Type I interferon blockade with anifrolumab in patients with systemic lupus erythematosus modulates key immunopathological pathways in a gene expression and proteomic analysis of two phase 3 trials.

INTRODUCTION: Anifrolumab is a type I interferon (IFN) receptor 1 (IFNAR1) blocking antibody approved for treating patients with systemic lupus erythematosus (SLE). Here, we investigated the immunomodulatory mechanisms of anifrolumab using longitudinal transcriptomic and proteomic analyses of the 52-week, randomised, phase 3 TULIP-1 and TULIP-2 trials. METHODS: Patients with moderate to severe SLE were enrolled in TULIP-1 and TULIP-2 and received intravenous anifrolumab or placebo alongside standard therapy. Whole-blood expression of 18 017 genes using genome-wide RNA sequencing (RNA-seq) (pooled TULIP; anifrolumab, n=244; placebo, n=258) and 184 plasma proteins using Olink and Simoa panels (TULIP-1; anifrolumab, n=124; placebo, n=132) were analysed. We compared treatment groups via gene set enrichment analysis using MetaBase pathway analysis, blood transcriptome modules, in silico deconvolution of RNA-seq and longitudinal linear mixed effect models for gene counts and protein levels. RESULTS: Compared with placebo, anifrolumab modulated >2000 genes by week 24, with overlapping results at week 52 and 41 proteins by week 52. IFNAR1 blockade with anifrolumab downregulated multiple type I and II IFN-induced gene modules/pathways and type III IFN-λ protein levels, and impacted apoptosis-associated and neutrophil extracellular trap-associated transcriptional pathways, innate cell activating chemokines and receptors, proinflammatory cytokines and B-cell activating cytokines. In silico deconvolution of RNA-seq data indicated an increase from baseline of mucosal-associated invariant and γδT cells and a decrease of monocytes following anifrolumab treatment. DISCUSSION: Type I IFN blockade with anifrolumab modulated multiple inflammatory pathways downstream of type I IFN signalling, including apoptotic, innate and adaptive mechanisms that play key roles in SLE immunopathogenesis.

Multiomics links global surfactant dysregulation with airflow obstruction and emphysema in COPD.

Rationale: Pulmonary surfactant is vital for lung homeostasis as it reduces surface tension to prevent alveolar collapse and provides essential immune-regulatory and antipathogenic functions. Previous studies demonstrated dysregulation of some individual surfactant components in COPD. We investigated relationships between COPD disease measures and dysregulation of surfactant components to gain new insights into potential disease mechanisms. Methods: Bronchoalveolar lavage proteome and lipidome were characterised in ex-smoking mild/moderate COPD subjects (n=26) and healthy ex-smoking (n=20) and never-smoking (n=16) controls using mass spectrometry. Serum surfactant protein analysis was performed. Results: Total phosphatidylcholine, phosphatidylglycerol, phosphatidylinositol, surfactant protein (SP)-B, SP-A and SP-D concentrations were lower in COPD versus controls (log2 fold change (log2FC) -2.0, -2.2, -1.5, -0.5, -0.7 and -0.5 (adjusted p<0.02), respectively) and correlated with lung function. Total phosphatidylcholine, phosphatidylglycerol, phosphatidylinositol, SP-A, SP-B, SP-D, napsin A and CD44 inversely correlated with computed tomography small airways disease measures (expiratory to inspiratory mean lung density) (r= -0.56, r= -0.58, r= -0.45, r= -0.36, r= -0.44, r= -0.37, r= -0.40 and r= -0.39 (adjusted p<0.05)). Total phosphatidylcholine, phosphatidylglycerol, phosphatidylinositol, SP-A, SP-B, SP-D and NAPSA inversely correlated with emphysema (% low-attenuation areas): r= -0.55, r= -0.61, r= -0.48, r= -0.51, r= -0.41, r= -0.31 and r= -0.34, respectively (adjusted p<0.05). Neutrophil elastase, known to degrade SP-A and SP-D, was elevated in COPD versus controls (log2FC 0.40, adjusted p=0.0390), and inversely correlated with SP-A and SP-D. Serum SP-D was increased in COPD versus healthy ex-smoking volunteers, and predicted COPD status (area under the curve 0.85). Conclusions: Using a multiomics approach, we demonstrate, for the first time, global surfactant dysregulation in COPD that was associated with emphysema, giving new insights into potential mechanisms underlying the cause or consequence of disease.

