Modelling electric vehicles use: a survey on the methods

In the literature electric vehicle use is modelled using of a variety of approaches in power systems, energy and environmental analyses as well as in travel demand analysis. This paper provides a systematic review of these diverse approaches using a twofold classification of electric vehicle use representation, based on the time scale and on substantive differences in the modelling techniques. For time of day analysis of demand we identify activity-based modelling (ABM) as the most attractive because it provides a framework amenable for integrated cross-sector analyses, required for the emerging integration of the transport and electricity network. However, we find that the current examples of implementation of AMB simulation tools for EV-grid interaction analyses have substantial limitations. Amongst the most critical there is the lack of realism how charging behaviour is represented

SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules.

To be effective as a drug, a potent molecule must reach its target in the body in sufficient concentration, and stay there in a bioactive form long enough for the expected biologic events to occur. Drug development involves assessment of absorption, distribution, metabolism and excretion (ADME) increasingly earlier in the discovery process, at a stage when considered compounds are numerous but access to the physical samples is limited. In that context, computer models constitute valid alternatives to experiments. Here, we present the new SwissADME web tool that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar. Easy efficient input and interpretation are ensured thanks to a user-friendly interface through the login-free website http://www.swissadme.ch. Specialists, but also nonexpert in cheminformatics or computational chemistry can predict rapidly key parameters for a collection of molecules to support their drug discovery endeavours

The Novel μ-Opioid Receptor Antagonist GSK1521498 Decreases Both Alcohol Seeking and Drinking: Evidence from a New Preclinical Model of Alcohol Seeking.

Distinct environmental and conditioned stimuli influencing ethanol-associated appetitive and consummatory behaviors may jointly contribute to alcohol addiction. To develop an effective translational animal model that illuminates this interaction, daily seeking responses, maintained by alcohol-associated conditioned stimuli (CSs), need to be dissociated from alcohol drinking behavior. For this, we established a procedure whereby alcohol seeking maintained by alcohol-associated CSs is followed by a period during which rats have the opportunity to drink alcohol. This cue-controlled alcohol-seeking procedure was used to compare the effects of naltrexone and GSK1521498, a novel selective μ-opioid receptor antagonist, on both voluntary alcohol-intake and alcohol-seeking behaviors. Rederived alcohol-preferring, alcohol-nonpreferring, and high-alcohol-drinking replicate 1 line of rats (Indiana University) first received 18 sessions of 24 h home cage access to 10% alcohol and water under a 2-bottle choice procedure. They were trained subsequently to respond instrumentally for access to 15% alcohol under a second-order schedule of reinforcement, in which a prolonged period of alcohol-seeking behavior was maintained by contingent presentations of an alcohol-associated CS acting as a conditioned reinforcer. This seeking period was terminated by 20 min of free alcohol drinking access that achieved significant blood alcohol concentrations. The influence of pretreatment with either naltrexone (0.1-1-3 mg/kg) or GSK1521498 (0.1-1-3 mg/kg) before instrumental sessions was measured on both seeking and drinking behaviors, as well as on drinking in the 2-bottle choice procedure. Naltrexone and GSK1521498 dose-dependently reduced both cue-controlled alcohol seeking and alcohol intake in the instrumental context as well as alcohol intake in the choice procedure. However, GSK1521498 showed significantly greater effectiveness than naltrexone, supporting its potential use for promoting abstinence and preventing relapse in alcohol addiction

SwissTargetPrediction: a web server for target prediction of bioactive small molecules.

Bioactive small molecules, such as drugs or metabolites, bind to proteins or other macro-molecular targets to modulate their activity, which in turn results in the observed phenotypic effects. For this reason, mapping the targets of bioactive small molecules is a key step toward unraveling the molecular mechanisms underlying their bioactivity and predicting potential side effects or cross-reactivity. Recently, large datasets of protein-small molecule interactions have become available, providing a unique source of information for the development of knowledge-based approaches to computationally identify new targets for uncharacterized molecules or secondary targets for known molecules. Here, we introduce SwissTargetPrediction, a web server to accurately predict the targets of bioactive molecules based on a combination of 2D and 3D similarity measures with known ligands. Predictions can be carried out in five different organisms, and mapping predictions by homology within and between different species is enabled for close paralogs and orthologs. SwissTargetPrediction is accessible free of charge and without login requirement at http://www.swisstargetprediction.ch

Attracting cavities for docking. Replacing the rough energy landscape of the protein by a smooth attracting landscape.

