scholarly journals PB-kPRED: knowledge-based prediction of protein backbone conformation using a structural alphabet

2017 ◽  
Author(s):  
Iyanar Vetrivel ◽  
Swapnil Mahajan ◽  
Manoj Tyagi ◽  
Lionel Hoffmann ◽  
Yves-Henri Sanejouand ◽  
...  
Keyword(s):  
Protein Structures ◽  
Scoring Function ◽  
Evolutionary Information ◽  
Structural Alphabet ◽  
Local Structures ◽  
Knowledge Based ◽  
Scanning Strategies ◽  
Accuracy Of Prediction ◽  
The Impact ◽  
Protein Blocks

AbstractLibraries of structural prototypes that abstract protein local structures are known as structural alphabets and have proven to be very useful in various aspects of protein structure analyses and predictions. One such library, Protein Blocks (PBs), is composed of 16 standard 5-residues long structural prototypes. This form of analyzing proteins involves drafting its structure as a string of PBs. Thus, predicting the local structure of a protein in terms of protein blocks is a step towards the objective of predicting its 3-D structure. Here a new approach, kPred, is proposed towards this aim that is independent of the evolutionary information available. It involves (i) organizing the structural knowledge in the form of a database of pentapeptide fragments extracted from all protein structures in the PDB and (ii) apply a purely knowledge-based algorithm, not relying on secondary structure predictions or sequence alignment profiles, to scan this database and predict most probable backbone conformations for the protein local structures.Based on the strategy used for scanning the database, the method was able to achieve efficient mean Q16 accuracies between 40.8% and 66.3% for a non-redundant subset of the PDB filtered at 30% sequence identity cut-off. The impact of these scanning strategies on the prediction was evaluated and is discussed. A scoring function that gives a good estimate of the accuracy of prediction was further developed. This score estimates very well the accuracy of the algorithm (R2 of 0.82). An online version of the tool is provided freely for non-commercial usage at http://www.bo-protscience.fr/kpred/.

Use of Nutrition Information and Understanding of “Percent Daily Value” on Nutrition Facts Tables: Evaluating the Impact of a National Public Education Campaign among Youth and Young Adults in Canada

2019 ◽  
Vol 80 (4) ◽  
pp. 200-204 ◽  
Author(s):  
Brittany Cormier ◽  
Lana Vanderlee ◽  
David Hammond
Keyword(s):  
Population Level ◽  
Correct Recall ◽  
Nutrition Information ◽  
Education Campaign ◽  
Knowledge Based ◽  
Public Education Campaign ◽  
Youth And Young Adults ◽  
Campaign Message ◽  
Health Canada ◽  
The Impact

Purpose: In 2010, Health Canada implemented a national campaign to improve understanding of “percent daily value” (%DV) in Nutrition Facts Tables (NFTs). This study examined sources of nutrition information and knowledge of %DV information communicated in the campaign. Methods: Respondents aged 16–30 years completed the Canada Food Study in 2016 (n = 2665). Measures included sources of nutrition information, NFT use, and %DV knowledge based on the campaign message (“5% DV or less is a little; 15% DV or more is a lot”). A logistic regression examined correlates of providing “correct” responses to %DV questions related to the campaign messaging. Results: Overall, 7.2% (n = 191) respondents correctly indicated that 5% is “a little”, and 4.3% (n = 115) correctly indicated 15% DV was “a lot”. Only 4.0% (n = 107) correctly answered both. Correct recall of %DV amounts was not associated with number of information sources reported, but was greater among those who were female, were younger, and reported greater NFT understanding and serving size information use (P < 0.05 for all). Conclusions: Results show low awareness of messaging from the Nutrition Facts Education Campaign among young Canadians. Such a mass media campaign may be insufficient on its own to enhance population-level understanding of %DV.

Recent Advances of In-Silico Modeling of Potent Antagonists for the Adenosine Receptors

2019 ◽  
Vol 25 (7) ◽  
pp. 750-773 ◽  
Author(s):  
Pabitra Narayan Samanta ◽  
Supratik Kar ◽  
Jerzy Leszczynski
Keyword(s):  
Drug Targets ◽  
Biological Activities ◽  
Scoring Function ◽  
Md Simulations ◽  
Energy Calculation ◽  
Binding Modes ◽  
Macromolecular Systems ◽  
In Silico Modeling ◽  
Mathematical Algorithms ◽  
The Impact

The rapid advancement of computer architectures and development of mathematical algorithms offer a unique opportunity to leverage the simulation of macromolecular systems at physiologically relevant timescales. Herein, we discuss the impact of diverse structure-based and ligand-based molecular modeling techniques in designing potent and selective antagonists against each adenosine receptor (AR) subtype that constitutes multitude of drug targets. The efficiency and robustness of high-throughput empirical scoring function-based approaches for hit discovery and lead optimization in the AR family are assessed with the help of illustrative examples that have led to nanomolar to sub-micromolar inhibition activities. Recent progress in computer-aided drug discovery through homology modeling, quantitative structure-activity relation, pharmacophore models, and molecular docking coupled with more accurate free energy calculation methods are reported and critically analyzed within the framework of structure-based virtual screening of AR antagonists. Later, the potency and applicability of integrated molecular dynamics (MD) methods are addressed in the context of diligent inspection of intricated AR-antagonist binding processes. MD simulations are exposed to be competent for studying the role of the membrane as well as the receptor flexibility toward the precise evaluation of the biological activities of antagonistbound AR complexes such as ligand binding modes, inhibition affinity, and associated thermodynamic and kinetic parameters.