Proteomic profiling of serum identifies a molecular signature that correlates with clinical outcomes in COPD.

OBJECTIVE: Novel biomarkers related to main clinical hallmarks of Chronic obstructive pulmonary disease (COPD), a heterogeneous disorder with pulmonary and extra-pulmonary manifestations, were investigated by profiling the serum levels of 1305 proteins using Slow Off-rate Modified Aptamers (SOMA)scan technology. METHODS: Serum samples were collected from 241 COPD subjects in the multicenter French Cohort of Bronchial obstruction and Asthma to measure the expression of 1305 proteins using SOMAscan proteomic platform. Clustering of the proteomics was applied to identify disease subtypes and their functional annotation and association with key clinical parameters were examined. Cluster findings were revalidated during a follow-up visit, and compared to those obtained in a group of 47 COPD patients included in the Melbourne Longitudinal COPD Cohort. RESULTS: Unsupervised clustering identified two clusters within COPD subjects at inclusion. Cluster 1 showed elevated levels of factors contributing to tissue injury, whereas Cluster 2 had higher expression of proteins associated with enhanced immunity and host defense, cell fate, remodeling and repair and altered metabolism/mitochondrial functions. Patients in Cluster 2 had a lower incidence of exacerbations, unscheduled medical visits and prevalence of emphysema and diabetes. These protein expression patterns were conserved during a follow-up second visit, and substanciated, by a large part, in a limited series of COPD patients. Further analyses identified a signature of 15 proteins that accurately differentiated the two COPD clusters at the 2 visits. CONCLUSIONS: This study provides insights into COPD heterogeneity and suggests that overexpression of factors involved in lung immunity/host defense, cell fate/repair/ remodelling and mitochondrial/metabolic activities contribute to better clinical outcomes. Hence, high throughput proteomic assay offers a powerful tool for identifying COPD endotypes and facilitating targeted therapies.

Evaluation of FOXO1 Target Engagement Using a Single-Cell Microfluidic Platform.

The cellular thermal shift assay (CETSA) has been used extensively since its introduction to study drug-target engagement within both live cells and cellular lysate. This has proven to be a useful tool in early stage drug discovery and is used to study a wide range of protein classes. We describe the application of a single-cell CETSA workflow within a microfluidic affinity capture (MAC) chip. This has enabled us to quantitatively determine the active FOXO1 single-molecule count and observe FOXO1 stabilization and destabilization in the presence of three small molecule inhibitors, including demonstrating the determination of EC50. The successful use of the MAC chip for single-cell CETSA paves the way for the study of precious clinical samples owing to the low number of cells needed by the chip. It also provides a useful tool for studying any underlying population heterogeneity that exists within a cellular system, a feature that is usually masked when conducting ensemble measurements.

Rare variant contribution to human disease in 281,104 UK Biobank exomes.

Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variants to common disease remains relatively unexplored. The UK Biobank contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the effect of rare variation on a broad collection of traits1,2. Here we study the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UK Biobank participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene-phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single-variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene-phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UK Biobank participants of African, East Asian or South Asian ancestry. Our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal ( http://azphewas.com/ ).

