Pluskal T.,Okinawa Institute of Science and Technology |
Uehara T.,Eisai Co. |
Yanagida M.,Okinawa Institute of Science and Technology
Analytical Chemistry | Year: 2012
Mass spectrometry is commonly applied to qualitatively and quantitatively profile small molecules, such as peptides, metabolites, or lipids. Modern mass spectrometers provide accurate measurements of mass-to-charge ratios of ions, with errors as low as 1 ppm. Even such high mass accuracy, however, is not sufficient to determine the unique chemical formula of each ion, and additional algorithms are necessary. Here we present a universal software tool for predicting chemical formulas from high-resolution mass spectrometry data, developed within the MZmine 2 framework. The tool is based on the use of a combination of heuristic techniques, including MS/MS fragmentation analysis and isotope pattern matching. The performance of the tool was evaluated using a real metabolomic data set obtained with the Orbitrap MS detector. The true formula was correctly determined as the highest-ranking candidate for 79% of the tested compounds. The novel isotope pattern-scoring algorithm outperformed a previously published method in 64% of the tested Orbitrap spectra. The software described in this manuscript is freely available and its source code can be accessed within the MZmine 2 source code repository. © 2012 American Chemical Society.
Yu M.J.,Eisai Co.
Journal of Chemical Information and Modeling | Year: 2010
A conceptually simple, fully in silico model to predict total clearance of new compounds in humans is described. Based on the premise that similar molecules will exhibit similar pharmacokinetic properties, we used a k-nearest-neighbors (kNN) technique to predict total clearance by comparison with known reference agents. Molecular similarity was defined using readily calculated one- and two-dimensional molecular descriptors, and the reference set was obtained by combining the Obach and Berellini sets of human pharmacokinetic data. Neutral molecules and drugs whose biological activity is associated with a metal center were removed from the combined set. The remaining 462 compounds were partitioned into a training and external test set of 370 and 92 compounds, respectively. For acids, bases, zwitterions, and quaternary ammonium/pyridinium ions, average prediction accuracy was within two-fold of observed for the external test set (n = 92). Using a collection of 20 drugs from the literature with ≥3 preclinical animal species allometric scaling data, accuracy of the in silico kNN model was not as good as the rule of exponents, but better than simple allometry (SA), and approached that of combination multiexponential allometry (ME) as defined by the number of predictions with ≥50% error. For a collection of 18 drugs with two species (rat-dog) data, the kNN model outperformed both SA and combination ME using the same performance standard. Since the model is fully in silico and, therefore, capable of generating total clearance predictions in the absence of any experimental data, it can be used to help guide early drug discovery research efforts, such as virtual compound library screening, and analogue prioritization prior to chemical synthesis and biological evaluation. Model validation was accomplished using the external test set, three- and five-fold cross-validation and two different y-randomization techniques (y-shuffling and random number pseudodescriptors). © 2010 American Chemical Society.
Graczyk P.P.,Eisai Co.
Future Medicinal Chemistry | Year: 2013
JNK is involved in a broad range of physiological processes. Several inflammatory and neurodegenerative diseases, such as multiple sclerosis, Alzheimer's and Parkinson's disease have been linked with the dysregulated JNK pathway. Research on disease models using the relevant knockout mice has highlighted the importance of specific JNK isoformsin-particular disorders and has stimulated further efforts in the drug-discovery area. However, most of the experimental evidence for the efficacy of JNK inhibition in animal models is from studies using JNK inhibitors, which are not isoform selective. Some of the more recent compounds exhibit good oral bioavailability, CNS penetration and selectivity against the rest of the kinome. Efforts to design isoform-selective inhibitors have produced a number of examples with various selectivity profiles. This article presents recent progress in this area and comment on the role of isoform selectivity for efficacy. © 2013 Future Science Ltd.
Hanada T.,Eisai Co.
Expert Opinion on Drug Discovery | Year: 2014
Introduction: Perampanel is a novel AMPA receptor antagonist, approved in over 35 countries as an adjunctive therapy for the treatment of partial-onset seizures with or without secondarily generalized seizures in patients with epilepsy aged 12 years and older (18 years and older in Canada). These countries include the members of the European Union, the USA, Canada and Switzerland. The AMPA receptor antagonist, perampanel, is the first approved antiepileptic drug to inhibit excitation of postsynaptic membranes through the selective inhibition of glutamate receptors. Areas covered: This drug discovery case history focuses on the discovery and profiling of perampanel. It analyzes the pharmacological, behavioral and molecular mechanisms of perampanel and how they contribute to the therapeutic benefits of the drug. The article is based on the data reported in published preclinical and clinical studies, product labels and poster presentations. Expert opinion: Preclinical studies of perampanel have identified its broad-spectrum antiseizure effects in acute seizure models, with a narrow therapeutic index in the rotarod test similar to other AMPA receptor antagonists. This narrow therapeutic index is a potential problem for AMPA receptor antagonists. However, the discovery that perampanel has a very long half-life in humans, with gradual accumulation in plasma, could contribute to the development of tolerance. This, coupled with the identification of an optimal dosing strategy for individual patients, may help to maximize the utility of perampanel in the treatment of epilepsy. © 2014 Informa UK, Ltd.
Eisai Co. | Date: 2012-10-30
The present invention provides compounds, methods for the synthesis thereof and methods for the use thereof in the treatment of various disorders including inflammatory or autoimmune disorders, and disorders involving malignancy or increased angiogenesis.