Knowledge graph analytics platform with LINCS and IDG for Parkinson's disease target illumination.

BACKGROUND: LINCS, "Library of Integrated Network-based Cellular Signatures", and IDG, "Illuminating the Druggable Genome", are both NIH projects and consortia that have generated rich datasets for the study of the molecular basis of human health and disease. LINCS L1000 expression signatures provide unbiased systems/omics experimental evidence. IDG provides compiled and curated knowledge for illumination and prioritization of novel drug target hypotheses. Together, these resources can support a powerful new approach to identifying novel drug targets for complex diseases, such as Parkinson's disease (PD), which continues to inflict severe harm on human health, and resist traditional research approaches. RESULTS: Integrating LINCS and IDG, we built the Knowledge Graph Analytics Platform (KGAP) to support an important use case: identification and prioritization of drug target hypotheses for associated diseases. The KGAP approach includes strong semantics interpretable by domain scientists and a robust, high performance implementation of a graph database and related analytical methods. Illustrating the value of our approach, we investigated results from queries relevant to PD. Approved PD drug indications from IDG's resource DrugCentral were used as starting points for evidence paths exploring chemogenomic space via LINCS expression signatures for associated genes, evaluated as target hypotheses by integration with IDG. The KG-analytic scoring function was validated against a gold standard dataset of genes associated with PD as elucidated, published mechanism-of-action drug targets, also from DrugCentral. IDG's resource TIN-X was used to rank and filter KGAP results for novel PD targets, and one, SYNGR3 (Synaptogyrin-3), was manually investigated further as a case study and plausible new drug target for PD. CONCLUSIONS: The synergy of LINCS and IDG, via KG methods, empowers graph analytics methods for the investigation of the molecular basis of complex diseases, and specifically for identification and prioritization of novel drug targets. The KGAP approach enables downstream applications via integration with resources similarly aligned with modern KG methodology. The generality of the approach indicates that KGAP is applicable to many disease areas, in addition to PD, the focus of this paper.

edge2vec: Representation learning using edge semantics for biomedical knowledge discovery.

BACKGROUND: Representation learning provides new and powerful graph analytical approaches and tools for the highly valued data science challenge of mining knowledge graphs. Since previous graph analytical methods have mostly focused on homogeneous graphs, an important current challenge is extending this methodology for richly heterogeneous graphs and knowledge domains. The biomedical sciences are such a domain, reflecting the complexity of biology, with entities such as genes, proteins, drugs, diseases, and phenotypes, and relationships such as gene co-expression, biochemical regulation, and biomolecular inhibition or activation. Therefore, the semantics of edges and nodes are critical for representation learning and knowledge discovery in real world biomedical problems. RESULTS: In this paper, we propose the edge2vec model, which represents graphs considering edge semantics. An edge-type transition matrix is trained by an Expectation-Maximization approach, and a stochastic gradient descent model is employed to learn node embedding on a heterogeneous graph via the trained transition matrix. edge2vec is validated on three biomedical domain tasks: biomedical entity classification, compound-gene bioactivity prediction, and biomedical information retrieval. Results show that by considering edge-types into node embedding learning in heterogeneous graphs, edge2vec significantly outperforms state-of-the-art models on all three tasks. CONCLUSIONS: We propose this method for its added value relative to existing graph analytical methodology, and in the real world context of biomedical knowledge discovery applicability.

Changes in the Factor VIII C2 domain upon membrane binding determined by hydrogen-deuterium exchange MS.

Factor VIII enhances the catalytic activity of Factor IXa in a membrane-bound enzyme complex and both proteins are necessary to prevent haemophilia. Tandem lectin-like C domains mediate the membrane binding of Factor VIII and membrane-interactive residues have been identified. However, the available data provide little insight into the dynamic changes that occur upon membrane binding. We used time-based hydrogen-deuterium exchange MS to evaluate the dynamics of FVIII-C2 (Factor VIII C2 domain) alone and when membrane bound. The results confirm the participation of previously identified membrane-interactive loops in the binding mechanism. In addition, they indicate that a long peptide segment, encompassing a membrane-interactive loop and strands of the ß-barrel core, is remarkably dynamic prior to membrane binding. The flexibility is reduced following membrane binding. In addition, regions that interact with the A1 and C1 domains have reduced solvent exchange. Thus the isolated C2 domain has extensive flexibility that is subject to stabilization and could be related to interactions between domains as well as between Factor VIII and Factor IXa or Factor X. These results confirm that the proposed membrane-binding loops of the FVIII-C2 interact with the membrane in a manner that leads to protection from solvent exposure.

Conformational analysis of Epac activation using amide hydrogen/deuterium exchange mass spectrometry.