Dysregulation of COVID-19 related gene expression in the COPD lung.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) patients are at increased risk of poor outcome from Coronavirus disease (COVID-19). Early data suggest elevated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) receptor angiotensin converting enzyme 2 (ACE2) expression, but relationships to disease phenotype and downstream regulators of inflammation in the Renin-Angiotensin system (RAS) are unknown. We aimed to determine the relationship between RAS gene expression relevant to SARS-CoV-2 infection in the lung with disease characteristics in COPD, and the regulation of newly identified SARS-CoV-2 receptors and spike-cleaving proteases, important for SARS-CoV-2 infection. METHODS: We quantified gene expression using RNA sequencing of epithelial brushings and bronchial biopsies from 31 COPD and 37 control subjects. RESULTS: ACE2 gene expression (log2-fold change (FC)) was increased in COPD compared to ex-smoking (HV-ES) controls in epithelial brushings (0.25, p = 0.042) and bronchial biopsies (0.23, p = 0.050), and correlated with worse lung function (r = - 0.28, p = 0.0090). ACE2 was further increased in frequent exacerbators compared to infrequent exacerbators (0.51, p = 0.00045) and associated with use of ACE inhibitors (ACEi) (0.50, p = 0.0034), having cardiovascular disease (0.23, p = 0.048) or hypertension (0.34, p = 0.0089), and inhaled corticosteroid use in COPD subjects in bronchial biopsies (0.33, p = 0.049). Angiotensin II receptor type (AGTR)1 and 2 expression was decreased in COPD bronchial biopsies compared to HV-ES controls with log2FC of -0.26 (p = 0.033) and - 0.40, (p = 0.0010), respectively. However, the AGTR1:2 ratio was increased in COPD subjects compared with HV-ES controls, log2FC of 0.57 (p = 0.0051). Basigin, a newly identified potential SARS-CoV-2 receptor was also upregulated in both brushes, log2FC of 0.17 (p = 0.0040), and bronchial biopsies, (log2FC of 0.18 (p = 0.017), in COPD vs HV-ES. Transmembrane protease, serine (TMPRSS)2 was not differentially regulated between control and COPD. However, various other spike-cleaving proteases were, including TMPRSS4 and Cathepsin B, in both epithelial brushes (log2FC of 0.25 (p = 0.0012) and log2FC of 0.56 (p = 5.49E-06), respectively) and bronchial biopsies (log2FC of 0.49 (p = 0.00021) and log2FC of 0.246 (p = 0.028), respectively). CONCLUSION: This study identifies key differences in expression of genes related to susceptibility and aetiology of COVID-19 within the COPD lung. Further studies to understand the impact on clinical course of disease are now required.

Identification of a missense variant in SPDL1 associated with idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a fatal disorder characterised by progressive, destructive lung scarring. Despite substantial progress, the genetic determinants of this disease remain incompletely defined. Using whole genome and whole exome sequencing data from 752 individuals with sporadic IPF and 119,055 UK Biobank controls, we performed a variant-level exome-wide association study (ExWAS) and gene-level collapsing analyses. Our variant-level analysis revealed a novel association between a rare missense variant in SPDL1 and IPF (NM_017785.5:g.169588475 G > A p.Arg20Gln; p = 2.4 × 10-7, odds ratio = 2.87, 95% confidence interval: 2.03-4.07). This signal was independently replicated in the FinnGen cohort, which contains 1028 cases and 196,986 controls (combined p = 2.2 × 10-20), firmly associating this variant as an IPF risk allele. SPDL1 encodes Spindly, a protein involved in mitotic checkpoint signalling during cell division that has not been previously described in fibrosis. To the best of our knowledge, these results highlight a novel mechanism underlying IPF, providing the potential for new therapeutic discoveries in a disease of great unmet need.

MODifieR: an Ensemble R Package for Inference of Disease Modules from Transcriptomics Networks.

MOTIVATION: Complex diseases are due to the dense interactions of many disease-associated factors that dysregulate genes that in turn form the so-called disease modules, which have shown to be a powerful concept for understanding pathological mechanisms. There exist many disease module inference methods that rely on somewhat different assumptions, but there is still no gold standard or best-performing method. Hence, there is a need for combining these methods to generate robust disease modules. RESULTS: We developed MODule IdentiFIER (MODifieR), an ensemble R package of nine disease module inference methods from transcriptomics networks. MODifieR uses standardized input and output allowing the possibility to combine individual modules generated from these methods into more robust disease-specific modules, contributing to a better understanding of complex diseases. AVAILABILITY AND IMPLEMENTATION: MODifieR is available under the GNU GPL license and can be freely downloaded from https://gitlab.com/Gustafsson-lab/MODifieR and as a Docker image from https://hub.docker.com/r/ddeweerd/modifier. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Fungal Dysbiosis and Intestinal Inflammation in Children With Beta-Cell Autoimmunity.

