Toxicogenomic biomarkers for renal papillary injury in rats.

Renal papillary injury is a common side effect observed during nonclinical and clinical investigations in drug development. The present study aimed to identify genomic biomarkers for early and sensitive detection of renal papillary injury in rats. We hypothesized that previously identified genomic biomarkers for tubular injury might be applicable for the sensitive detection of papillary injury in rats.

Toxicogenomic multigene biomarker for predicting the future onset of proximal tubular injury in rats.

Drug-induced renal tubular injury is a major concern in the preclinical safety evaluation of drug candidates. Toxicogenomics is now a generally accepted tool for identifying chemicals with potential safety problems. The specific aim of the present study was to develop a model for use in predicting the future onset of drug-induced proximal tubular injury following repeated dosing with various nephrotoxicants.

Identification of a novel set of biomarkers for evaluating phospholipidosis-inducing potential of compounds using rat liver microarray data measured 24-h after single dose administration.

Phospholipid accumulation manifests as an adverse effect of cationic amphiphilic drugs in particular. Detection, however, by histopathology examination is time-consuming and may require repeated administration of compounds for several weeks. To eliminate compounds with potential for inducing phospholipidosis from the discovery pipeline, we have identified and validated a set of biomarkers for predicting the phospholipidosis-inducing potential utilizing a comprehensive rat transcriptome microarray database created by the Japanese Toxicogenomics and Toxicogenomics Informatics Projects (TGP/TGP2) together with in-house data.

Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database.

The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens.

Predicting drug-induced hepatotoxicity using QSAR and toxicogenomics approaches.

Quantitative structure-activity relationship (QSAR) modeling and toxicogenomics are typically used independently as predictive tools in toxicology. In this study, we evaluated the power of several statistical models for predicting drug hepatotoxicity in rats using different descriptors of drug molecules, namely, their chemical descriptors and toxicogenomics profiles. The records were taken from the Toxicogenomics Project rat liver microarray database containing information on 127 drugs ( http://toxico.

Analysis of multiple compound-protein interactions reveals novel bioactive molecules.

The discovery of novel bioactive molecules advances our systems-level understanding of biological processes and is crucial for innovation in drug development. For this purpose, the emerging field of chemical genomics is currently focused on accumulating large assay data sets describing compound-protein interactions (CPIs). Although new target proteins for known drugs have recently been identified through mining of CPI databases, using these resources to identify novel ligands remains unexplored.

Identification of genomic biomarkers for concurrent diagnosis of drug-induced renal tubular injury using a large-scale toxicogenomics database.

Drug-induced renal tubular injury is one of the major concerns in preclinical safety evaluations. Toxicogenomics is becoming a generally accepted approach for identifying chemicals with potential safety problems. In the present study, we analyzed 33 nephrotoxicants and 8 non-nephrotoxic hepatotoxicants to elucidate time- and dose-dependent global gene expression changes associated with proximal tubular toxicity.

GLIDA: GPCR--ligand database for chemical genomics drug discovery--database and tools update.

G-protein coupled receptors (GPCRs) represent one of the most important families of drug targets in pharmaceutical development. GLIDA is a public GPCR-related Chemical Genomics database that is primarily focused on the integration of information between GPCRs and their ligands. It provides interaction data between GPCRs and their ligands, along with chemical information on the ligands, as well as biological information regarding GPCRs.

Comprehensive analysis of distinctive polyketide and nonribosomal peptide structural motifs encoded in microbial genomes.

We developed a highly accurate method to predict polyketide (PK) and nonribosomal peptide (NRP) structures encoded in microbial genomes. PKs/NRPs are polymers of carbonyl/peptidyl chains synthesized by polyketide synthases (PKS) and nonribosomal peptide synthetases (NRPS). We analyzed domain sequences corresponding to specific substrates and physical interactions between PKSs/NRPSs in order to predict which substrates (carbonyl/peptidyl units) are selected and assembled into highly ordered chemical structures.