Predicting Volume of Distribution in Humans: Performance of In Silico Methods for a Large Set of Structurally Diverse Clinical Compounds.

Volume of distribution at steady state (VD,ss) is one of the key pharmacokinetic parameters estimated during the drug discovery process. Despite considerable efforts to predict VD,ss, accuracy and choice of prediction methods remain a challenge, with evaluations constrained to a small set (<150) of compounds. To address these issues, a series of in silico methods for predicting human VD,ss directly from structure were evaluated using a large set of clinical compounds. Machine learning (ML) models were built to predict VD,ss directly and to predict input parameters required for mechanistic and empirical VD,ss predictions. In addition, log D, fraction unbound in plasma (fup), and blood-to-plasma partition ratio (BPR) were measured on 254 compounds to estimate the impact of measured data on predictive performance of mechanistic models. Furthermore, the impact of novel methodologies such as measuring partition (Kp) in adipocytes and myocytes (n = 189) on VD,ss predictions was also investigated. In predicting VD,ss directly from chemical structures, both mechanistic and empirical scaling using a combination of predicted rat and dog VD,ss demonstrated comparable performance (62%-71% within 3-fold). The direct ML model outperformed other in silico methods (75% within 3-fold, r 2 = 0.5, AAFE = 2.2) when built from a larger data set. Scaling to human from predicted VD,ss of either rat or dog yielded poor results (<47% within 3-fold). Measured fup and BPR improved performance of mechanistic VD,ss predictions significantly (81% within 3-fold, r 2 = 0.6, AAFE = 2.0). Adipocyte intracellular Kp showed good correlation to the VD,ss but was limited in estimating the compounds with low VD,ss SIGNIFICANCE STATEMENT: This work advances the in silico prediction of VD,ss directly from structure and with the aid of in vitro data. Rigorous and comprehensive evaluation of various methods using a large set of clinical compounds (n = 956) is presented. The scale of techniques evaluated is far beyond any previously presented. The novel data set (n = 254) generated using a single protocol for each in vitro assay reported in this study could further aid in advancing VD,ss prediction methodologies.

Discovery and Lead-Optimization of 4,5-Dihydropyrazoles as Mono-Kinase Selective, Orally Bioavailable and Efficacious Inhibitors of Receptor Interacting Protein 1 (RIP1) Kinase.

RIP1 kinase regulates necroptosis and inflammation and may play an important role in contributing to a variety of human pathologies, including inflammatory and neurological diseases. Currently, RIP1 kinase inhibitors have advanced into early clinical trials for evaluation in inflammatory diseases such as psoriasis, rheumatoid arthritis, and ulcerative colitis and neurological diseases such as amyotrophic lateral sclerosis and Alzheimer's disease. In this paper, we report on the design of potent and highly selective dihydropyrazole (DHP) RIP1 kinase inhibitors starting from a high-throughput screen and the lead-optimization of this series from a lead with minimal rat oral exposure to the identification of dihydropyrazole 77 with good pharmacokinetic profiles in multiple species. Additionally, we identified a potent murine RIP1 kinase inhibitor 76 as a valuable in vivo tool molecule suitable for evaluating the role of RIP1 kinase in chronic models of disease. DHP 76 showed efficacy in mouse models of both multiple sclerosis and human retinitis pigmentosa.

Novel KV7 ion channel openers for the treatment of epilepsy and implications for detrusor tissue contraction.

Neuronal voltage-gated potassium channels, KV7s, are the molecular mediators of the M current and regulate membrane excitability in the central and peripheral neuronal systems. Herein, we report novel small molecule KV7 openers that demonstrate anti-seizure activities in electroshock and pentylenetetrazol-induced seizure models without influencing Rotarod readouts in mice. The anti-seizure activity was determined to be proportional to the unbound concentration in the brain. KV7 channels are also expressed in the bladder smooth muscle (detrusor) and activation of these channels may cause localized undesired effects. Therefore, the impact of individual KV7 isoforms was investigated in human detrusor tissue using a panel of KV7 openers with distinct activity profiles among KV7 isoforms. KCNQ4 and KCNQ5 mRNA were highly expressed in detrusor tissue, yet a compound that has significantly reduced activity on homomeric KV7.4 did not reduce detrusor contraction. This may suggest that the homomeric KV7.4 channel plays a less significant role in bladder contraction and further investigation is needed.

