A global comparison of the human and T. brucei degradomes gives insights about possible parasite drug targets

Unveiling the peptidases of parasites from the office chair - The endothelin-converting enzyme case study

The emergence of high-throughput methodologies such as next-generation sequencing and proteomics has necessitated significant advancements in biological databases and bioinformatic tools, therefore reshaping the landscape of research into parasitic peptidases. In this review we outline the development of these resources along the -omics technologies and their transformative impact on the field. Apart from extensive summary of general and specific databases and tools, we provide a general pipeline on how to use these resources effectively to identify candidate peptidases from these large datasets and how to gain as much information about them as possible without leaving the office chair. This pipeline is then applied in an illustrative case study on the endothelin-converting enzyme 1 homologue from Schistosoma mansoni and attempts to highlight the contemporary capabilities of bioinformatics. The case study demonstrate how such approach can aid to hypothesize enzyme functions and interactions through computational analysis alone effectively and emphasizes how such virtual investigations can guide and optimize subsequent wet lab experiments therefore potentially saving precious time and resources. Finally, by showing what can be achieved without traditional wet laboratory methods, this review provides a compelling narrative on the use of bioinformatics to bridge the gap between big data and practical research applications, highlighting the key role of these technologies in furthering our understanding of parasitic diseases.

Genome-Wide Analysis of Haemonchus contortus Proteases and Protease Inhibitors Using Advanced Informatics Provides Insights into Parasite Biology and Host-Parasite Interactions

Biodiversity within the animal kingdom is associated with extensive molecular diversity. The expansion of genomic, transcriptomic and proteomic data sets for invertebrate groups and species with unique biological traits necessitates reliable in silico tools for the accurate identification and annotation of molecules and molecular groups. However, conventional tools are inadequate for lesser-known organismal groups, such as eukaryotic pathogens (parasites), so that improved approaches are urgently needed. Here, we established a combined sequence- and structure-based workflow system to harness well-curated publicly available data sets and resources to identify, classify and annotate proteases and protease inhibitors of a highly pathogenic parasitic roundworm (nematode) of global relevance, called Haemonchus contortus (barber's pole worm). This workflow performed markedly better than conventional, sequence-based classification and annotation alone and allowed the first genome-wide characterisation of protease and protease inhibitor genes and gene products in this worm. In total, we identified 790 genes encoding 860 proteases and protease inhibitors representing 83 gene families. The proteins inferred included 280 metallo-, 145 cysteine, 142 serine, 121 aspartic and 81 "mixed" proteases as well as 91 protease inhibitors, all of which had marked physicochemical diversity and inferred involvements in >400 biological processes or pathways. A detailed investigation revealed a remarkable expansion of some protease or inhibitor gene families, which are likely linked to parasitism (e.g., host-parasite interactions, immunomodulation and blood-feeding) and exhibit stage- or sex-specific transcription profiles. This investigation provides a solid foundation for detailed explorations of the structures and functions of proteases and protease inhibitors of H. contortus and related nematodes, and it could assist in the discovery of new drug or vaccine targets against infections or diseases.

High Throughput and Computational Repurposing for Neglected Diseases

Purpose

Neglected tropical diseases (NTDs) represent are a heterogeneous group of communicable diseases that are found within the poorest populations of the world. There are 23 NTDs that have been prioritized by the World Health Organization, which are endemic in 149 countries and affect more than 1.4 billion people, costing these developing economies billions of dollars annually. The NTDs result from four different causative pathogens: protozoa, bacteria, helminth and virus. The majority of the diseases lack effective treatments. Therefore, new therapeutics for NTDs are desperately needed.

Methods

We describe various high throughput screening and computational approaches that have been performed in recent years. We have collated the molecules identified in these studies and calculated molecular properties.

Results

Numerous global repurposing efforts have yielded some promising compounds for various neglected tropical diseases. These compounds when analyzed as one would expect appear drug-like. Several large datasets are also now in the public domain and this enables machine learning models to be constructed that then facilitate the discovery of new molecules for these pathogens.

Conclusions

In the space of a few years many groups have either performed experimental or computational repurposing high throughput screens against neglected diseases. These have identified compounds which in many cases are already approved drugs. Such approaches perhaps offer a more efficient way to develop treatments which are generally not a focus for global pharmaceutical companies because of the economics or the lack of a viable market. Other diseases could perhaps benefit from these repurposing approaches.

Electronic supplementary material

The online version of this article (10.1007/s11095-018-2558-3) contains supplementary material, which is available to authorized users.