Although gut bacterial dysbiosis is recognized as a regulator of beta-cell autoimmunity, no data is available on fungal dysbiosis in the children at the risk of type 1 diabetes (T1D). We hypothesized that the co-occurrence of fungal and bacterial dysbiosis contributes to the intestinal inflammation and autoimmune destruction of insulin-producing beta-cells in T1D. Fecal and blood samples were collected from 26 children tested positive for at least one diabetes-associated autoantibody (IAA, GADA, IA-2A or ICA) and matched autoantibody-negative children with HLA-conferred susceptibility to T1D (matched for HLA-DQB1 haplotype, age, gender and early childhood nutrition). Bacterial 16S and fungal ITS2 sequencing, and analyses of the markers of intestinal inflammation, namely fecal human beta-defensin-2 (HBD2), calprotectin and secretory total IgA, were performed. Anti-Saccharomyces cerevisiae antibodies (ASCA) and circulating cytokines, IFNG, IL-17 and IL-22, were studied. After these analyses, the children were followed for development of clinical T1D (median 8 years and 8 months). Nine autoantibody positive children were diagnosed with T1D, whereas none of the autoantibody negative children developed T1D during the follow-up. Fungal dysbiosis, characterized by high abundance of fecal Saccharomyces and Candida, was found in the progressors, i.e., children with beta-cell autoimmunity who during the follow-up progressed to clinical T1D. These children showed also bacterial dysbiosis, i.e., increased Bacteroidales and Clostridiales ratio, which was, however, found also in the non-progressors, and is thus a common nominator in the children with beta-cell autoimmunity. Furthermore, the progressors showed markers of intestinal inflammation detected as increased levels of fecal HBD2 and ASCA IgG to fungal antigens. We conclude that the fungal and bacterial dysbiosis, and intestinal inflammation are associated with the development of T1D in children with beta-cell autoimmunity.

Activation of group 2 innate lymphoid cells after allergen challenge in asthmatic patients.

BACKGROUND: Group 2 innate lymphoid cells (ILC2s) are effective producers of IL-5 and IL-13 during allergic inflammation and bridge the innate and adaptive immune responses. ILC2 numbers are increased in asthmatic patients compared with healthy control subjects. Thus far, human data describing their phenotype during acute allergic inflammation in the lung are incomplete. OBJECTIVES: This study aims to characterize and compare blood- and lung-derived ILC2s before and after segmental allergen challenge in patients with mild-to-moderate asthma with high blood eosinophil counts (≥300 cells/µL). METHODS: ILC2s were isolated from blood and bronchoalveolar lavage (BAL) fluid before and after segmental allergen challenge. Cells were sorted by means of flow cytometry, cultured and analyzed for cytokine release or migration, and sequenced for RNA expression. RESULTS: ILC2s were nearly absent in the alveolar space under baseline conditions, but numbers increased significantly after allergen challenge (P < .05), whereas at the same time, ILC2 numbers in blood were reduced (P < .05). Prostaglandin D2 and CXCL12 levels in BAL fluid correlated with decreased ILC2 numbers in blood (P = .004, respective P = .024). After allergen challenge, several genes promoting type 2 inflammation were expressed at greater levels in BAL fluid compared with blood ILC2s, whereas blood ILC2s remain unactivated. CONCLUSION: ILC2s accumulate at the site of allergic inflammation and are recruited from the blood. Their transcriptional and functional activation pattern promotes type 2 inflammation.

Bleomycin hydrolase regulates the release of chemokines important for inflammation and wound healing by keratinocytes.

Bleomycin hydrolase (BLMH) is a well-conserved cysteine protease widely expressed in several mammalian tissues. In skin, which contains high levels of BLMH, this protease is involved in the degradation of citrullinated filaggrin monomers into free amino acids important for skin hydration. Interestingly, the expression and activity of BLMH is reduced in patients with atopic dermatitis (AD) and psoriasis, and BLMH knockout mice acquire tail dermatitis. Apart from its already known function, we have discovered a novel role of BLMH in the regulation of inflammatory chemokines and wound healing. We show that lowered BLMH levels in keratinocytes result in increased release of the pro-inflammatory chemokines CXCL8 and GROα, which are upregulated in skin from AD patients compared to healthy individuals. Conditioned media from keratinocytes expressing low levels of BLMH increased chemotaxis by neutrophils and caused a delayed wound healing in the presence of low-level TNFα. This defective wound healing was improved by blocking the shared receptor of CXCL8 and GROα, namely CXCR2, using a specific receptor antagonist. Collectively, our results present a novel function of BLMH in regulating the secretion of chemokines involved in inflammation and wound healing in human keratinocytes.

Unexplored therapeutic opportunities in the human genome.

This corrects the article DOI: 10.1038/nrd.2018.14.

Unexplored therapeutic opportunities in the human genome.