scholarly journals Role of PFKFB3 and PFKFB4 in Cancer: Genetic Basis, Impact on Disease Development/Progression, and Potential as Therapeutic Targets

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 909
Author(s):  
Krzysztof Kotowski ◽  
Jakub Rosik ◽  
Filip Machaj ◽  
Stanisław Supplitt ◽  
Daniel Wiczew ◽  
...  
Keyword(s):  
Current Knowledge ◽  
Treatment Options ◽  
Protein Structures ◽  
New Drugs ◽  
Proliferating Cells ◽  
Cancer Tissues ◽  
The Impact ◽  
Rate Limiting ◽  
Synthesis And Degradation

Glycolysis is a crucial metabolic process in rapidly proliferating cells such as cancer cells. Phosphofructokinase-1 (PFK-1) is a key rate-limiting enzyme of glycolysis. Its efficiency is allosterically regulated by numerous substances occurring in the cytoplasm. However, the most potent regulator of PFK-1 is fructose-2,6-bisphosphate (F-2,6-BP), the level of which is strongly associated with 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase activity (PFK-2/FBPase-2, PFKFB). PFK-2/FBPase-2 is a bifunctional enzyme responsible for F-2,6-BP synthesis and degradation. Four isozymes of PFKFB (PFKFB1, PFKFB2, PFKFB3, and PFKFB4) have been identified. Alterations in the levels of all PFK-2/FBPase-2 isozymes have been reported in different diseases. However, most recent studies have focused on an increased expression of PFKFB3 and PFKFB4 in cancer tissues and their role in carcinogenesis. In this review, we summarize our current knowledge on all PFKFB genes and protein structures, and emphasize important differences between the isoenzymes, which likely affect their kinase/phosphatase activities. The main focus is on the latest reports in this field of cancer research, and in particular the impact of PFKFB3 and PFKFB4 on tumor progression, metastasis, angiogenesis, and autophagy. We also present the most recent achievements in the development of new drugs targeting these isozymes. Finally, we discuss potential combination therapies using PFKFB3 inhibitors, which may represent important future cancer treatment options.

A noise reduction method for semi-supervised community detection based on harmonic function

2018 ◽  
Vol 32 (14) ◽  
pp. 1850166 ◽  
Author(s):  
Lilin Fan ◽  
Kaiyuan Song ◽  
Dong Liu
Keyword(s):  
Harmonic Function ◽  
Prior Knowledge ◽  
Community Detection ◽  
Detection Methods ◽  
Detection Process ◽  
Knowledge Based ◽  
Detection Approach ◽  
Series Of Experiments ◽  
Novel Strategy ◽  
The Impact

Semi-supervised community detection is an important research topic in the field of complex network, which incorporates prior knowledge and topology to guide the community detection process. However, most of the previous work ignores the impact of the noise from prior knowledge during the community detection process. This paper proposes a novel strategy to identify and remove the noise from prior knowledge based on harmonic function, so as to make use of prior knowledge more efficiently. Finally, this strategy is applied to three state-of-the-art semi-supervised community detection methods. A series of experiments on both real and artificial networks demonstrate that the accuracy of semi-supervised community detection approach can be further improved.

Innovative performance of project teams: the role of organizational structure and knowledge-based dynamic capability

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rodrigo Valio Dominguez Gonzalez
Keyword(s):  
Organizational Structure ◽  
Industrial Sector ◽  
Project Team ◽  
Project Teams ◽  
Knowledge Generation ◽  
Dynamic Capability ◽  
Content Type ◽  
Innovative Performance ◽  
Knowledge Based ◽  
The Impact

Purpose This study aims to investigate the relationship between knowledge-based dynamic capability and organizational structure on team innovative performance in Brazilian industrial companies. Design/methodology/approach This study is based on data from a survey of 262 respondents from 65 companies in the Brazilian industrial sector with project teams and followed the partial least squares approach to model the structural equation that was used for data analysis. Findings The results of the study show that mechanical structures with a high degree of formalization and centralization have a negative impact on knowledge-based dynamic capability and integration has a positive relationship with dynamic capability. Moreover, the research shows that project team innovative performance is directly affected by knowledge generation and combination capability; however, knowledge acquisition/absorption does not interfere with project team innovative activity. Practical implications This study contributes to the managers of firms in the industrial sector by analyzing how the characteristics of organizational structure impact dynamic capability and project team innovative performance. The results of this study indicate that more mechanical structures have more difficulty in developing knowledge-based dynamic capability in the context of project teams. Originality/value This study advances the concept of knowledge-based dynamic capability from the firm level to the project team level. This study accesses a research gap that characterizes organizational structure as an antecedent of dynamic capability, analyzing the impact of organizational structure on the dimensions of dynamic capability and of the latter on project team innovative performance.

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