Metabonomic profiling of bladder cancer.

Early diagnosis and life-long surveillance are clinically important to improve the long-term survival of bladder cancer patients. Currently, a noninvasive biomarker that is as sensitive and specific as cystoscopy in detecting bladder tumors is lacking. Metabonomics is a complementary approach for identifying perturbed metabolic pathways in bladder cancer. Significant progress has been made using modern metabonomic techniques to characterize and distinguish bladder cancer patients from control subjects, identify marker metabolites, and shed insights on the disease biology and potential therapeutic targets. With its rapid development, metabonomics has the potential to impact the clinical management of bladder cancer patients in the future by revolutionizing the diagnosis and life-long surveillance strategies and stratifying patients for diagnostic, surgical, and therapeutic clinical trials. An introduction to metabonomics, typical metabonomic workflow, and critical evaluation of metabonomic investigations in identifying biomarkers for the diagnosis of bladder cancer are presented.

Urinary metabotyping of bladder cancer using two-dimensional gas chromatography time-of-flight mass spectrometry.

Cystoscopy is the gold standard clinical diagnosis of human bladder cancer (BC). As cystoscopy is expensive and invasive, it compromises patients' compliance toward surveillance screening and challenges the detection of recurrent BC. Therefore, the development of a noninvasive method for the diagnosis and surveillance of BC and the elucidation of BC progression become pertinent. In this study, urine samples from 38 BC patients and 61 non-BC controls were subjected to urinary metabotyping using two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS). Subsequent to data preprocessing and chemometric analysis, the orthogonal partial least-squares discriminant analysis (OPLS-DA, R2X=0.278, R2Y=0.904 and Q2Y (cumulative)=0.398) model was validated using permutation tests and receiver operating characteristic (ROC) analysis. Marker metabolites were further screened from the OPLS-DA model using statistical tests. GC×GC-TOFMS urinary metabotyping demonstrated 100% specificity and 71% sensitivity in detecting BC, while 100% specificity and 46% sensitivity were observed via cytology. In addition, the model revealed 46 metabolites that characterize human BC. Among the perturbed metabolic pathways, our clinical finding on the alteration of the tryptophan-quinolinic metabolic axis in BC suggested the potential roles of kynurenine in the malignancy and therapy of BC. In conclusion, global urinary metabotyping holds potential for the noninvasive diagnosis and surveillance of BC in clinics. In addition, perturbed metabolic pathways gleaned from urinary metabotyping shed new and established insights on the biology of human BC.

An automated Pearson's correlation change classification (APC3) approach for GC/MS metabonomic data using total ion chromatograms (TICs).

A fully automated and computationally efficient Pearson's correlation change classification (APC3) approach is proposed and shown to have overall comparable performance with both an average accuracy and an average AUC of 0.89 ± 0.08 but is 3.9 to 7 times faster, easier to use and have low outlier susceptibility in contrast to other dimensional reduction and classification combinations using only the total ion chromatogram (TIC) intensities of GC/MS data. The use of only the TIC permits the possible application of APC3 to other metabonomic data such as LC/MS TICs or NMR spectra. A RapidMiner implementation is available for download at http://padel.nus.edu.sg/software/padelapc3.

Global urinary metabolic profiling procedures using gas chromatography-mass spectrometry.

