Computational Approaches to Drug Profiling and Drug-Protein Interactions

Despite substantial increases in R&D spending within the pharmaceutical industry, denovo drug design has become a time-consuming endeavour. High attrition rates led to a long period of stagnation in drug approvals. Due to the extreme costs associated with introducing a drug to the market, locating and understanding the reasons for clinical failure is key to future productivity. As part of this PhD, three main contributions were made in this respect. First, the web platform, LigNFam enables users to interactively explore similarity relationships between ‘drug like’ molecules and the proteins they bind. Secondly, two deep-learning-based binding site comparison tools were developed, competing with the state-of-the-art over benchmark datasets. The models have the ability to predict offtarget interactions and potential candidates for target-based drug repurposing. Finally, the open-source ScaffoldGraph software was presented for the analysis of hierarchical scaffold relationships and has already been used in multiple projects, including integration into a virtual screening pipeline to increase the tractability of ultra-large screening experiments. Together, and with existing tools, the contributions made will aid in the understanding of drug-protein relationships, particularly in the fields of off-target prediction and drug repurposing, helping to design better drugs faster

Classification of Protein-Binding Sites Using a Spherical Convolutional Neural Network

The analysis and comparison of protein-binding sites aid various applications in the drug discovery process, e.g., hit finding, drug repurposing, and polypharmacology. Classification of binding sites has been a hot topic for the past 30 years, and many different methods have been published. The rapid development of machine learning computational algorithms, coupled with the large volume of publicly available protein–ligand 3D structures, makes it possible to apply deep learning techniques in binding site comparison. Our method uses a cutting-edge spherical convolutional neural network based on the DeepSphere architecture to learn global representations of protein-binding sites. The model was trained on TOUGH-C1 and TOUGH-M1 data and validated with the ProSPECCTs datasets. Our results show that our model can (1) perform well in protein-binding site similarity and classification tasks and (2) learn and separate the physicochemical properties of binding sites. Lastly, we tested the model on a set of kinases, where the results show that it is able to cluster the different kinase subfamilies effectively. This example demonstrates the method’s promise for lead hopping within or outside a protein target, directly based on binding site information

Dynamics and energetics of trapped diurnal internal Kelvin waves around a midlatitude lsland

Author Posting. © American Meteorological Society, 2017. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 47 (2017): 2479-2498, doi:10.1175/JPO-D-16-0167.1.The generation of trapped and radiating internal tides around Izu‐Oshima Island located off Sagami Bay, Japan, is investigated using the three-dimensional Stanford Unstructured Nonhydrostatic Terrain-following Adaptive Navier–Stokes Simulator (SUNTANS) that is validated with observations of isotherm displacements in shallow water. The model is forced by barotropic tides, which generate strong baroclinic internal tides in the study region. Model results showed that when diurnal K1 barotropic tides dominate, resonance of a trapped internal Kelvin wave leads to large-amplitude internal tides in shallow waters on the coast. This resonance produces diurnal motions that are much stronger than the semidiurnal motions. The weaker, freely propagating, semidiurnal internal tides are generated on the western side of the island, where the M2 internal tide beam angle matches the topographic slope. The internal wave energy flux due to the diurnal internal tides is much higher than that of the semidiurnal tides in the study region. Although the diurnal internal tide energy is trapped, this study shows that steepening of the Kelvin waves produces high-frequency internal tides that radiate from the island, thus acting as a mechanism to extract energy from the diurnal motions.This study was supported by JST CREST Grant Number JPRMJCR12A6.2018-04-1