Molecular docking is a computational approach for predicting the most probable position of ligands in the binding sites of macromolecules and constitutes the cornerstone of structure-based computer-aided drug design. Here, we present a new algorithm called Attracting Cavities that allows molecular docking to be performed by simple energy minimizations only. The approach consists in transiently replacing the rough potential energy hypersurface of the protein by a smooth attracting potential driving the ligands into protein cavities. The actual protein energy landscape is reintroduced in a second step to refine the ligand position. The scoring function of Attracting Cavities is based on the CHARMM force field and the FACTS solvation model. The approach was tested on the 85 experimental ligand-protein structures included in the Astex diverse set and achieved a success rate of 80% in reproducing the experimental binding mode starting from a completely randomized ligand conformer. The algorithm thus compares favorably with current state-of-the-art docking programs

The improvement of the best practice guidelines for preimplantation genetic diagnosis of cystic fibrosis: toward an international consensus

Cystic fibrosis (CF) is one of the most common indications for preimplantation genetic diagnosis (PGD) for single gene disorders, giving couples the opportunity to conceive unaffected children without having to consider termination of pregnancy. However, there are no available standardized protocols, so that each center has to develop its own diagnostic strategies and procedures. Furthermore, reproductive decisions are complicated by the diversity of disease-causing variants in the CFTR (cystic fibrosis transmembrane conductance regulator) gene and the complexity of correlations between genotypes and associated phenotypes, so that attitudes and practices toward the risks for future offspring can vary greatly between countries. On behalf of the EuroGentest Network, eighteen experts in PGD and/or molecular diagnosis of CF from seven countries attended a workshop held in Montpellier, France, on 14 December 2011. Building on the best practice guidelines for amplification-based PGD established by ESHRE (European Society of Human Reproduction and Embryology), the goal of this meeting was to formulate specific guidelines for CF-PGD in order to contribute to a better harmonization of practices across Europe. Different topics were covered including variant nomenclature, inclusion criteria, genetic counseling, PGD strategy and reporting of results. The recommendations are summarized here, and updated information on the clinical significance of CFTR variants and associated phenotypes is presented

Patient-specific Bacteroides genome variants in pouchitis

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in mBio 7 (2016): e01713-16, doi:10.1128/mBio.01713-16.A 2-year longitudinal microbiome study of 22 patients who underwent colectomy with an ileal pouch anal anastomosis detected significant increases in distinct populations of Bacteroides during 9 of 11 patient visits that coincided with inflammation (pouchitis). Oligotyping and metagenomic short-read annotation identified Bacteroides populations that occurred in early samples, bloomed during inflammation, and reappeared after antibiotic treatment. Targeted cultivation of Bacteroides isolates from the same individual at multiple time points and from several patients detected subtle genomic changes, including the identification of rapidly evolving genomic elements that differentiate isogenic strains of Bacteroides fragilis from the mucosa versus lumen. Each patient harbored Bacteroides spp. that are closely related to commonly occurring clinical isolates, including Bacteroides ovatus, B. thetaiotaomicron, B. vulgatus, and B. fragilis, which contained unique loci in different patients for synthesis of capsular polysaccharides. The presence of unique Bacteroides capsular polysaccharide loci within different hosts and between the lumen and mucosa may represent adaptations to stimulate, suppress, and evade host-specific immune responses at different microsites of the ileal pouch.Leona M. and Harry B. Helmsley Charitable Trust; Bay and Paul Foundations; Frank R. Lillie Research Innovation Award; Gastrointestinal Research Foundation of Chicag

The shape of things to come? Expanding the inequality and grievance model for civil war forecasts with event data

© The Author(s) 2017. We examine if dynamic information from event data can help improve on a model attempting to forecast civil war using measures reflecting plausible motivation and grievances. Buhaug, Cederman, and Gleditsch predict the risk of civil war using a horizontal inequality model with measures reflecting motivation and relevant group characteristics at the country level. The predictions from their model outperform in an out-of-sample forecast conventional countrylevel models of civil war, emphasizing vertical inequality and country characteristics. However, most grievance measures change little over time. We surmise that a model reflecting potential motivation for conflict can be improved with more dynamic information on mobilization and the behavior of actors. Our conjecture receives some support in the empirical analysis, where we consider both conflict onset and termination over territorial and governmental incompatibilities in the Uppsala/PRIO Armed Conflict Data, and find some evidence that event data can help improve forecasts. Moreover, models with the original grievance measures do better than purely event based models, supporting our claim that both structure and event based components can add value to conflict prediction models. However, the contribution of events to improving predictive power is modest and not entirely consistent, and some types of conflict events seem easier to forecast than others

Application of the SwissDrugDesign Online Resources in Virtual Screening.

SwissDrugDesign is an important initiative led by the Molecular Modeling Group of the SIB Swiss Institute of Bioinformatics. This project provides a collection of freely available online tools for computer-aided drug design. Some of these web-based methods, i.e., SwissSimilarity and SwissTargetPrediction, were especially developed to perform virtual screening, while others such as SwissADME, SwissDock, SwissParam and SwissBioisostere can find applications in related activities. The present review aims at providing a short description of these methods together with examples of their application in virtual screening, where SwissDrugDesign tools successfully supported the discovery of bioactive small molecules