The role of urinary metabolic profiling in systems biology research is expanding. This is because of the use of this technology for clinical diagnostic and mechanistic studies and for the development of new personalized health care and molecular epidemiology (population) studies. The methodologies commonly used for metabolic profiling are NMR spectroscopy, liquid chromatography mass spectrometry (LC/MS) and gas chromatography-mass spectrometry (GC/MS). In this protocol, we describe urine collection and storage, GC/MS and data preprocessing methods, chemometric data analysis and urinary marker metabolite identification. Results obtained using GC/MS are complementary to NMR and LC/MS. Sample preparation for GC/MS analysis involves the depletion of urea via treatment with urease, protein precipitation with methanol, and trimethylsilyl derivatization. The protocol described here facilitates the metabolic profiling of ∼400-600 metabolites in 120 urine samples per week.

Use of urine volatile organic compounds to discriminate tuberculosis patients from healthy subjects.

Development of noninvasive methods for tuberculosis (TB) diagnosis, with the potential to be administered in field situations, remains as an unmet challenge. A wide array of molecules are present in urine and reflect the pathophysiological condition of a subject. With infection, an alteration in the molecular constituents is anticipated, characterization of which may form a basis for TB diagnosis. In the present study volatile organic compounds (VOCs) in human urine derived from TB patients and healthy controls were identified and quantified using headspace gas chromatography/mass spectrometry (GC/MS). We found significant (p < 0.05) increase in the abundance of o-xylene (6.37) and isopropyl acetate (2.07) and decreased level of 3-pentanol (0.59), dimethylstyrene (0.37), and cymol (0.42) in TB patients compared to controls. These markers could discriminate TB from healthy controls and related diseases like lung cancer and chronic obstructive pulmonary disorder. This study suggests a possibility of using urinary VOCs for the diagnosis of human TB.

Comparative evaluation of software for retention time alignment of gas chromatography/time-of-flight mass spectrometry-based metabonomic data.

In chromatography-based metabonomic research, retention time (RT) alignment of chromatographic peaks poses a challenge for the accurate profiling of biomarkers. Although a number of RT alignment software has been reported, the performance of these software packages have not been comprehensively evaluated. This study aimed to evaluate the RT alignment accuracy of publicly available and commercial RT alignment software. Two gas chromatography/mass spectrometry (GC/MS) datasets acquired from a mixture of standard metabolites and human bladder cancer urine samples, were used to assess three publicly available software packages, MetAlign, MZmine and TagFinder, and two commercial applications comprising the Calibration feature and Statistical Compare of ChromaTOF software. The overall RT alignment accuracies in aligning standard compounds mixture were 93, 92, 74, 73 and 42% for Calibration feature, MZmine, MetAlign, Statistical Compare and TagFinder, respectively. Additionally, unique trends were observed for the individual software with regards to the different experimental conditions related to extent and direction of RT shifts. Conflicting performance was observed for human urine samples suggesting that RT misalignments still occurred despite the use of RT alignment software. While RT alignment remains an inevitable step in data preprocessing, metabonomic researchers are recommended to perform manual check on the RT alignment of important biomarkers as part of their validation process.

Metabolic footprinting of tumorigenic and nontumorigenic uroepithelial cells using two-dimensional gas chromatography time-of-flight mass spectrometry.

