Identification of Ligands with Tailored Selectivity: Strategies & Application

In the field of computer-aided drug design, docking is a computational tool, often used to evaluate the sterical and chemical complementarity between two molecules. This technique can be used to estimate the binding or non-binding of a small molecule to a protein binding site. The classical application of docking is to find those molecules within a large set of molecules that bind a certain target protein and modulate its biological activity. This setup can be considered as established for a single target protein. In contrast to this, the docking to multiple target structures offers new possible applications. It can be used, for example, to assess the binding profile of a ligand against a number of proteins. In this work, the applicability of docking is assessed in such a scenario where multiple target structures are used. The corresponding proteins mostly belong to the family of G protein-coupled receptors. This protein family is very large and numerous GPCRs have been identified as potential drug targets, explaining the their relevance in pharmaceutical research. The protein structures used herein have different relationships and thus represent different application scenarios. The first case study uses two structures belonging to different proteins. These proteins are CXCR3 and CXCR4, a pair of chemokine GPCRs. In this chapter, new ligands are identified that bind to these proteins and modulate their biological activity. More importantly, for each of these newly identified ligands it could be predicted using docking, whether this ligand binds only to one of the two target proteins or to both. This study proves the applicability of docking to identify ligands with tailored selectivity. In addition, these ligands show excellent binding affinities to their respective target or targets. In the following two studies, the docking to different structures of the same target protein is investigated. The first application aims at identifying ligands selective for either one of two isoforms of the zebrafish CXC receptor 4. Subsequently, multiple conformations of the chemokine receptor CCR5 are used to show that different starting structures can identify different ligands. Next to the plain identification of chemically new ligands, experimental hurdles to prove the biological activity of these molecules in a functional assay is discussed. These difficulties are based on the fact that docking evaluates the structural complementarity between molecules and protein structures rather than predicting the effect of these molecules on the proteins. In addition, GPCRs form a challenging set of target proteins, since their ligands can induce a variety of different effects. Finally, the general applicability of multi-target docking to a very large number of structures is investigated. For this evaluation, kinases are used as protein family since many more structures have been experimentally determined for these proteins compared to GPCRs as membrane proteins. First, using published experimental data, a dataset is created consisting of several hundred kinase structures and a set of small-molecule kinase inhibitors. This dataset is characterised by the availability of experimental binding data for each single kinase-inhibitor combination. These experimental data were subsequently compared to the docking results of each ligand into each single kinase structure. The results indicate that a reliable selectivity prediction for a ligand is highly demanding in such a large-scale setup and beyond current possibilities. However, it can be shown that the prediction accuracy of docking can be improved by normalising the docking scores over multiple ligands and proteins. Based on these findings, the idea of "protein decoys" is developed, which might in the future allow more accurate predictions of selectivity profiles using docking

Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?

The standard conclusion that is drawn from this empirical evidence is that many or most aggregate economic time series contain a unit root. However, it is important to note that in this empirical work the unit root is set up as the null hypothesis testing is carried out ensures that the null hypothesis is accepted unless there is strong evidence against it. Therefore, an alternative explanation for the common failure to reject a unit root is simply that most economic time series are not very informative about whether or not there is a unit root; or, equivalently, that standard unit root tests are not very powerful against relevant alternatives

Unprecedented chemical transformation: crystallographic evidence for 1,1,2,2-tetrahydroxyethane captured within an Fe6Dy3 single molecule magnet

A nonanuclear {Fe6Dy3} coordination cluster displaying SMM behaviour in which an unprecedented chemical transformation provides structural information for the existence of 1,1,2,2-tetrahydroxyethane is reported

Similarity- and substructure-based development of β2-adrenergic receptor ligands based on unusual scaffolds

The β2-adrenergic receptor (β2AR) is a G protein-coupled receptor (GPCR) and a well-explored target. Here, we report the discovery of 13 ligands, ten of which are novel, of this particular GPCR. They have been identified by similarity- and substructure-based searches using multiple ligands, which were described in an earlier study, as starting points. Of note, two of the molecules used as queries here distinguish themselves from other β2AR antagonists by their unique scaffold. The molecules described in this work allow us to explore the ligand space around the previously reported molecules in greater detail, leading to insights into their structure−activity relationship. We also report experimental binding and selectivity data and putative binding modes for the novel molecules

