs) 1 and 2, whereas LTD(4) did so exclusively via LIMK-2. Finally, both exogenous LTB(4) and LTD(4) enhanced AM fungicidal activity in an NADPH oxidase-dependent manner. Our data identify LTB(4) and LTD(4) as key mediators of innate immunity against C. albicans, which act by both distinct and conserved signaling mechanisms to enhance multiple antimicrobial functions of AMs.

Integration of Ligand- and Target-Based Virtual Screening for the Discovery of Cruzain Inhibitors

A myriad of methods are available for virtual screening of small organic compound databases. In this study we have successfully applied a quantitative model of consensus measurements, using a combination of 3D similarity searches (ROCS and EON), Hologram Quantitative Structure Activity Relationships (HQSAR) and docking (FRED, FlexX, Glide and AutoDock Vina), to retrieve cruzain inhibitors from collected databases. All methods were assessed individually and then combined in a Ligand-Based Virtual Screening (LBVS) and Target-Based Virtual Screening (TBVS) consensus scoring, using Receiving Operating Characteristic (ROC) curves to evaluate their performance. Three consensus strategies were used: scaled-rank-by-number, rank-by-rank and rank-by-vote, with the most thriving the scaled-rank-by-number strategy, considering that the stiff ROC curve appeared to be satisfactory in every way to indicate a higher enrichment power at early retrieval of active compounds from the database. The ligand-based method provided access to a robust and predictive HQSAR model that was developed to show superior discrimination between active and inactive compounds, which was also better than ROCS and EON procedures. Overall, the integration of fast computational techniques based on ligand and target structures resulted in a more efficient retrieval of cruzain inhibitors with desired pharmacological profiles that may be useful to advance the discovery of new trypanocidal agents.