In this study, gas chromatography mass spectrometry (GC-MS) and two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC-TOFMS) were employed for the metabolic footprinting of a pair of immortalized human uroepithelial cells namely HUC-1 (nontumorigenic) and HUC T-2 (tumorigenic). Both HUC-1 and HUC T-2 cell lines were cultivated in 1 mL of Ham's F-12 media. Subsequent to 48 h of incubation, 200 microL of cell culture supernatant was protein-precipitated using 1.7 mL of methanol and an aliquot of 1.5 mL of the mixture was separated, dried, trimethylsilyl-derivatized, and analyzed using GC-MS and GCxGC-TOFMS. Metabolic profiles were analyzed using multivariate data analysis techniques to evaluate the changes of the metabolomes. Both GC-MS and GCxGC-TOFMS analyses showed distinct differences in metabolic phenotypes of the normal and tumorigenic human bladder cells (partial least squares-discriminant analysis (PLS-DA) of GCxGC-TOFMS data; two latent variables, R (2) X = 0.418, R (2) Y = 0.977 and Q (2) (cumulative) = 0.852). Twenty metabolites were identified as being statistically different between the two cell types. These metabolites revealed that several key metabolic pathways were perturbed in tumorigenic urothelial cells as compared to the normal cells. Application of GCxGC-TOFMS offered several advantages compared to classical one-dimensional GC-MS which include enhanced chromatographic resolution (without increase in analytical run time), increase in sensitivity, improved identification of metabolites, and also separation of reagent artifacts from the metabolite peaks. Our results reinforced the advantages of GCxGC-TOFMS and the role of metabolomics in characterizing bladder cancer biology using in vitro cell culture models.

Noninvasive urinary metabonomic diagnosis of human bladder cancer.

Cystoscopy is considered the gold standard for the clinical diagnosis of human bladder cancer (BC). As cystoscopy is expensive and invasive, it may compromise patients' compliance and account for the failure in detecting recurrent BC in some patients. In this paper, we investigated the role of urinary metabonomics in the diagnosis of human BC. Gas chromatography/time-of-flight mass spectrometry was applied for the urinary metabolic profiling of 24 BC patients and 51 non-BC controls. The acquired data were analyzed using multivariate principal component analysis followed by orthogonal partial least-squares discriminant analysis (OPLS-DA). Model validity was verified using permutation tests and receiver operating characteristic (ROC) analysis. BC patients were clearly distinguished from non-BC subjects based on their global urinary metabolic profiles (OPLS-DA, 4 latent variables, R(2)X = 0.420, R(2)Y = 0.912 and Q(2) (cumulative) = 0.245; ROC AUC of 0.90; 15 marker metabolites). One-hundred percent sensitivity in detecting BC was observed using urinary metabonomics versus 33% sensitivity achieved by urinary cytology. Additionally, urinary metabonomics exhibited potential in the staging and grading of bladder tumors. In summary, urinary metabonomics is amenable for the noninvasive diagnosis of human BC.

Development and validation of a gas chromatography/mass spectrometry metabonomic platform for the global profiling of urinary metabolites.

This paper presents a simple and reliable gas chromatography/mass spectrometry (GC/MS) method for the metabonomic analysis of human urine samples. The sample preparation involved the depletion of excess urea via treatment with urease and subsequent protein precipitation using ice-cold ethanol. An aliquot of the mixture was separated, dried, trimethylsilyl (TMS)-derivatized and 1.0 microL of the derivatized extract was injected into the GC/MS system via split injection (1:10). Approximately 150 putative metabolites belonging to different chemical classes were identified from the pooled human urine samples. All the identified metabolites were selected to evaluate precision and stability of the GC/MS assay. More than 95% of the metabolites demonstrated good reproducibility, with intra-day and inter-day precision values below 15%. Metabolic profiling of 53 healthy male and female urine samples in combination with pattern recognition techniques was performed to further validate the GC/MS metabolite profiling assay. Principal component analysis (PCA) followed by orthogonal partial least squares analysis (OPLS) revealed differences between urinary metabolite profiles of healthy male and female subjects. This validated GC/MS metabolic profiling method may be further applied to the metabonomic screening of urinary biomarkers in clinical studies.

Metabonomics investigation of human urine after ingestion of green tea with gas chromatography/mass spectrometry, liquid chromatography/mass spectrometry and (1)H NMR spectroscopy.

