Docking scoring functions are notoriously weak predictors of binding affinity. They typically assign a common set of weights to the individual energy terms that contribute to the overall energy ...score; however, these weights should be gene family dependent. In addition, they incorrectly assume that individual interactions contribute toward the total binding affinity in an additive manner. In reality, noncovalent interactions often depend on one another in a nonlinear manner. In this paper, we show how the use of support vector machines (SVMs), trained by associating sets of individual energy terms retrieved from molecular docking with the known binding affinity of each compound from high-throughput screening experiments, can be used to improve the correlation between known binding affinities and those predicted by the docking program eHiTS. We construct two prediction models: a regression model trained using IC(50) values from BindingDB, and a classification model trained using active and decoy compounds from the Directory of Useful Decoys (DUD). Moreover, to address the issue of overrepresentation of negative data in high-throughput screening data sets, we have designed a multiple-planar SVM training procedure for the classification model. The increased performance that both SVMs give when compared with the original eHiTS scoring function highlights the potential for using nonlinear methods when deriving overall energy scores from their individual components. We apply the above methodology to train a new scoring function for direct inhibitors of Mycobacterium tuberculosis (M.tb) InhA. By combining ligand binding site comparison with the new scoring function, we propose that phosphodiesterase inhibitors can potentially be repurposed to target M.tb InhA. Our methodology may be applied to other gene families for which target structures and activity data are available, as demonstrated in the work presented here.
Employing a comprehensive dataset spanning 11 European Union countries, we provide novel insights on how country-level institutional factors affect differences in the extent of real earnings ...management (REM) activity by publicly listed and privately held firms (the ‘REM gap’). Thus, we explain why the public–private firm REM gap varies systematically across countries. Exploring the impact of country-level governance and legal environment, we observe the REM gap to be greater in weaker market settings and in jurisdictions with higher book-tax conformity, despite REM levels overall typically being lower in such jurisdictions. While overall REM levels are positively related with the strength of investor protection and the extent of disclosure requirements and negatively related with ownership concentration levels, these factors play only a modest role in explaining variations in the REM gap. Our broad-based evidence also provides consistent support for the existence internationally of a ‘partial substitution effect’ where increased (decreased) REM activity is offset to some extent, but not wholly, by reduced (increased) accruals-based earnings management activity. Our findings have important implications regarding the comparability of financial statement information provided by public and private firms.
Motivation: Protein assemblies are currently poorly represented in structural databases and their structural elucidation is a key goal in biology. Here we analyse clefts in protein surfaces, likely ...to correspond to binding ‘hot-spots’, and rank them according to sequence conservation and simple measures of physical properties including hydrophobicity, desolvation, electrostatic and van der Waals potentials, to predict which are involved in binding in the native complex. Results: The resulting differences between predicting binding-sites at protein–protein and protein–ligand interfaces are striking. There is a high level of prediction accuracy (≤93%) for protein–ligand interactions, based on the following attributes: van der Waals potential, electrostatic potential, desolvation and surface conservation. Generally, the prediction accuracy for protein–protein interactions is lower, with the exception of enzymes. Our results show that the ease of cleft desolvation is strongly predictive of interfaces and strongly maintained across all classes of protein-binding interface. Contact:r.m.jackson@leeds.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
We report a computational approach that integrates structural bioinformatics, molecular modelling and systems biology to construct a drug-target network on a structural proteome-wide scale. The ...approach has been applied to the genome of Mycobacterium tuberculosis (M.tb), the causative agent of one of today's most widely spread infectious diseases. The resulting drug-target interaction network for all structurally characterized approved drugs bound to putative M.tb receptors, we refer to as the 'TB-drugome'. The TB-drugome reveals that approximately one-third of the drugs examined have the potential to be repositioned to treat tuberculosis and that many currently unexploited M.tb receptors may be chemically druggable and could serve as novel anti-tubercular targets. Furthermore, a detailed analysis of the TB-drugome has shed new light on the controversial issues surrounding drug-target networks 1-3. Indeed, our results support the idea that drug-target networks are inherently modular, and further that any observed randomness is mainly caused by biased target coverage. The TB-drugome (http://funsite.sdsc.edu/drugome/TB) has the potential to be a valuable resource in the development of safe and efficient anti-tubercular drugs. More generally the methodology may be applied to other pathogens of interest with results improving as more of their structural proteomes are determined through the continued efforts of structural biology/genomics.
