60 research outputs found
Target highlights in CASP14 : Analysis of models by structure providers
Abstract The biological and functional significance of selected CASP14 targets are described by the authors of the structures. The authors highlight the most relevant features of the target proteins and discuss how well these features were reproduced in the respective submitted predictions. The overall ability to predict three-dimensional structures of proteins has improved remarkably in CASP14, and many difficult targets were modelled with impressive accuracy. For the first time in the history of CASP, the experimentalists not only highlighted that computational models can accurately reproduce the most critical structural features observed in their targets, but also envisaged that models could serve as a guidance for further studies of biologically-relevant properties of proteins. This article is protected by copyright. All rights reserved.Peer reviewe
Robust kernel distance multivariate control chart using support vector principles
It is important to monitor manufacturing processes in order to improve product
quality and reduce production cost. Statistical Process Control (SPC) is the
most commonly used method for process monitoring, in particular making
distinctions between variations attributed to normal process variability to
those caused by ‘special causes’. Most SPC and multivariate SPC (MSPC) methods
are parametric in that they make assumptions about the distributional properties
and autocorrelation structure of in-control process parameters, and, if
satisfied, are effective in managing false alarms/-positives and false-
negatives. However, when processes do not satisfy these assumptions, the
effectiveness of SPC methods is compromised. Several non-parametric control
charts based on sequential ranks of data depth measures have been proposed in
the literature, but their development and implementation have been rather slow
in industrial process control. Several non-parametric control charts based on
machine learning principles have also been proposed in the literature to
overcome some of these limitations. However, unlike conventional SPC methods,
these non-parametric methods require event data from each out-of-control process
state for effective model building. The paper presents a new non-parametric
multivariate control chart based on kernel distance that overcomes these
limitations by employing the notion of one-class classification based on support
vector principles. The chart is non-parametric in that it makes no assumptions
regarding the data probability density and only requires ‘normal’ or in-control
data for effective representation of an in-control process. It does, however,
make an explicit provision to incorporate any available data from out-of-control
process states. Experimental evaluation on a variety of benchmarking datasets
suggests that the proposed chart is effective for process mo
Design and synthesis of polycyclic indoles under green conditions via Fischer indolization
A simple and useful synthetic route to aza-polyquinane derivatives involving Fischer indolization under green conditions has been demonstrated. Selenium dioxide is found to be useful for oxidizing some of these indole derivatives
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HipBA-promoter structures reveal the basis of heritable multidrug tolerance
Exploiting location and contextual information to develop a comprehensive framework for proactive handover in heterogeneous environments
The development and deployment of several wireless
and cellular networks mean that users will demand to be always connected as they move around. Mobile nodes will therefore have several interfaces and connections will be seamlessly switched among available networks using vertical handover techniques. Proactive handover mechanisms can be combined with the deployment of a number of location-based systems that provide location information to a very high degree of accuracy in different contexts. Furthermore, this new environment will also allow contextual information such as user profiles as well as the availability of local services to be combined to provide optimal
communications for mobile users. The goal of this paper is
therefore to explore the development of a comprehensive framework for achieving optimal communication in heterogeneous wireless environments using location and contextual information to provide efficient handover mechanisms. Using location-based techniques, it is possible to demonstrate that the Time Before Vertical Handover as well as the Network Dwell Time can be accurately estimated. These techniques are dependent on accurately estimating the handover radius. This paper investigates how location and context awareness can be used to estimate the best handover radius. The paper also explores how such techniques may be integrated into the Y-Comm architecture which is being used to explore the development of future mobile networks. Finally, the paper highlights the use of ontological
techniques as a mechanism for specifying and prototyping such systems
Bulk-Phase Ion Conduction in Cocrystalline LiCl·<i>N</i>,<i>N</i>‑Dimethylformamide: A New Paradigm for Solid Electrolytes Based upon the Pearson Hard–Soft Acid–Base Concept
Bulk-Phase Ion Conduction in Cocrystalline LiCl·<i>N</i>,<i>N</i>‑Dimethylformamide: A New Paradigm
for Solid Electrolytes Based upon the Pearson Hard–Soft Acid–Base
Concep
Bulk-Phase Ion Conduction in Cocrystalline LiCl·<i>N</i>,<i>N</i>‑Dimethylformamide: A New Paradigm for Solid Electrolytes Based upon the Pearson Hard–Soft Acid–Base Concept
Bulk-Phase Ion Conduction in Cocrystalline LiCl·<i>N</i>,<i>N</i>‑Dimethylformamide: A New Paradigm
for Solid Electrolytes Based upon the Pearson Hard–Soft Acid–Base
Concep
Design, docking, MD simulation and in-silco ADMET prediction studies of novel indole-based benzamides targeting estrogen receptor alfa positive for effective breast cancer therapy
Breast cancer is one of the most common malignancies in women, afflicting millions of lives each year. Our current study suggests that the development of the most promising 7-substituted -1-(4-(piperidine-1-yl methoxy)benzyl)-1H-indole-3-carboxamide derivatives results in potent anticancer agents through in-silico investigations. The molecular docking was performed against estrogen receptor alpha (ER-α) positive (PDB ID: 3UUD) of breast cancer cells to anticipate the binding modes of the designed compounds and the likely mode of action. The interactions between the ligands and amino acid residues were thoroughly elucidated. The stability of the docked protein-ligand complexes was further confirmed by 100 ns molecular simulations methods. From in-silico studies, indole-based benzamides exhibited satisfactory physicochemical, drug-likeness and toxicity properties. To conclude, the most promising substituted benzamide analogs on the indole ring could serve as a possible modulator against ER-α positive breast cancer
Design, docking, MD simulation and in-silco ADMET prediction studies of novel indole-based benzamides targeting estrogen receptor alfa positive for effective breast cancer therapy
Breast cancer is one of the most common malignancies in women, afflicting millions of lives each year. Our current study suggests that the development of the most promising 7-substituted -1-(4-(piperidine-1-yl methoxy)benzyl)-1H-indole-3-carboxamide derivatives results in potent anticancer agents through in-silico investigations. The molecular docking was performed against estrogen receptor alpha (ER-α) positive (PDB ID: 3UUD) of breast cancer cells to anticipate the binding modes of the designed compounds and the likely mode of action. The interactions between the ligands and amino acid residues were thoroughly elucidated. The stability of the docked protein-ligand complexes was further confirmed by 100 ns molecular simulations methods. From in-silico studies, indole-based benzamides exhibited satisfactory physicochemical, drug-likeness and toxicity properties. To conclude, the most promising substituted benzamide analogs on the indole ring could serve as a possible modulator against ER-α positive breast cancer
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