973 resultados para ACCURATE DOCKING
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In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.
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The physical disector is a method of choice for estimating unbiased neuron numbers; nevertheless, calibration is needed to evaluate each counting method. The validity of this method can be assessed by comparing the estimated cell number with the true number determined by a direct counting method in serial sections. We reconstructed a 1/5 of rat lumbar dorsal root ganglia taken from two experimental conditions. From each ganglion, images of 200 adjacent semi-thin sections were used to reconstruct a volumetric dataset (stack of voxels). On these stacks the number of sensory neurons was estimated and counted respectively by physical disector and direct counting methods. Also, using the coordinates of nuclei from the direct counting, we simulate, by a Matlab program, disector pairs separated by increasing distances in a ganglion model. The comparison between the results of these approaches clearly demonstrates that the physical disector method provides a valid and reliable estimate of the number of sensory neurons only when the distance between the consecutive disector pairs is 60 microm or smaller. In these conditions the size of error between the results of physical disector and direct counting does not exceed 6%. In contrast when the distance between two pairs is larger than 60 microm (70-200 microm) the size of error increases rapidly to 27%. We conclude that the physical dissector method provides a reliable estimate of the number of rat sensory neurons only when the separating distance between the consecutive dissector pairs is no larger than 60 microm.
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Numerous studies have documented subtle but consistent sex differences in self-reports and observer-ratings of five-factor personality traits, and such effects were found to show well- defined developmental trajectories and remarkable similarity across nations. In contrast, very little is known about perceived gender differences in five-factor traits in spite of their potential implications for gender biases at the interpersonal and societal level. In particular, it is not clear how perceived gender differences in five-factor personality vary across age groups and national contexts and to what extent they accurately reflect assessed sex differences in personality. To address these questions, we analyzed responses from 3,323 individuals across 26 nations (mean age = 22.3 years, 31% male) who were asked to rate the five-factor personality traits of typical men or women in three age groups (adolescent, adult, and older adult) in their respective nations. Raters perceived women as slightly higher in openness, agreeableness, and conscientiousness as well as some aspects of extraversion and neuroticism. Perceived gender differences were fairly consistent across nations and target age groups and mapped closely onto assessed sex differences in self- and observer-rated personality. Associations between the average size of perceived gender differences and national variations in sociodemographic characteristics, value systems, or gender equality did not reach statistical significance. Findings contribute to our understanding of the underlying mechanisms of gender stereotypes of personality and suggest that perceptions of actual sex differences may play a more important role than culturally based gender roles and socialization processes.
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Abstract
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Age trajectories for personality traits are known to be similar across cultures. To address whether stereotypes of age groups reflect these age-related changes in personality, we asked participants in 26 countries (N = 3,323) to rate typical adolescents, adults, and old persons in their own country. Raters across nations tended to share similar beliefs about different age groups; adolescents were seen as impulsive, rebellious, undisciplined, preferring excitement and novelty, whereas old people were consistently considered lower on impulsivity, activity, antagonism, and Openness. These consensual age group stereotypes correlated strongly with published age differences on the five major dimensions of personality and most of 30 specific traits, using as criteria of accuracy both self-reports and observer ratings, different survey methodologies, and data from up to 50 nations. However, personal stereotypes were considerably less accurate, and consensual stereotypes tended to exaggerate differences across age groups.
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Proper and rapid diagnosis of orthopedic device-related infection is important for successful treatment. Sonication has been shown to improve the diagnostic performance. We hypothesized that the combination of sonication with a novel method called microcalorimetry will further improve and accelerate the diagnosis of implant infection. We prospectively included 39 consecutive patients (mean age 59 years, 62% males) at our institution from whom 29 orthopedic prostheses and 10 osteosynthesis material were explanted. The explanted device was sonicated. The resulting sonication fluid was analyzed using microcalorimetry. Using standardized criteria to define orthopedic device-related infection, 12 cases (31%) were defined as infected. In all, positive periprosthetic tissue cultures were found. The sensitivity and specificity of microcalorimetry of sonication fluid were 100% and 97%, respectively. Mean time to detection, defined as time to reach a rising heat flow signal of 20 µW measured after equilibiration needed to get accurate measurement, was 10.9 h. In summary, microcalorimetry of sonication fluid is a reliable and a fast method in detecting the presence of microorganisms in orthopedic device-related infection. © 2013 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 31:1700-1703, 2013.
