In silico repositioning of approved drugs against Schistosoma mansoni energy metabolism targets

Schistosoma mansoni α-N-acetylgalactosaminidase (SmNAGAL) regulates coordinated parasite movement and egg production

α-galactosidase (α-GAL) and α-N-acetylgalactosaminidase (α-NAGAL) are two glycosyl hydrolases responsible for maintaining cellular homeostasis by regulating glycan substrates on proteins and lipids. Mutations in the human genes encoding either enzyme lead to neurological and neuromuscular impairments seen in both Fabry- and Schindler/Kanzaki- diseases. Here, we investigate whether the parasitic blood fluke Schistosoma mansoni, responsible for the neglected tropical disease schistosomiasis, also contains functionally important α-GAL and α-NAGAL proteins. As infection, parasite maturation and host interactions are all governed by carefully-regulated glycosylation processes, inhibiting S. mansoni's α-GAL and α-NAGAL activities could lead to the development of novel chemotherapeutics. Sequence and phylogenetic analyses of putative α-GAL/α-NAGAL protein types showed Smp_089290 to be the only S. mansoni protein to contain the functional amino acid residues necessary for α-GAL/α-NAGAL substrate cleavage. Both α-GAL and α-NAGAL enzymatic activities were higher in females compared to males (p<0.05; α-NAGAL > α-GAL), which was consistent with smp_089290's female biased expression. Spatial localisation of smp_089290 revealed accumulation in parenchymal cells, neuronal cells, and the vitellaria and mature vitellocytes of the adult schistosome. siRNA-mediated knockdown (>90%) of smp_089290 in adult worms significantly inhibited α-NAGAL activity when compared to control worms (siLuc treated males, p<0.01; siLuc treated females, p<0.05). No significant reductions in α-GAL activities were observed in the same extracts. Despite this, decreases in α-NAGAL activities correlated with a significant inhibition in adult worm motility as well as in egg production. Programmed CRISPR/Cas9 editing of smp_089290 in adult worms confirmed the egg reduction phenotype. Based on these results, Smp_089290 was determined to act predominantly as an α-NAGAL (hereafter termed SmNAGAL) in schistosome parasites where it participates in coordinating movement and oviposition processes. Further characterisation of SmNAGAL and other functionally important glycosyl hydrolases may lead to the development of a novel anthelmintic class of compounds.

Proteins as Targets in Anti-Schistosomal Drug Discovery and Vaccine Development

Proteins hardly function in isolation; they form complexes with other proteins or molecules to mediate cell signaling and control cellular processes in various organisms. Protein interactions control mechanisms that lead to normal and/or disease states. The use of competitive small molecule inhibitors to disrupt disease-relevant protein-protein interactions (PPIs) holds great promise for the development of new drugs. Schistosome invasion of the human host involves a variety of cross-species protein interactions. The pathogen expresses specific proteins that not only facilitate the breach of physical and biochemical barriers present in skin, but also evade the immune system and digestion of human hemoglobin, allowing for survival in the host for years. However, only a small number of specific protein interactions between the host and parasite have been functionally characterized; thus, in-depth understanding of the molecular mechanisms of these interactions is a key component in the development of new treatment methods. Efforts are now focused on developing a schistosomiasis vaccine, as a proposed better strategy used either alone or in combination with Praziquantel to control and eliminate this disease. This review will highlight protein interactions in schistosomes that can be targeted by specific PPI inhibitors for the design of an alternative treatment to Praziquantel.

InContext: curation of medical context for drug indications

Accurate and precise information about the therapeutic uses (indications) of a drug is essential for applications in drug repurposing and precision medicine. Leading online drug resources such as DrugCentral and DrugBank provide rich information about various properties of drugs, including their indications. However, because indications in such databases are often partly automatically mined, some may prove to be inaccurate or imprecise. Particularly challenging for text mining methods is the task of distinguishing between general disease mentions in drug product labels and actual indications for the drug. For this, the qualifying medical context of the disease mentions in the text should be studied. Some examples include contraindications, co-prescribed drugs and target patient qualifications. No existing indication curation efforts attempt to capture such information in a precise way. Here we fill this gap by presenting a novel curation protocol for extracting indications and machine processable annotations of contextual information about the therapeutic use of a drug. We implemented the protocol on a reference set of FDA-approved drug product labels on the DailyMed website to curate indications for 150 anti-cancer and cardiovascular drugs. The resulting corpus - InContext - focuses on anti-cancer and cardiovascular drugs because of the heightened societal interest in cancer and heart disease. In order to understand how InContext relates with existing reputable drug indication databases, we analysed it’s overlap with a state-of-the-art indications database - LabeledIn - as well as a reputable online drug compendium - DrugCentral. We found that 40% of indications sampled from DrugCentral (and 23% from LabeledIn) respectively, could not be accounted for in InContext. This raises questions about the veracity of indications not appearing in InContext. The additional contextual information curated by InContext about disease mentions in drug SPLs provides a foundation for more precise, structured and formal representations of knowledge related to drug therapeutic use, in order to increase accuracy and agreement of drug indication extraction methods for in silico drug repurposing.