A Multiple Classifier System Identifies Novel Cannabinoid CB2 Receptor Ligands

open access articleDrugs have become an essential part of our lives due to their ability to improve people’s health and quality of life. However, for many diseases, approved drugs are not yet available or existing drugs have undesirable side effects, making the pharmaceutical industry strive to discover new drugs and active compounds. The development of drugs is an expensive process, which typically starts with the detection of candidate molecules (screening) for an identified protein target. To this end, the use of high-performance screening techniques has become a critical issue in order to palliate the high costs. Therefore, the popularity of computer-based screening (often called virtual screening or in-silico screening) has rapidly increased during the last decade. A wide variety of Machine Learning (ML) techniques has been used in conjunction with chemical structure and physicochemical properties for screening purposes including (i) simple classifiers, (ii) ensemble methods, and more recently (iii) Multiple Classifier Systems (MCS). In this work, we apply an MCS for virtual screening (D2-MCS) using circular fingerprints. We applied our technique to a dataset of cannabinoid CB2 ligands obtained from the ChEMBL database. The HTS collection of Enamine (1.834.362 compounds), was virtually screened to identify 48.432 potential active molecules using D2-MCS. This list was subsequently clustered based on circular fingerprints and from each cluster, the most active compound was maintained. From these, the top 60 were kept, and 21 novel compounds were purchased. Experimental validation confirmed six highly active hits (>50% displacement at 10 μM and subsequent Ki determination) and an additional five medium active hits (>25% displacement at 10 μM). D2-MCS hence provided a hit rate of 29% for highly active compounds and an overall hit rate of 52%

Advances in GPCR Modeling Evaluated by the GPCR Dock 2013 Assessment: Meeting New Challenges

Despite tremendous successes of GPCR crystallography, the receptors with available structures represent only a small fraction of human GPCRs. An important role of the modeling community is to maximize structural insights for the remaining receptors and complexes. The community-wide GPCR Dock assessment was established to stimulate and monitor the progress in molecular modeling and ligand docking for GPCRs. The four targets in the present third assessment round presented new and diverse challenges for modelers, including prediction of allosteric ligand interaction and activation states in 5-hydroxytryptamine receptors 1B and 2B, and modeling by extremely distant homology for smoothened receptor. Forty-four modeling groups participated in the assessment. State-of-the-art modeling approaches achieved close-to-experimental accuracy for small rigid orthosteric ligands and models built by close homology, and they correctly predicted protein fold for distant homology targets. Predictions of long loops and GPCR activation states remain unsolved problems

DSM-III and DSM-III-R schizotypal symptoms in borderline personality disorder

The frequency of DSM-III and DSM-III-R schizotypal personality disorder (SPD) symptoms and diagnosis was explored in 39 inpatients classified as borderline by the Diagnostic Interview for Borderlines (DIB) and 19 inpatient major depressive disorder (MDD) controls. Most SPD symptoms in all groups, except the nondepressed borderlines, derived from social-interpersonal items. By DSM-III, 24 borderlines (62%) but only six controls (32%) had cognitive-perceptual SPD symptoms (P = .03), whereas by DSM-III-R only 14 borderlines (36%) and seven controls (37%) had such symptoms. Of the 24 borderlines showing cognitive-perceptual symptoms, 16 also had MDD, a significant difference from the non-MDD borderlines (P = .04). This difference disappears in DSM-III-R. The results suggest that some SPD symptoms in borderlines may be related to a concurrent affective episode.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28693/1/0000513.pd

Inter-rater agreement of comorbid DSM-IV personality disorders in substance abusers

<p>Abstract</p> <p>Background</p> <p>Little is known about the inter-rater agreement of personality disorders in clinical settings.</p> <p>Methods</p> <p>Clinicians rated 75 patients with substance use disorders on the DSM-IV criteria of personality disorders in random order, and on rating scales representing the severity of each.</p> <p>Results</p> <p>Convergent validity agreement was moderate (range for r = 0.55, 0.67) for cluster B disorders rated with DSM-IV criteria, and discriminant validity was moderate for eight of the ten personality disorders. Convergent validity of the rating scales was only moderate for antisocial and narcissistic personality disorder.</p> <p>Discussion</p> <p>Dimensional ratings may be used in research studies and clinical practice with some caution, and may be collected as one of several sources of information to describe the personality of a patient.</p

