Similarity metrics for ligands reflecting the similarity of the target proteins

In this study we evaluate how far the scope of similarity searching can be extended to identify not only ligands binding to the same target as the reference ligand(s) but also ligands of other homologous targets without initially known ligands. This "homology-based similarity searching" requires molecular representations reflecting the ability of a molecule to interact with target proteins. The Similog keys, which are introduced here as a new molecular representation, were designed to fulfill such requirements. They are based only on the molecular constitution and are counts of atom triplets. Each triplet is characterized by the graph distances and the types of its atoms. The atom-typing scheme classifies each atom by its function as H-bond donor or acceptor and by its electronegativity and bulkiness. In this study the Similog keys are investigated in retrospective in silico screening experiments and compared with other conformation independent molecular representations. Studied were molecules of the MDDR database for which the activity data was augmented by standardized target classification information from public protein classification databases. The MDDR molecule set was split randomly into two halves. The first half formed the candidate set. Ligands of four targets (dopamine D2 receptor, opioid delta-receptor, factor Xa serine protease, and progesterone receptor) were taken from the second half to form the respective reference sets. Different similarity calculation methods are used to rank the molecules of the candidate set by their similarity to each of the four reference sets. The accumulated counts of molecules binding to the reference target and groups of targets with decreasing homology to it were examined as a function of the similarity rank for each reference set and similarity method. In summary, similarity searching based on Unity 2D-fingerprints or Similog keys are found to be equally effective in the identification of molecules binding to the same target as the reference set. However, the application of the Similog keys is more effective in comparison with the other investigated methods in the identification of ligands binding to any target belonging to the same family as the reference target. We attribute this superiority to the fact that the Similog keys provide a generalization of the chemical elements and that the keys are counted instead of merely noting their presence or absence in a binary form. The second most effective molecular representation are the occurrence counts of the public ISIS key fragments, which like the Similog method, incorporates key counting as well as a generalization of the chemical elements. The results obtained suggest that ligands for a new target can be identified by the following three-step procedure: 1. Select at least one target with known ligands which is homologous to the new target. 2. Combine the known ligands of the selected target(s) to a reference set. 3. Search candidate ligands for the new targets by their similarity to the reference set using the Similog method. This clearly enlarges the scope of similarity searching from the classical application for a single target to the identification of candidate ligands for whole target families and is expected to be of key utility for further systematic chemogenomics exploration of previously well explored target families.     

Automated immobilized metal affinity chromatography/nano-liquid chromatography/electrospray ionization mass spectrometry platform for profiling protein phosphorylation sites

A versatile integrated system has been developed for the automated enrichment and analysis of phosphopeptides by immobilized metal affinity chromatography/nano-liquid chromatography/electrospray ionization mass spectrometry (IMAC/nano-LC/ESI-MS). This system utilizes two independently controlled high-performance liquid chromatography (HPLC) pumps, an autosampler and microvalves to prepare and elute samples into an ion trap mass spectrometer. The use of robust reversed-phase HPLC columns with integrated ESI emitter tips enables the reproducible detection and identification of low-femtomole quantities of phosphopeptides. The entire system is coordinated through a simple user interface by customized software. The ruggedness of the system is demonstrated by highly reproducible analyses of single and multi-protein digests, while its utility is demonstrated by the thorough evaluation of the relative immunoprecipitation efficiencies of several commercially available anti-phosphotyrosine antibodies.     

Precise predictions for same-sign W-boson scattering at the LHC

Vector-boson scattering processes are of great importance for the current run-II and future runs of the Large Hadron Collider. The presence of triple and quartic gauge couplings in the process gives access to the gauge sector of the Standard Model (SM) and possible new-physics contributions there. To test any new-physics hypothesis, sound knowledge of the SM contributions is necessary, with a precision which at least matches the experimental uncertainties of existing and forthcoming measurements. In this article we present a detailed study of the vector-boson scattering process with two positively-charged leptons and missing transverse momentum in the final state. In particular, we first carry out a systematic comparison of the various approximations that are usually performed for this kind of process against the complete calculation, at LO and NLO QCD accuracy. Such a study is performed both in the usual fiducial region used by experimental collaborations and in a more inclusive phase space, where the differences among the various approximations lead to more sizeable effects. Afterwards, we turn to predictions matched to parton showers, at LO and NLO: we show that on the one hand, the inclusion of NLO QCD corrections leads to more stable predictions, but on the other hand the details of the matching and of the parton-shower programs cause differences which are considerably larger than those observed at fixed order, even in the experimental fiducial region. We conclude with recommendations for experimental studies of vector-boson scattering processes.     

A Two-Surface Problem of the Electron Flow in a Semiconductor on the Basis of Kinetic Theory

A steady flow of electrons in a semiconductor between two parallel plane Ohmic contacts is studied on the basis of the semiconductor Boltzmann equation, assuming a relaxation-time collision term, and the Poisson equation for the electrostatic potential. A systematic asymptotic analysis of the Boltzmann–Poisson system for small Knudsen numbers (scaled mean free paths) is carried out in the case where the Debye length is of the same order as the distance between the contacts and where the applied potential is of the same order as the thermal potential. A system of drift-diffusion-type equations and their boundary conditions is obtained up to second order in the Knudsen number. A numerical comparison is made between the obtained system and the original Boltzmann–Poisson system.     

Crystal and molecular structures and experimentally determined charge densities of fluorinated ethenes

Crystals of various fluorinated ethenes were grown by in situ crystallization from their melts on a diffractometer, allowing the structures of tetrafluoroethene (C2F4), trifluoroethene (C2HF)3, 1,1-difluoroethene (C2H2F2), (E)-1,2-difluoroethene (C2H2F2), and (Z)-1,2-difluoroethene (C2H2F2) to be determined by X-ray crystallography. Unexpectedly, the C=C bond lengths show only small variations arising from fluorine substitution. These findings are supported by ab initio calculations at a DFT level of theory and the results of topological analyses of the experimentally determined and theoretically calculated charge densities.     

Statistical bootstrapping methods in VaR calculation

Monte Carlo methods are often applied to problems in finance especially in the area of risk calculation by the Value-atRisk (VaR) measure. Different applications of statistical resampling techniques are shown, specifically bootstrapping, to refine the computational results in different ways. Methods are provided for improving backtesting stability, acceleration of Monte Carlo VaR convergence by orders of magnitude, and incorporating covariance matrix uncertainty in VaR figures. Existing methods are applied and new solutions developed. Extensive numerical tests on large numbers of randomly generated portfolios prove the effectiveness of the suggested solutions.