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Neglected diseases, such as Chagas disease, African sleeping sickness, and intestinal worms, affect millions of the world's poor. They disproportionately affect marginalized populations, lack effective treatments or vaccines, or existing products are not accessible to the populations affected. Computational approaches have been used across many of these diseases for various aspects of research or development, and yet data produced by computational approaches are not integrated and widely accessible to others. Here, we identify gaps in which computational approaches have been used for some neglected diseases and not others. We also make recommendations for the broad-spectrum integration of these techniques into a neglected disease drug discovery and development workflow.

SummarySmall ubiquitin-related modifier (SUMO) is implicated in the regulation of numerous biological processes including transcription, protein localization, and cell cycle control. Protein modification by SUMO is found in Plasmodium falciparum; however, its role in the regulation of the parasite life cycle is poorly understood. Here we describe functional studies of a SUMO-specific protease (SENP) of P. falciparum, PfSENP1 (PFL1635w). Expression of the catalytic domain of PfSENP1 and biochemical profiling using a positional scanning substrate library demonstrated that this protease has unique cleavage sequence preference relative to the human SENPs. In addition, we describe a class of small molecule inhibitors of this protease. The most potent lead compound inhibited both recombinant PfSENP1 activity and P. falciparum replication in infected human blood. These studies provide valuable new tools for the study of SUMOylation in P. falciparum.

Background Chagas disease is a neglected tropical disease (NTD) caused by the eukaryotic parasite Trypanosoma cruzi. The current clinical and preclinical pipeline for T. cruzi is extremely sparse and lacks drug target diversity. Methodology/Principal Findings In the present study we developed a computational approach that utilized data from several public whole-cell, phenotypic high throughput screens that have been completed for T. cruzi by the Broad Institute, including a single screen of over 300,000 molecules in the search for chemical probes as part of the NIH Molecular Libraries program. We have also compiled and curated relevant biological and chemical compound screening data including (i) compounds and biological activity data from the literature, (ii) high throughput screening datasets, and (iii) predicted metabolites of T. cruzi metabolic pathways. This information was used to help us identify compounds and their potential targets. We have constructed a Pathway Genome Data Base for T. cruzi. In addition, we have developed Bayesian machine learning models that were used to virtually screen libraries of compounds. Ninety-seven compounds were selected for in vitro testing, and 11 of these were found to have EC50 < 10μM. We progressed five compounds to an in vivo mouse efficacy model of Chagas disease and validated that the machine learning model could identify in vitro active compounds not in the training set, as well as known positive controls. The antimalarial pyronaridine possessed 85.2% efficacy in the acute Chagas mouse model. We have also proposed potential targets (for future verification) for this compound based on structural similarity to known compounds with targets in T. cruzi. Conclusions/ Significance We have demonstrated how combining chemoinformatics and bioinformatics for T. cruzi drug discovery can bring interesting in vivo active molecules to light that may have been overlooked. The approach we have taken is broadly applicable to other NTDs., Author Summary Chagas disease is a neglected tropical disease (NTD) caused by the eukaryotic parasite Trypanosoma cruzi. The disease is endemic to Latin America but is increasingly found in North America and Europe, primarily through immigration, and the spread of this disease is bringing new attention to the need for novel, safe, and effective therapeutics to treat T. cruzi infection. We have used data from a phenotypic screen to build Bayesian models to predict anti-parasitic activity against T. cruzi in vitro. These models were used to score various small libraries of molecules. We selected less than 100 compounds for testing and found in vitro actives, some of which were tested in an in vivo efficacy model. We identified the antimalarial pyronaridine as having in vivo efficacy and provides us with a new starting point for further investigation and optimization.