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Molecular docking softwares are one of the important tools of modern drug development pipelines. The promising achievements of the last 10 years emphasize the need for further improvement, as reflected by several recent publications (Leach et al., J Med Chem 2006, 49, 5851; Warren et al., J Med Chem 2006, 49, 5912). Our initial approach, EADock, showed a good performance in reproducing the experimental binding modes for a set of 37 different ligand-protein complexes (Grosdidier et al., Proteins 2007, 67, 1010). This article presents recent improvements regarding the scoring and sampling aspects over the initial implementation, as well as a new seeding procedure based on the detection of cavities, opening the door to blind docking with EADock. These enhancements were validated on 260 complexes taken from the high quality Ligand Protein Database [LPDB, (Roche et al., J Med Chem 2001, 44, 3592)]. Two issues were identified: first, the quality of the initial structures cannot be assumed and a manual inspection and/or a search in the literature are likely to be required to achieve the best performance. Second the description of interactions involving metal ions still has to be improved. Nonetheless, a remarkable success rate of 65% was achieved for a large scale blind docking assay, when considering only the top ranked binding mode and a success threshold of 2 A RMSD to the crystal structure. When looking at the five-top ranked binding modes, the success rate increases up to 76%. In a standard local docking assay, success rates of 75 and 83% were obtained, considering only the top ranked binding mode, or the five top binding modes, respectively.
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Pseudoachondroplasia (PSACH) and multiple epiphyseal dysplasia (MED) are relatively common skeletal dysplasias resulting in short-limbed dwarfism, joint pain, and stiffness. PSACH and the largest proportion of autosomal dominant MED (AD-MED) results from mutations in cartilage oligomeric matrix protein (COMP); however, AD-MED is genetically heterogenous and can also result from mutations in matrilin-3 (MATN3) and type IX collagen (COL9A1, COL9A2, and COL9A3). In contrast, autosomal recessive MED (rMED) appears to result exclusively from mutations in sulphate transporter solute carrier family 26 (SLC26A2). The diagnosis of PSACH and MED can be difficult for the nonexpert due to various complications and similarities with other related diseases and often mutation analysis is requested to either confirm or exclude the diagnosis. Since 2003, the European Skeletal Dysplasia Network (ESDN) has used an on-line review system to efficiently diagnose cases referred to the network prior to mutation analysis. In this study, we present the molecular findings in 130 patients referred to ESDN, which includes the identification of novel and recurrent mutations in over 100 patients. Furthermore, this study provides the first indication of the relative contribution of each gene and confirms that they account for the majority of PSACH and MED.
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AIMS: Managing patients with alcohol dependence includes assessment for heavy drinking, typically by asking patients. Some recommend biomarkers to detect heavy drinking but evidence of accuracy is limited. METHODS: Among people with dependence, we assessed the performance of disialo-carbohydrate-deficient transferrin (%dCDT, ≥1.7%), gamma-glutamyltransferase (GGT, ≥66 U/l), either %dCDT or GGT positive, and breath alcohol (> 0) for identifying 3 self-reported heavy drinking levels: any heavy drinking (≥4 drinks/day or >7 drinks/week for women, ≥5 drinks/day or >14 drinks/week for men), recurrent (≥5 drinks/day on ≥5 days) and persistent heavy drinking (≥5 drinks/day on ≥7 consecutive days). Subjects (n = 402) with dependence and current heavy drinking were referred to primary care and assessed 6 months later with biomarkers and validated self-reported calendar method assessment of past 30-day alcohol use. RESULTS: The self-reported prevalence of any, recurrent and persistent heavy drinking was 54, 34 and 17%. Sensitivity of %dCDT for detecting any, recurrent and persistent self-reported heavy drinking was 41, 53 and 66%. Specificity was 96, 90 and 84%, respectively. %dCDT had higher sensitivity than GGT and breath test for each alcohol use level but was not adequately sensitive to detect heavy drinking (missing 34-59% of the cases). Either %dCDT or GGT positive improved sensitivity but not to satisfactory levels, and specificity decreased. Neither a breath test nor GGT was sufficiently sensitive (both tests missed 70-80% of cases). CONCLUSIONS: Although biomarkers may provide some useful information, their sensitivity is low the incremental value over self-report in clinical settings is questionable.
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BACKGROUND: Deep brain stimulation (DBS) is recognized as an effective treatment for movement disorders. We recently changed our technique, limiting the number of brain penetrations to three per side. OBJECTIVES: The first aim was to evaluate the electrode precision on both sides of surgery since we implemented this surgical technique. The second aim was to analyse whether or not the electrode placement was improved with microrecording and macrostimulation. METHODS: We retrospectively reviewed operation protocols and MRIs of 30 patients who underwent bilateral DBS. For microrecording and macrostimulation, we used three parallel channels of the 'Ben Gun' centred on the MRI-planned target. Pre- and post-operative MRIs were merged. The distance between the planned target and the centre of the implanted electrode artefact was measured. RESULTS: There was no significant difference in targeting precision on both sides of surgery. There was more intra-operative adjustment of the second electrode positioning based on microrecording and macrostimulation, which allowed to significantly approach the MRI-planned target on the medial-lateral axis. CONCLUSION: There was more electrode adjustment needed on the second side, possibly in relation with brain shift. We thus suggest performing a single central track with electrophysiological and clinical assessment, with multidirectional exploration on demand for suboptimal clinical responses.