A large proportion of biomedical research and the development of therapeutics is focused on a small fraction of the human genome. In a strategic effort to map the knowledge gaps around proteins encoded by the human genome and to promote the exploration of currently understudied, but potentially druggable, proteins, the US National Institutes of Health launched the Illuminating the Druggable Genome (IDG) initiative in 2014. In this article, we discuss how the systematic collection and processing of a wide array of genomic, proteomic, chemical and disease-related resource data by the IDG Knowledge Management Center have enabled the development of evidence-based criteria for tracking the target development level (TDL) of human proteins, which indicates a substantial knowledge deficit for approximately one out of three proteins in the human proteome. We then present spotlights on the TDL categories as well as key drug target classes, including G protein-coupled receptors, protein kinases and ion channels, which illustrate the nature of the unexplored opportunities for biomedical research and therapeutic development.

Neutrophils in ulcerative colitis: a review of selected biomarkers and their potential therapeutic implications.

OBJECTIVES: This review article describes the role of neutrophils in mucosal injury and the resulting crypt abscesses characteristic of ulcerative colitis. We also review selected biomarkers for monitoring neutrophil presence and activity in the mucosa as well as their potential as therapeutic targets. MATERIAL: We have collated and selectively reviewed data on the most prominent well-established and emerging neutrophil-related biomarkers and potential therapeutic targets (calprotectin, lactoferrin, CXCR1, CXCR2, MMP-9, NGAL, elafin, HNE, pANCAs, MPO, CD16, CD177, CD64, HNPs, SLPI and PTX3) in ulcerative colitis. RESULTS: Systemic and intestinal neutrophil activity increases substantially in active ulcerative colitis, driving tissue damage and extra-intestinal manifestations. Calprotectin is a robust neutrophil and disease biomarker, and a few neutrophil-related targets are being clinically explored as therapeutic targets. CONCLUSION: We propose that targeting neutrophils and their inflammatory mediators per se is an opportunity that should be explored to identify new effective medical therapies. The overall clinical goal for neutrophil-targeted therapy will be to modulate, but not completely silence, neutrophil activity, thereby abolishing the destructive inflammation with associated acute and chronic tissue damage without compromising host-defense.

The value of integrating pre-clinical data to predict nausea and vomiting risk in humans as illustrated by AZD3514, a novel androgen receptor modulator.

Nausea and vomiting are components of a complex mechanism that signals food avoidance and protection of the body against the absorption of ingested toxins. This response can also be triggered by pharmaceuticals. Predicting clinical nausea and vomiting liability for pharmaceutical agents based on pre-clinical data can be problematic as no single animal model is a universal predictor. Moreover, efforts to improve models are hampered by the lack of translational animal and human data in the public domain. AZD3514 is a novel, orally-administered compound that inhibits androgen receptor signaling and down-regulates androgen receptor expression. Here we have explored the utility of integrating data from several pre-clinical models to predict nausea and vomiting in the clinic. Single and repeat doses of AZD3514 resulted in emesis, salivation and gastrointestinal disturbances in the dog, and inhibited gastric emptying in rats after a single dose. AZD3514, at clinically relevant exposures, induced dose-responsive "pica" behaviour in rats after single and multiple daily doses, and induced retching and vomiting behaviour in ferrets after a single dose. We compare these data with the clinical manifestation of nausea and vomiting encountered in patients with castration-resistant prostate cancer receiving AZD3514. Our data reveal a striking relationship between the pre-clinical observations described and the experience of nausea and vomiting in the clinic. In conclusion, the emetic nature of AZD3514 was predicted across a range of pre-clinical models, and the approach presented provides a valuable framework for predicition of clinical nausea and vomiting.

Evaluation of the use of imaging parameters for the detection of compound-induced hepatotoxicity in 384-well cultures of HepG2 cells and cryopreserved primary human hepatocytes.

Drug-induced liver injury (DILI) is a major cause of failed drug development, withdrawal and restricted usage. Therefore screening assays which aid selection of candidate drugs with reduced propensity to cause DILI are required. We have investigated the toxicity of 144 drugs, 108 of which caused DILI, using assays identified in the literature as having some predictivity for hepatotoxicity. The validated assays utilised either HepG2 cells, HepG2 cells in the presence of rat S9 fraction or isolated human hepatocytes. All parameters were quantified by multiplexed and automated high content fluorescence microscopy, at appropriate time points after compound administration (4, 24 or 48h). The individual endpoint which identified drugs that caused DILI with greatest precision was maximal fold induction in CM-H2DFFDA staining in hepatocytes after 24h (41% sensitivity, 86% specificity). However, hierarchical clustering analysis of all endpoints provided the most sensitive identification of drugs which caused DILI (58% sensitivity, 75% specificity). We conclude that multi-parametric high content cell toxicity assays can enable in vitro detection of drugs that have high propensity to cause DILI in vivo but that many DILI compounds exhibit few in vitro signals when evaluated using these assays.