Memory-Relevant Mushroom Body Output Synapses Are Cholinergic

Memories are stored in the fan-out fan-in neural architectures of the mammalian cerebellum and hippocampus and the insect mushroom bodies. However, whereas key plasticity occurs at glutamatergic synapses in mammals, the neurochemistry of the memory-storing mushroom body Kenyon cell output synapses is unknown. Here we demonstrate a role for acetylcholine (ACh) in Drosophila. Kenyon cells express the ACh-processing proteins ChAT and VAChT, and reducing their expression impairs learned olfactory-driven behavior. Local ACh application, or direct Kenyon cell activation, evokes activity in mushroom body output neurons (MBONs). MBON activation depends on VAChT expression in Kenyon cells and is blocked by ACh receptor antagonism. Furthermore, reducing nicotinic ACh receptor subunit expression in MBONs compromises odor-evoked activation and redirects odor-driven behavior. Lastly, peptidergic corelease enhances ACh-evoked responses in MBONs, suggesting an interaction between the fast- and slow-acting transmitters. Therefore, olfactory memories in Drosophila are likely stored as plasticity of cholinergic synapses

HerMES: A Statistical Measurement of the Redshift Distribution of Herschel-SPIRE Sources Using the Cross-correlation Technique

The wide-area imaging surveys with the Herschel Space Observatory at submillimeter (sub-mm) wavelengths have now resulted in catalogs of the order of one-hundred-thousand dusty, starburst galaxies. These galaxies capture an important phase of galaxy formation and evolution, but, unfortunately, the redshift distribution of these galaxies, N(z), is still mostly uncertain due to limitations associated with counterpart identification at optical wavelengths and spectroscopic follow-up. We make a statistical estimate of N(z) using a clustering analysis of sub-mm galaxies detected at each of 250, 350 and 500 μm from the Herschel Multi-tiered Extragalactic Survey centered on the Boötes field. We cross-correlate Herschel galaxies against galaxy samples at optical and near-IR wavelengths from the Sloan Digital Sky Survey, the NOAO Deep Wide Field Survey, and the Spitzer Deep Wide Field Survey. We create optical and near-IR galaxy samples based on their photometric or spectroscopic redshift distributions and test the accuracy of those redshift distributions with similar galaxy samples defined with catalogs from the Cosmological Evolution Survey (COSMOS), which has superior spectroscopic coverage. We model the clustering auto- and cross-correlations of Herschel and optical/IR galaxy samples to estimate N(z) and clustering bias factors. The S_(350) > 20 mJy galaxies have a bias factor varying with redshift as b(z) = 1.0^(+1.0)_(–0.5)(1 + z)^1.2^(+0.3)_(–0.7). This bias and the redshift dependence is broadly in agreement with galaxies that occupy dark matter halos of mass in the range of 1012 to 10^(13) M_☉. We find that galaxy selections in all three Spectral and Photometric Imaging Receiver (SPIRE) bands share a similar average redshift, with = 1.8 ± 0.2 for 250 μm selected samples, and = 1.9 ± 0.2 for both 350 and 500 μm samples, while their distributions behave differently. For 250 μm selected galaxies we find the a larger number of sources with z ≤ 1 when compared with the subsequent two SPIRE bands, with 350 and 500 μm selected SPIRE samples having peaks in N(z) at progressively higher redshifts. We compare our clustering-based N(z) results to sub-mm galaxy model predictions in the literature, and with an estimate of N(z) using a stacking analysis of COSMOS 24 μm detections

A national appraisal of haemodialysis vascular access provision in Scotland

Purpose: Published registry data demonstrate longstanding variation in the utilisation of different vascular access (VA) modalities between Scottish renal units; this may reflect different clinical processes between centres. A comprehensive appraisal was undertaken to understand the processes underpinning VA creation and maintenance across Scotland. Methods: A mixed methods approach was utilised. Fifty-two semi-structured interviews were conducted with patients and clinicians in all ten, adult and paediatric, Scottish renal units. Interview transcripts were subjected to thematic analysis. Clinical activity data were prospectively collected for six weeks, and correlated with registry data. Results: VA accounts for a large clinical workload. There was significant inter-centre variation in the utilisation of different VA modalities, and patients described frustrating, dissatisfying experiences. VA creation and maintenance pathways functioned best when nephrologists, surgeons and radiologists were co-located on the same campus with close multi-disciplinary working, protected clinical time, and proactive VA maintenance. No unit routinely measured or discussed procedure outcomes or strategic aspects of their service. Conclusions: Varied clinical outcomes reflected varied clinical processes. Optimised clinical pathways, staff education and measurement of clinical outcomes may improve VA service quality and facilitate safer, more effective, patient-centred care