SummaryThe Plasmodium proteasome has been suggested to be a potential antimalarial drug target; however, toxicity of inhibitors has prevented validation of this enzyme in vivo. We report a screen of a library of 670 analogs of the recent US Food and Drug Administration-approved inhibitor, carfilzomib, to identify compounds that selectively kill parasites. We identified one compound, PR3, that has significant parasite killing activity in vitro but dramatically reduced toxicity in host cells. We found that this parasite-specific toxicity is not due to selective targeting of the Plasmodium proteasome over the host proteasome, but instead is due to a lack of activity against one of the human proteasome subunits. Subsequently, we used PR3 to significantly reduce parasite load in Plasmodium berghei infected mice without host toxicity, thus validating the proteasome as a viable antimalarial drug target.

The need for new drugs and vaccines for neglected tropical diseases (NTDs) is widely accepted [1]. Yet, encouraging pharmaceutical and biotechnology company investment in developing these much-needed treatments remains a challenge due to a lack of a commercial market driving companies to pursue NTD projects [2]. To address this challenge, economists Ridley, Grabowski, and Moe at Duke University conceived of an incentive to encourage investment in the development of new drugs and vaccines for NTDs: the US Food and Drug Administration's (FDA) priority review voucher (PRV) program [3]. The program was signed into law on September 27, 2007 [4], and went into effect one year later. Under the program, the FDA awards a voucher to the sponsor of a newly approved drug or vaccine that targets an NTD (such as cholera or dengue) or malaria and tuberculosis (TB). The voucher, which can be traded or sold, entitles the holder to a 6-month priority review for a future new drug application that would not otherwise qualify for priority review—potentially shaving between 4 and 12 months from the standard FDA review process [5]. Since the program's inception, only one PRV has been awarded, to Novartis Pharmaceuticals Co. for their 2009 approval of the antimalarial drug Coartem. Novartis used the voucher to accelerate the review of one of its own products, rather than selling it on the marketplace. Because a product resulting from a PRV has not yet been sold in the marketplace, the value remains uncertain. Early economic models estimated that the worth of a PRV could range from US$50 million to US$500 million, with an average value of US$322 million, and a variation in value based on the therapeutic area for which it is used [5], [6]. Part of predicting the value relies on the supply and demand of vouchers; that is, will the number of vouchers awarded be absorbed by the blockbuster products that are likely to be the intended recipients of benefit from accelerated review? The lack of understanding as to how many PRVs may be awarded in the future limits companies from predicting the potential value of a voucher that might be earned. In the absence of a tangible example of a voucher's market value, companies, the FDA, policymakers, and other program stakeholders could benefit from examining NTD product pipelines, understanding when the next PRV(s) are expected to be issued, and ultimately quantifying the supply side of the PRV market. In addition, it is unclear to global health stakeholders whether companies are actively pursuing PRV-eligible products, and if they are, whether the PRV incentive has had an impact on their motivation [5], [6]. Here, we present an analysis of the drug and vaccine development pipeline to a) identify products that meet eligibility criteria to earn a PRV, and b) predict the number of PRVs that will be issued over the next 10 years. Of those products currently in clinical development, standard industry probabilities of success (POS) were applied to predict how many drugs and vaccines will ultimately earn regulatory approval, and therefore a PRV. Presumably, if stakeholders are armed with a supply forecast of the PRV market over the next decade, companies can conduct more informed calculations of value estimates, policymakers can assess whether the demand market for PRVs absorbs those vouchers being awarded, and the FDA can more accurately predict their expected workload increases when the PRVs are used.

Summary Sentrin specific proteases (SENPs) are responsible for activating and deconjugating SUMO (Small Ubiquitin-like MOdifier) from target proteins. It remains difficult to study this posttranslational modification due to the lack of reagents that can be used to block the removal of SUMO from substrates. Here, we describe the identification of small molecule SENP inhibitors and active site probes containing aza-epoxide and acyloxymethyl ketone (AOMK) reactive groups. Both classes of compounds are effective inhibitors of hSENPs 1, 2, 5, and 7 while only the AOMKs efficiently inhibit hSENP6. Unlike previous reported peptide vinyl sulfones, these compounds covalently labeled the active site cysteine of multiple recombinantly expressed SENP proteases and the AOMK probe showed selective labeling of these SENPs when added to complex protein mixtures. The AOMK compounds therefore represent promising new reagents to study the process of SUMO deconjugation.