Novel pseudopeptides incorporating a benzodiazepine-based turn mimetic--targeting Mycobacterium tuberculosis ribonucleotide reductase.

Peptides mimicking the C-terminus of the small subunit (R2) of Mycobacterium tuberculosis ribonucleotide reductase (RNR) can compete for binding to the large subunit (R1) and thus inhibit RNR activity. Moreover, it has been suggested that the binding of the R2 C-terminus is very similar in M. tuberculosis and Salmonella typhimurium. Based on modeling studies of a crystal structure of the holocomplex of the S. typhimurium enzyme, a benzodiazepine-based turn mimetic was identified and a set of novel compounds incorporating the benzodiazepine scaffold was synthesized. The compounds were evaluated in a competitive fluorescence polarization assay and in an RNR activity assay. These studies revealed that the compounds incorporating the benzodiazepine scaffold have the ability to compete for the M. tuberculosis R2 binding site with low-micromolar affinity.

Exploiting Pharmacological Similarity to Identify Safety Concerns - Listen to What the Data Tells You.

Whilst most new drugs are designed to act on a single target or a small number of targets, many do show broad pharmacological activity. In some cases this can be beneficial and necessary for efficacy and in others it can be detrimental, leading to increased safety liability. To probe off-target pharmacology most drug discovery programs include screening against a broad panel of targets that represent known troublesome pharmacology. Hits against any one of these targets can then be subjected to a risk assessment for potential safety problems in preclinical or clinical studies. In addition, the secondary pharmacology profile can also be thought of as an alternative description of the compound and as such can be used as a method for assessing 'similarity'. Consequently, inspection of the in vivo findings of pharmacological neighbors can give important insights into potential safety liabilities that are neither identified by pure chemical similarity searches nor by risk assessment on individual targets. Here we show that the pharmacological profile contains additional information as compared to chemical similarity, and also demonstrate how this can be used in the hazard assessment done during drug discovery and development.

Application of data mining and visualization techniques for the prediction of drug-induced nausea in man.

The therapeutic value of many drugs can be limited by gastrointestinal (GI) adverse effects such as nausea and vomiting. Nausea is a subjective human sensation, hence little is known about preclinical biomarkers that may accurately and effectively predict its presence in man. The aim of this analysis was to use informatics and data-mining tools to identify plausible preclinical GI effects that may be associated with nausea and that could be of potential use in its prediction. A total of 86 marketed drugs were used in this analysis, and the main outcome was a confirmation that nausogenic and non-nausogenic drugs can be clearly separated based on their preclinical GI observations. Specifically, combinations of common preclinical GI effects (vomiting, diarrhea, and salivary hypersecretion) proved to be strong predictors. The model was subsequently validated with a subset of 20 blinded proprietary small molecules and successfully predicted clinical outcome in 90% of cases. This investigation demonstrated the feasibility of data-mining approaches to facilitate discovery of novel, plausible associations that can be used to understand drug-induced adverse effects.

DrugPred: a structure-based approach to predict protein druggability developed using an extensive nonredundant data set.

Judging if a protein is able to bind orally available molecules with high affinity, i.e. if a protein is druggable, is an important step in target assessment. In order to derive a structure-based method to predict protein druggability, a comprehensive, nonredundant data set containing crystal structures of 71 druggable and 44 less druggable proteins was compiled by literature search and data mining. This data set was subsequently used to train a structure-based druggability predictor (DrugPred) using partial least-squares projection to latent structures discriminant analysis (PLS-DA). DrugPred performed well in discriminating druggable from less druggable binding sites for both internal and external predictions. The method is robust against conformational changes in the binding site and outperforms previously published methods. The superior performance of DrugPred is likely due to the size and composition of the training set which, in contrast to most previously developed methods, only contains cavities that have evolved to bind a natural ligand.