Panchromatic spectral energy distributions of Herschel sources

(abridged) Far-infrared Herschel photometry from the PEP and HerMES programs is combined with ancillary datasets in the GOODS-N, GOODS-S, and COSMOS fields. Based on this rich dataset, we reproduce the restframe UV to FIR ten-colors distribution of galaxies using a superposition of multi-variate Gaussian modes. The median SED of each mode is then fitted with a modified version of the MAGPHYS code that combines stellar light, emission from dust heated by stars and a possible warm dust contribution heated by an AGN. The defined Gaussian grouping is also used to identify rare sources. The zoology of outliers includes Herschel-detected ellipticals, very blue z~1 Ly-break galaxies, quiescent spirals, and torus-dominated AGN with star formation. Out of these groups and outliers, a new template library is assembled, consisting of 32 SEDs describing the intrinsic scatter in the restframe UV-to-submm colors of infrared galaxies. This library is tested against L(IR) estimates with and without Herschel data included, and compared to eight other popular methods often adopted in the literature. When implementing Herschel photometry, these approaches produce L(IR) values consistent with each other within a median absolute deviation of 10-20%, the scatter being dominated more by fine tuning of the codes, rather than by the choice of SED templates. Finally, the library is used to classify 24 micron detected sources in PEP GOODS fields. AGN appear to be distributed in the stellar mass (M*) vs. star formation rate (SFR) space along with all other galaxies, regardless of the amount of infrared luminosity they are powering, with the tendency to lie on the high SFR side of the "main sequence". The incidence of warmer star-forming sources grows for objects with higher specific star formation rates (sSFR), and they tend to populate the "off-sequence" region of the M*-SFR-z space.Comment: Accepted for publication in A&A. Some figures are presented in low resolution. The new galaxy templates are available for download at the address http://www.mpe.mpg.de/ir/Research/PEP/uvfir_temp

HerMES: the rest-frame UV emission and a lensing model for the z= 6.34 luminous dusty starburst galaxy HFLS3

We discuss the rest-frame ultraviolet emission from the starbursting galaxy HFLS3 at a redshift of 6.34. The galaxy was discovered in Herschel/SPIRE data due to its red color in the submillimeter wavelengths from 250 to 500 μm. Keck/NIRC2 K s -band adaptive optics imaging data showed two potential near-IR counterparts near HFLS3. Previously, the northern galaxy was taken to be in the foreground at z = 2.1, while the southern galaxy was assumed to be HFLS3's near-IR counterpart. The recently acquired Hubble/WFC3 and Advanced Camera for Surveys (ACS) imaging data show conclusively that both optically bright galaxies are in the foreground at z < 6. A new lensing model based on the Hubble imaging data and the millimeter-wave continuum emission yields a magnification factor of 2.2 ± 0.3, with a 95% confidence upper limit on the magnification of 3.5. When corrected for lensing, the instantaneous star formation rate is 1320 M ☉ yr–1, with the 95% confidence lower limit around 830 M ☉ yr–1. The dust and stellar masses of HFLS3 from the same spectral energy distribution (SED) models are at the level of 3 × 108 M ☉ and ~5 × 1010 M ☉, respectively, with large systematic uncertainties on assumptions related to the SED model. With Hubble/WFC3 images, we also find diffuse near-IR emission about 0.5 arcsec (~3 kpc) to the southwest of HFLS3 that remains undetected in the ACS imaging data. The emission has a photometric redshift consistent with either z ~ 6 or a dusty galaxy template at z ~ 2