Rating of personality disorder features in popular movie characters

BACKGROUND: Tools for training professionals in rating personality disorders are few. We present one such tool: rating of fictional persons. However, before ratings of fictional persons can be useful, we need to know whether raters get the same results, when rating fictional characters. METHOD: Psychology students at the University of Copenhagen (N = 8) rated four different movie characters from four movies based on three systems: Global rating scales representing each of the 10 personality disorders in the DSM-IV, a criterion list of all criteria for all DSM-IV personality disorders in random order, and the Ten Item Personality Inventory for rating the five-factor model. Agreement was estimated based on intraclass-correlation. RESULTS: Agreement for rating scales for personality disorders ranged from 0.04 to 0.54. For personality disorder features based on DSM-IV criteria, agreement ranged from 0.24 to 0.89, and agreement for the five-factor model ranged from 0.05 to 0.88. The largest multivariate effect was observed for criteria count followed by the TIPI, followed by rating scales. Raters experienced personality disorder criteria as the easiest, and global personality disorder scales as the most difficult, but with significant variation between movies. CONCLUSION: Psychology students with limited or no clinical experience can agree well on the personality traits of movie characters based on watching the movie. Rating movie characters may be a way to practice assessment of personality

Overcoming Data Scarcity Related Issues for Landslide Susceptibility Modeling with Machine Learning

peer reviewedLandslide susceptibility maps can be a useful tool to support holistic urban planning in mountainous environments. Data-driven methods for landslide susceptibility modeling work well even in data scarce areas, and there is an increasing relevance of machine learning methods that help analyze efficiently large and complex datasets. In this contribution we present some of our study examples to show how data quality, quantity, complexity, and preparation can have major effects on the outcomes of landslide susceptibility modeling. The aforementioned aspects are too often neglected in spite of their relevance, both in data scarce, but also data rich areas. We also use these examples to discuss the way we evaluate landslide susceptibility models, as the spatial performance of landslide susceptibility maps often differs from the mathematical performance. We finally discuss the necessity of standards for input data, modeling results and result communication to improve the usability of landslide susceptibility models in urban planning

Tropical biogeomorphic seagrass landscapes for coastal protection:Persistence and wave attenuation during major storms events

The intensity of major storm events generated within the Atlantic Basin is projected to rise with the warming of the oceans, which is likely to exacerbate coastal erosion. Nature-based flood defence has been proposed as a sustainable and effective solution to protect coastlines. However, the ability of natural ecosystems to withstand major storms like tropical hurricanes has yet to be thoroughly tested. Seagrass meadows both stabilise sediment and attenuate waves, providing effective coastal protection services for sandy beaches. To examine the tolerance of Caribbean seagrass meadows to extreme storm events, and to investigate the extent of protection they deliver to beaches, we employed a combination of field surveys, biomechanical measurements and wave modelling simulations. Field surveys of sea- grass meadows before and after a direct hit by the category 5 Hurricane Irma documented that estab- lished seagrass meadows of Thalassia testudinum re- mained unaltered after the extreme storm event. The flexible leaves and thalli of seagrass and calci- fying macroalgae inhabiting the meadows were shown to sustain the wave forces that they are likely to experience during hurricanes. In addition, the seagrass canopy and the complex biogeomorphic landscape built by the seagrass meadows combine to significantly dissipate extreme wave forces, ensuring that erosion is minimised within sandy beach fore- shores. The persistence of the Caribbean seagrass meadows and their coastal protection services dur- ing extreme storm events ensures that a stable coastal ecosystem and beach foreshore is maintained in tropical regions

MyChEMBL: A Virtual Platform for Distributing Cheminformatics Tools and Open Data

MyChEMBL is an open virtual platform which provides a free, secure, standardised and easy to use chemoinformatics environment for bioactivity data mining, machine learning, application development, learning and teaching. The main technical features of myChEMBL along with its applications and future plans are discussed here.FWN – Publicaties zonder aanstelling Universiteit Leide

Molecular insights into disease-associated glutamate transporter (EAAT1 / SLC1A3) variants using in silico and in vitro approaches

Medicinal Chemistr