A method using gas chromatography/mass spectrometry (GC/MS), liquid chromatography/mass spectrometry (LC/MS) and (1)H NMR with pattern recognition tools such as principle components analysis (PCA) was used to study the human urinary metabolic profiles after the intake of green tea. From the normalized peak areas obtained from GC/MS and LC/MS and peak heights from (1)H NMR, statistical analyses were used in the identification of potential biomarkers. Metabolic profiling by GC/MS provided a different set of quantitative signatures of metabolites that can be used to characterize the molecular changes in human urine samples. A comparison of normalized metabonomics data for selected metabolites in human urine samples in the presence of potential overlapping peaks after tea ingestion from LC/MS and (1)H NMR showed the reliability of the current approach and method of normalization. The close agreements of LC/MS with (1)H NMR data showed that the effects of ion suppression in LC/MS for early eluting metabolites were not significant. Concurrently, the specificity of detecting the stated metabolites by (1)H NMR and LC/MS was demonstrated. Our data showed that a number of metabolites involved in glucose metabolism, citric acid cycle and amino acid metabolism were affected immediately after the intake of green tea. The proposed approach provided a more comprehensive picture of the metabolic changes after intake of green tea in human urine. The multiple analytical approach together with pattern recognition tools is a useful platform to study metabolic profiles after ingestion of botanicals and medicinal plants.

Gas chromatography/mass spectrometry in metabolic profiling of biological fluids.

One of the objectives of metabonomics is to identify subtle changes in metabolite profiles between biological systems of different physiological or pathological states. Gas chromatography mass spectrometry (GC/MS) is a widely used analytical tool for metabolic profiling in various biofluids, such as urine and blood due to its high sensitivity, peak resolution and reproducibility. The availability of the GC/MS electron impact (EI) spectral library further facilitates the identification of diagnostic biomarkers and aids the subsequent mechanistic elucidation of the biological or pathological variations. With the advent of new comprehensive two dimensional GC (GC x GC) coupled to time-of-flight mass spectrometry (TOFMS), it is possible to detect more than 1200 compounds in a single analytical run. In this review, we discuss the applications of GC/MS in the metabolic profiling of urine and blood, and discuss its advances in methodologies and technologies.

Determination of rosuvastatin in rat plasma by HPLC: Validation and its application to pharmacokinetic studies.

A specific, accurate, precise and reproducible high-performance liquid chromatography (HPLC) method was developed for the estimation of rosuvastatin (RST), a novel, synthetic and potent HMG-CoA inhibitor in rat plasma. The assay procedure involved simple liquid-liquid extraction of RST and internal standard (IS, ketoprofen) from a small plasma volume directly into acetonitrile. The organic layer was separated and evaporated under a gentle stream of nitrogen at 40 degrees C. The residue was reconstituted in the mobile phase and injected onto a Kromasil KR 100-5C18 column (4.6 x 250 mm, 5 microm). Mobile phase consisting of 0.05 m formic acid and acetonitrile (55:45, v/v) was used at a flow rate of 1.0 mL/min for the effective separation of RST and IS. The detection of the analyte peak was achieved by monitoring the eluate using a UV detector set at 240 nm. The ratio of peak area of analyte to IS was used for quantification of plasma samples. Nominal retention times of RST and IS were 8.6 and 12.5 min, respectively. The standard curve for RST was linear (r2 > 0.999) in the concentration range 0.02-10 microg/mL. Absolute recoveries of RST and IS were 85-110 and >100%, respectively, from rat plasma. The lower limit of quantification (LLOQ) of RST was 0.02 microg/mL. The inter- and intra-day precisions in the measurement of quality control (QC) samples, 0.02, 0.06, 1.6 and 8.0 microg/mL, were in the range 7.24-12.43% relative standard deviation (RSD) and 2.28-10.23% RSD, respectively. Accuracy in the measurement of QC samples was in the range 93.05-112.17% of the spiked nominal values. Both analyte and IS were stable in the battery of stability studies, viz. benchtop, autosampler and freeze-thaw cycles. RST was found to be stable for a period of 30 days on storage at -80 degrees C. The application of the assay to determine the pharmacokinetic disposition after a single oral dose to rats is described.