Motivation: Identifying the location of ligand binding sites on a protein is of fundamental importance for a range of applications including molecular docking, de novo drug design and structural ...identification and comparison of functional sites. Here, we describe a new method of ligand binding site prediction called Q-SiteFinder. It uses the interaction energy between the protein and a simple van der Waals probe to locate energetically favourable binding sites. Energetically favourable probe sites are clustered according to their spatial proximity and clusters are then ranked according to the sum of interaction energies for sites within each cluster. Results: There is at least one successful prediction in the top three predicted sites in 90% of proteins tested when using Q-SiteFinder. This success rate is higher than that of a commonly used pocket detection algorithm (Pocket-Finder) which uses geometric criteria. Additionally, Q-SiteFinder is twice as effective as Pocket-Finder in generating predicted sites that map accurately onto ligand coordinates. It also generates predicted sites with the lowest average volumes of the methods examined in this study. Unlike pocket detection, the volumes of the predicted sites appear to show relatively low dependence on protein volume and are similar in volume to the ligands they contain. Restricting the size of the pocket is important for reducing the search space required for docking and de novo drug design or site comparison. The method can be applied in structural genomics studies where protein binding sites remain uncharacterized since the 86% success rate for unbound proteins appears to be only slightly lower than that of ligand-bound proteins. Availability: Both Q-SiteFinder and Pocket-Finder have been made available online at http://www.bioinformatics.leeds.ac.uk/qsitefinder and http://www.bioinformatics.leeds.ac.uk/pocketfinder Contact: r.m.jackson@leeds.ac.uk
Cryogels consisting of polyvinyl alcohol and iron (II, III) oxide magnetic nanoparticles coated with a model drug-acetaminophen, were developed as a tunable platform for thermally triggered drug ...release, based on shape-selective heat transfer. Two different shapes of cryogels; discs and spherical caps, were formed via adding polymer-nanoparticle-drug mixtures into 3D printed molds, followed by freeze-thawing five times. No additional chemical crosslinking agents were used for gel formation and the iron oxide nanoparticles were coated with acetaminophen using only citric acid as a hydrogen-bonding linker. The two gel shapes displayed varying levels of acetaminophen release within 42-50 °C, which are ideal temperatures for hyperthermia induced drug delivery. The amount and time of drug-release were shown to be tunable by changing the temperature of the medium and the shape of the gels, while keeping all other factors (ex. gel volume, surface area, polymer/nanoparticle concentrations and drug-loading) constant. The discs displayed higher drug release at all temperatures while being particularly effective at lower temperatures (42-46 °C), in contrast to the spherical caps, which were more effective at higher temperatures (48-50 °C). Magnetic hyperthermia-mediated thermal imaging and temperature profiling studies revealed starkly different heat transfer behavior from the two shapes of gels. The disc gels retained their structural integrity up to 51 °C, while the spherical caps were stable up to 59 °C, demonstrating shape-dependent robustness. The highly customizable physicochemical features, facile synthesis, biocompatibility and tunable drug release ability of these cryogels offer potential for their application as a low cost, safe and effective platform for hyperthermia-mediated drug delivery, for external applications such as wound care/muscle repair or internal applications such as melanoma treatment.
Hyperbaric oxygen (HBO) has been advocated in the prevention and treatment of osteoradionecrosis (ORN) of the jaw after head and neck radiation therapy, but supporting evidence is weak. The aim of ...this randomized trial was to establish the benefit of HBO in the prevention of ORN after high-risk surgical procedures to the irradiated mandible.
HOPON was a randomized, controlled, phase 3 trial. Participants who required dental extractions or implant placement in the mandible with prior radiation therapy >50 Gy were recruited. Eligible patients were randomly assigned 1:1 to receive or not receive HBO. All patients received chlorhexidine mouthwash and antibiotics. For patients in the HBO arm, oxygen was administered in 30 daily dives at 100% oxygen to a pressure of 2.4 atmospheres absolute for 80 to 90 minutes. The primary outcome measure was the diagnosis of ORN 6 months after surgery, as determined by a blinded central review of clinical photographs and radiographs. The secondary endpoints included grade of ORN, ORN at other time points, acute symptoms, pain, and quality of life.
A total of 144 patients were randomized, and data from 100 patients were analyzed for the primary endpoint. The incidence of ORN at 6 months was 6.4% and 5.7% for the HBO and control groups, respectively (odds ratio, 1.13; 95% confidence interval, 0.14-8.92; P = 1). Patients in the hyperbaric arm had fewer acute symptoms but no significant differences in late pain or quality of life. Dropout was higher in the HBO arm, but the baseline characteristics of the groups that completed the trial were comparable between the 2 arms.
The low incidence of ORN makes recommending HBO for dental extractions or implant placement in the irradiated mandible unnecessary. These findings are in contrast with a recently published Cochrane review and previous trials reporting rates of ORN (non-HBO) of 14% to 30% and challenge a long-established standard of care.
The importance of the mix: The use of chloroform as solvent, the ligand (R)‐2 and VO(acac)2 as catalyst, and H2O2 as oxidant promotes the highly enantioselective oxidation of simple alkyl aryl ...sulfides 1 to give alkyl aryl sulfoxides (R)‐3 (see scheme). The success of this process partly derives from an efficient kinetic resolution of the product sulfoxides.
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