Exchange proteins directly activated by cAMP (Epac) play important roles in mediating the effects of cAMP through the activation of downstream small GTPases, Rap. To delineate the mechanism of Epac activation, we probed the conformation and structural dynamics of Epac using amide hydrogen/deuterium exchange and structural modeling. Our studies show that cAMP induces significant conformational changes that lead to a spatial rearrangement of the regulatory components of Epac and allows the exposure of the catalytic core for effector binding without imposing significant conformational change on the catalytic core. Homology modeling and comparative structural analyses of the cAMP binding domains of Epac and cAMP-dependent protein kinase (PKA) lead to a model of Epac activation, in which Epac and PKA activation by cAMP employs the same underlying principle, although the detailed structural and conformational changes associated with Epac and PKA activation are significantly different.

Imidazole antibiotics inhibit the nitric oxide dioxygenase function of microbial flavohemoglobin.

Flavohemoglobins metabolize nitric oxide (NO) to nitrate and protect bacteria and fungi from NO-mediated damage, growth inhibition, and killing by NO-releasing immune cells. Antimicrobial imidazoles were tested for their ability to coordinate flavohemoglobin and inhibit its NO dioxygenase (NOD) function. Miconazole, econazole, clotrimazole, and ketoconazole inhibited the NOD activity of Escherichia coli flavohemoglobin with apparent K(i) values of 80, 550, 1,300, and 5,000 nM, respectively. Saccharomyces cerevisiae, Candida albicans, and Alcaligenes eutrophus enzymes exhibited similar sensitivities to imidazoles. Imidazoles coordinated the heme iron atom, impaired ferric heme reduction, produced uncompetitive inhibition with respect to O(2) and NO, and inhibited NO metabolism by yeasts and bacteria. Nevertheless, these imidazoles were not sufficiently selective to fully mimic the NO-dependent growth stasis seen with NOD-deficient mutants. The results demonstrate a mechanism for NOD inhibition by imidazoles and suggest a target for imidazole engineering.

Molecular interactions between matrilysin and the matrix metalloproteinase inhibitor doxycycline investigated by deuterium exchange mass spectrometry.

Matrix metalloproteinases (MMPs) play an essential role in normal and pathological extracellular matrix degradation. Deuterium exchange mass spectrometry (DXMS) was used to localize the binding regions of the broad-spectrum MMP inhibitor doxycycline on the active form of matrilysin (residues 95-267) and to assess alterations in structure induced by doxycycline binding. DXMS analyses of inhibitor-bound versus inhibitor-free forms of matrilysin reveal two primary sites of reduced hydrogen/deuterium exchange (residues 145-153; residues 193-204) that flank the structural zinc binding site. Equilibrium dialysis studies of doxycycline-matrilysin binding yielded a K(d) of 73 microM with a binding stoichiometry of 2.3 inhibitor molecules per protein, which compares well with DXMS results that show principal reduction in deuterium exchange at two sites. Lesser changes in deuterium exchange evident at the amino and carboxyl termini are attributed to inhibitor-induced structural fluctuations. Tryptophan fluorescence quenching experiments of matrilysin with potassium iodide suggest changes in conformation induced by doxycycline binding. In the presence of doxycycline, tryptophan quenching is reduced by approximately 17% relative to inhibitor-free matrilysin. Examination of the X-ray crystal structure of matrilysin shows that the doxycycline-binding site at residues 193 to 204 is positioned within the structural metal center of matrilysin, adjacent to the structural zinc atom and near both calcium atoms. These results suggest a mode of matrilysin inhibition by doxycycline that could involve interactions with the structural zinc atom and/or calcium atoms within the structural metal center of the protein.

Regulation of the nitric oxide reduction operon (norRVW) in Escherichia coli. Role of NorR and sigma54 in the nitric oxide stress response.

Nitric oxide (NO) induces NO-detoxifying enzymes in Escherichia coli suggesting sensitive mechanisms for coordinate control of NO defense genes in response to NO stress. Exposure of E. coli to sub-micromolar NO levels under anaerobic conditions rapidly induced transcription of the NO reductase (NOR) structural genes, norV and norW, as monitored by lac gene fusions. Disruption of rpoN (sigma(54)) impaired the NO-mediated induction of norV and norW transcription and NOR expression, whereas disruption of the upstream regulatory gene, norR, completely ablated NOR induction. NOR inducibility was restored to NorR null mutants by expressing NorR in trans. Furthermore, an internal deletion of the N-terminal domain of NorR activated NOR expression independent of NO exposure. Neither NorR nor sigma(54) was essential for NO-mediated induction of the NO dioxygenase (flavohemoglobin) encoded by hmp. However, elevated NOR activity inhibited NO dioxygenase induction, and, in the presence of dioxygen, NO dioxygenase inhibited norV induction by NO. The results demonstrate the role of NorR as a sigma(54)-dependent regulator of norVW expression. A role for the NorR N-terminal domain as a transducer or sensor for NO is suggested.