A Gravitational Wave Detector for Post Merger Neutron Stars: Beyond the Quantum Loss Limit of Michelson Fabry Perot Interferometer

Advanced gravitational-wave detectors that have made groundbreaking discoveries are Michelson interferometers with resonating optical cavities as their arms. As light travels at finite speed, these cavities are optimal for enhancing signals at frequencies below their bandwidth frequency. A small amount of optical loss will, however, significantly impact the high-frequency signals which are not optimally amplified. We find an elegant interferometer configuration with an "L-resonator" as the core, significantly surpassing the loss limited sensitivity of dual recycled Fabry Perot Michelson interferometers at high frequencies. Following this concept, we provide a broadband design of a 25 km detector with outstanding sensitivity between 2-4 kHz. We have performed Monte-Carlo population studies of binary neutron star mergers, given the most recent merger rate from the GWTC-3 catalog and several representative neutron star equations of state. We find that the new interferometer configuration significantly outperforms other third-generation detectors by a factor of 3 to 7 in the signal-to-noise ratio of the post-merger signal. Assuming a detection threshold with signal-to-noise ratio >5 and for the cases we have explored, the new design is the only detector that confidently achieves a detection rate larger than one per year, with the rate being 1 to 30 events per year.Comment: 12 pages, 9 figure

Out-of-surface vortices in spherical shells

The interplay of topological defects with curvature is studied for out-of-surface magnetic vortices in thin spherical nanoshells. In the case of easy-surface Heisenberg magnet it is shown that the curvature of the underlying surface leads to a coupling between the localized out-of-surface component of the vortex with its delocalized in-surface structure, i.e. polarity-chirality coupling.Comment: 6 pages, 4 figure

Magnetism in the Brown Dwarf Regime

A suite of discoveries in the last two decades demonstrate that we are now at a point where incorporating magnetic behavior is key for advancing our ability to characterize substellar and planetary systems. The next decade heralds the exciting maturation of the now-burgeoning field of brown dwarf magnetism, and investing now in brown dwarf magnetism will provide a key platform for exploring exoplanetary magnetism and habitability beyond the solar system. We anticipate significant discoveries including: the nature of substellar and planetary magnetic dynamos, the characterization of exo-aurora physics and brown dwarf magnetospheric environments, and the role of satellites in manifestations of substellar magnetic activity. These efforts will require significant new observational capabilities at radio and near infrared wavelengths, dedicated long-term monitoring programs, and committed support for the theoretical modeling efforts underpinning the physical processes of the magnetic phenomenaComment: Decadal 2020 science white pape

Optimal eddy viscosity for resolvent-based models of coherent structures in turbulent jets

Response modes computed via linear resolvent analysis of the turbulent mean-flow field have been shown to qualitatively capture characteristics of the observed turbulent coherent structures in both wall-bounded and free shear flows. To make such models predictive, the nonlinear forcing term must be closed either by including a self-consistent set of triadic interactions or through turbulence modeling. For the latter, several investigators have proposed using the mean-field eddy viscosity acting linearly on the fluctuation field. In this study, a data-driven approach is taken to quantitatively improve linear resolvent models by deducing an optimal eddy-viscosity field that maximizes the projection of the dominant resolvent mode to the energy-optimal coherent structure educed using spectral proper orthogonal decomposition (SPOD) of data from high-fidelity simulations. We use large-eddy simulation databases for round isothermal jets at subsonic, transonic, and supersonic conditions and show that the optimal eddy viscosity substantially improves the alignment between resolvent and SPOD modes, reaching over 90% alignment at those frequencies where the jet exhibits a low-rank response. We then consider a fixed model for the eddy viscosity and show that with the calibration of a single constant, the results are generally close to the optimal one. In particular, the use of a standard Reynolds-Averaged-Navier-Stokes (RANS) eddy-viscosity resolvent model, with a single scaling coefficient, provides substantial agreement between SPOD and resolvent modes for three turbulent jets and across the most energetic wavenumbers and frequencies