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BACKGROUND: Recent neuroimaging studies suggest that value-based decision-making may rely on mechanisms of evidence accumulation. However no studies have explicitly investigated the time when single decisions are taken based on such an accumulation process. NEW METHOD: Here, we outline a novel electroencephalography (EEG) decoding technique which is based on accumulating the probability of appearance of prototypical voltage topographies and can be used for predicting subjects' decisions. We use this approach for studying the time-course of single decisions, during a task where subjects were asked to compare reward vs. loss points for accepting or rejecting offers. RESULTS: We show that based on this new method, we can accurately decode decisions for the majority of the subjects. The typical time-period for accurate decoding was modulated by task difficulty on a trial-by-trial basis. Typical latencies of when decisions are made were detected at ∼500ms for 'easy' vs. ∼700ms for 'hard' decisions, well before subjects' response (∼340ms). Importantly, this decision time correlated with the drift rates of a diffusion model, evaluated independently at the behavioral level. COMPARISON WITH EXISTING METHOD(S): We compare the performance of our algorithm with logistic regression and support vector machine and show that we obtain significant results for a higher number of subjects than with these two approaches. We also carry out analyses at the average event-related potential level, for comparison with previous studies on decision-making. CONCLUSIONS: We present a novel approach for studying the timing of value-based decision-making, by accumulating patterns of topographic EEG activity at single-trial level.
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There is little consensus regarding how verticality (social power, dominance, and status) is related to accurate interpersonal perception. The relation could be either positive or negative, and there could be many causal processes at play. The present article discusses the theoretical possibilities and presents a meta-analysis of this question. In studies using a standard test of interpersonal accuracy, higher socioeconomic status (SES) predicted higher accuracy defined as accurate inference about the meanings of cues; also, higher experimentally manipulated vertical position predicted higher accuracy defined as accurate recall of others' words. In addition, although personality dominance did not predict accurate inference overall, the type of personality dominance did, such that empathic/responsible dominance had a positive relation and egoistic/aggressive dominance had a negative relation to accuracy. In studies involving live interaction, higher experimentally manipulated vertical position produced lower accuracy defined as accurate inference about cues; however, methodological problems place this result in doubt.
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We address the challenges of treating polarization and covalent interactions in docking by developing a hybrid quantum mechanical/molecular mechanical (QM/MM) scoring function based on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. To benchmark this scoring function within the EADock DSS docking algorithm, we created a publicly available dataset of high-quality X-ray structures of zinc metalloproteins ( http://www.molecular-modelling.ch/resources.php ). For zinc-bound ligands (226 complexes), the QM/MM scoring yielded a substantially improved success rate compared to the classical scoring function (77.0% vs 61.5%), while, for allosteric ligands (55 complexes), the success rate remained constant (49.1%). The QM/MM scoring significantly improved the detection of correct zinc-binding geometries and improved the docking success rate by more than 20% for several important drug targets. The performance of both the classical and the QM/MM scoring functions compare favorably to the performance of AutoDock4, AutoDock4Zn, and AutoDock Vina.
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Introduction La stimulation cérébrale profonde est reconnue comme étant un traitement efficace des pathologies du mouvement. Nous avons récemment modifié notre technique chirurgicale, en limitant le nombre de pénétrations intracérébrales à trois par hémisphère. Objectif Le premier objectif de cette étude est d'évaluer la précision de l'électrode implantée des deux côtés de la chirurgie, depuis l'implémentation de cette technique chirurgicale. Le deuxième objectif est d'étudier si l'emplacement de l'électrode implantée était amélioré grâce à l'électrophysiologie. Matériel et méthode Il s'agit d'une étude rétrospective reprenant les protocoles opératoires et imageries à résonnance magnétique (IRM) cérébrales de 30 patients ayant subi une stimulation cérébrale profonde bilatérale. Pour l'électrophysiologie, nous avons utilisé trois canules parallèles du « Ben Gun », centrées sur la cible planifiée grâce à l'IRM. Les IRM pré- et post-opératoires ont été fusionnées. La distance entre la cible planifiée et le centre de l'artéfact de l'électrode implantée a été mesurée. Résultats Il n'y a pas eu de différence significative concernant la précision du ciblage des deux côtés (hémisphères) de la chirurgie. Il y a eu plus d'ajustements peropératoires du deuxième côté de la chirurgie, basé sur l'électrophysiologie, ce qui a permis d'approcher de manière significative la cible planifiée grâce à l'IRM, sur l'axe médio- latéral. Conclusion Il y a plus d'ajustements nécessaires de la position de la deuxième électrode, possiblement en lien avec le « brain shift ». Nous suggérons de ce fait d'utiliser une trajectoire d'électrode centrale accompagnée par de l'électrophysiologie, associé à une évaluation clinique. En cas de résultat clinique sub-optimal, nous proposons d'effectuer une exploration multidirectionnelle.