A Kernel for Open Source Drug Discovery in Tropical Diseases

Open source drug discovery, a promising alternative avenue to conventional patent-based drug development, has so far remained elusive with few exceptions. A major stumbling block has been the absence of a critical mass of preexisting work that volunteers can improve through a series of granular contributions. This paper introduces the results from a newly assembled computational pipeline for identifying protein targets for drug discovery in ten organisms that cause tropical diseases. We have also experimentally tested two promising targets for their binding to commercially available drugs, validating one and invalidating the other. The resulting kernel provides a base of drug targets and lead candidates around which an open source community can nucleate. We invite readers to donate their judgment and in silico and in vitro experiments to develop these targets to the point where drug optimization can begin

Production of heparanase constructs suitable for nuclear magnetic resonance and drug discovery studies

Heparanase is an endo-β-D-glucosidase capable of specifically degrading heparan sulphate, one of the main components of the extracellular matrix. This 65 kDa polypeptide is implicated in cancer processes such as tumour formation, angiogenesis and metastasis, making it a very attractive target in antitumour treatments. Structure-based approaches to find inhibitors of heparanase have been historically hampered by the lack of success in crystallizing the protein. With the aim to undertake the NMR structural characterisation of heparanase, we have designed and produced, using recombinant methods, smaller constructs of heparanase containing the catalytically active glutamic acids and the two binding sites for heparan sulphate. An extensive range of expression and purification conditions were evaluated to alleviate the intrinsic low solubility and aggregation propensity of heparanase, allowing the obtention of the enzyme in milligram quantities, both unlabelled and ¹⁵N-labelled for NMR studies. Using the smallest of the designed constructs and applying NMR and SPR methodologies, we have demonstrated that known inhibitors of heparanase bind to this construct specifically and selectively with K(D) values in the range of those reported for human heparanase, validating it for future drug discovery projects focused on the identification of novel inhibitors of this enzyme

A kernel for open source drug discovery in tropical diseases.

BackgroundConventional patent-based drug development incentives work badly for the developing world, where commercial markets are usually small to non-existent. For this reason, the past decade has seen extensive experimentation with alternative R&D institutions ranging from private-public partnerships to development prizes. Despite extensive discussion, however, one of the most promising avenues-open source drug discovery-has remained elusive. We argue that the stumbling block has been the absence of a critical mass of preexisting work that volunteers can improve through a series of granular contributions. Historically, open source software collaborations have almost never succeeded without such "kernels".Methodology/principal findingsHERE, WE USE A COMPUTATIONAL PIPELINE FOR: (i) comparative structure modeling of target proteins, (ii) predicting the localization of ligand binding sites on their surfaces, and (iii) assessing the similarity of the predicted ligands to known drugs. Our kernel currently contains 143 and 297 protein targets from ten pathogen genomes that are predicted to bind a known drug or a molecule similar to a known drug, respectively. The kernel provides a source of potential drug targets and drug candidates around which an online open source community can nucleate. Using NMR spectroscopy, we have experimentally tested our predictions for two of these targets, confirming one and invalidating the other.Conclusions/significanceThe TDI kernel, which is being offered under the Creative Commons attribution share-alike license for free and unrestricted use, can be accessed on the World Wide Web at http://www.tropicaldisease.org. We hope that the kernel will facilitate collaborative efforts towards the discovery of new drugs against parasites that cause tropical diseases

Developmental Disruption of Erbb4 in Pet1+ Neurons Impairs Serotonergic Sub-System Connectivity and Memory Formation

International audienceThe serotonergic system of mammals innervates virtually all the central nervous system and regulates a broad spectrum of behavioral and physiological functions. In mammals, serotonergic neurons located in the rostral raphe nuclei encompass diverse sub-systems characterized by specific circuitry and functional features. Substantial evidence suggest that functional diversity of serotonergic circuits has a molecular and connectivity basis. However, the landscape of intrinsic developmental mechanisms guiding the formation of serotonergic sub-systems is unclear. Here, we employed developmental disruption of gene expression specific to serotonergic subsets to probe the contribution of the tyrosine kinase receptor ErbB4 to serotonergic circuit formation and function. Through an in vivo loss-of-function approach, we found that ErbB4 expression occurring in a subset of serotonergic neurons, is necessary for axonal arborization of defined long-range projections to the forebrain but is dispensable for the innervation of other targets of the serotonergic system. We also found that Erbb4-deletion does not change the global excitability or the number of neurons with serotonin content in the dorsal raphe nuclei. In addition, ErbB4-deficiency in serotonergic neurons leads to specific behavioral deficits in memory processing that involve aversive or social components. Altogether, our work unveils a developmental mechanism intrinsically acting through ErbB4 in subsets of serotonergic neurons to orchestrate a precise long-range circuit and ultimately involved in the formation of emotional and social memories