MQAPsingle: A quasi single-model approach for estimation of the quality of individual protein structure models

2016 ◽  
Vol 84 (8) ◽  
pp. 1021-1028 ◽  
Author(s):  
Marcin Pawlowski ◽  
Lukasz Kozlowski ◽  
Andrzej Kloczkowski
Keyword(s):  
Protein Structure ◽  
Single Model ◽  
Individual Protein ◽  
Model Approach

scholarly journals A single-model quality assessment method for poor quality protein structure

2020 ◽  
Author(s):  
Jianquan Ouyang ◽  
Ningqiao Huang ◽  
Yunqi Jiang
Keyword(s):  
Protein Structure ◽  
Quality Assessment ◽  
Structure Prediction ◽  
Assessment Method ◽  
Poor Quality ◽  
Single Model ◽  
Model Quality ◽  
Model Quality Assessment ◽  
Quality Assessment Method

Abstract Quality assessment of protein tertiary structure prediction models, in which structures of the best quality are selected from decoys, is a major challenge in protein structure prediction, and is crucial to determine a model’s utility and potential applications. Estimating the quality of a single model predicts the model’s quality based on the single model itself. In general, the Pearson correlation value of the quality assessment method increases in tandem with an increase in the quality of the model pool. However, there is no consensus regarding the best method to select a few good models from the poor quality model pool. In this work, we introduce a novel single-model quality assessment method for poor quality models that uses simple linear combinations of six features. We perform weighted search and linear regression on a large dataset of models from the 12th Critical Assessment of Protein Structure Prediction (CASP12) and benchmark the results on CASP13 models. We demonstrate that our method achieves outstanding performance on poor quality models.

scholarly journals A single-model quality assessment method for poor quality protein structure

2020 ◽  
Author(s):  
Jianquan Ouyang ◽  
Ningqiao Huang ◽  
Yunqi Jiang
Keyword(s):  
Protein Structure ◽  
Quality Assessment ◽  
Structure Prediction ◽  
Assessment Method ◽  
Poor Quality ◽  
Single Model ◽  
Model Quality ◽  
Model Quality Assessment ◽  
Quality Assessment Method

Abstract Background: Quality assessment of protein tertiary structure prediction models, in which structures of the best quality are selected from decoys, is a major challenge in protein structure prediction, and is crucial to determine a model’s utility and potential applications. Estimating the quality of a single model predicts the model’s quality based on the single model itself. In general, the Pearson correlation value of the quality assessment method increases in tandem with an increase in the quality of the model pool. However, there is no consensus regarding the best method to select a few good models from the poor quality model pool.Results: We introduce a novel single-model quality assessment method for poor quality models that uses simple linear combinations of six features. We perform weighted search and linear regression on a large dataset of models from the 12th Critical Assessment of Protein Structure Prediction (CASP12) and benchmark the results on CASP13 models. We demonstrate that our method achieves outstanding performance on poor quality models.Conclusions: According to results of poor protein structure assessment based on six features, contact prediction and relying on fewer prediction features can improve selection accuracy.

scholarly journals Toward the estimation of the absolute quality of individual protein structure models

2010 ◽  
Vol 27 (3) ◽  
pp. 343-350 ◽  
Author(s):  
Pascal Benkert ◽  
Marco Biasini ◽  
Torsten Schwede
Keyword(s):  
Protein Structure ◽  
Individual Protein ◽  
The Absolute

scholarly journals Physicochemical Characterization Cascade of Nanoadjuvant–Antigen Systems for Improving Vaccines

Vaccines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 544
Author(s):  
Giuditta Guerrini ◽  
Antonio Vivi ◽  
Sabrina Gioria ◽  
Jessica Ponti ◽  
Davide Magrì ◽  
...  
Keyword(s):  
Immune Response ◽  
Protein Structure ◽  
Physicochemical Properties ◽  
Physicochemical Characterization ◽  
Protein Antigen ◽  
Efficacy And Safety

Adjuvants have been used for decades to enhance the immune response to vaccines, in particular for the subunit-based adjuvants. Physicochemical properties of the adjuvant-protein antigen complexes, such as size, morphology, protein structure and binding, influence the overall efficacy and safety of the vaccine. Here we show how to perform an accurate physicochemical characterization of the nanoaluminum–ovalbumin complex. Using a combination of existing techniques, we developed a multi-staged characterization strategy based on measurements of increased complexity. This characterization cascade has the advantage of being very flexible and easily adaptable to any adjuvant-protein antigen combinations. It will contribute to control the quality of antigen–adjuvant complexes and immunological outcomes, ultimately leading to improved vaccines.

scholarly journals A Fumonisin Prevention Tool for Targeting and Ranking Agroclimatic Conditions Favoring Exposure in French Maize-Growing Areas

Toxins ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 214
Author(s):  
Agathe Roucou ◽  
Christophe Bergez ◽  
Benoît Méléard ◽  
Béatrice Orlando
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Fusarium Verticillioides ◽  
Agricultural Practices ◽  
Climatic Conditions ◽  
Agricultural Cooperatives ◽  
Mixed Model Approach ◽  
Food And Feed ◽  
Model Approach

The levels of fumonisins (FUMO)—mycotoxins produced by Fusarium verticillioides—in maize for food and feed are subject to European Union regulations. Compliance with the regulations requires the targeting of, among others, the agroclimatic factors influencing fungal contamination and FUMO production. Arvalis-Institut du végétal has created a national, multiyear database for maize, based on field survey data collected since 2003. This database contains information about agricultural practices, climatic conditions and FUMO concentrations at harvest for 738 maize fields distributed throughout French maize-growing regions. A linear mixed model approach highlights the presence of borers and the use of a late variety, high temperatures in July and October, and a water deficit during the maize cycle as creating conditions favoring maize contamination with Fusarium verticillioides. It is thus possible to target a combination of risk factors, consisting of this climatic sequence associated with agricultural practices of interest. The effects of the various possible agroclimatic combinations can be compared, grouped and classified as promoting very low to high FUMO concentrations, possibly exceeding the regulatory threshold. These findings should facilitate the creation of a national, informative and easy-to-use prevention tool for producers and agricultural cooperatives to manage the sanitary quality of their harvest.

scholarly journals Effects of ultrahigh pressure treatment on eating quality of steamed oat and oat protein structure

2021 ◽  
Vol 19 (1) ◽  
pp. 56-62
Author(s):  
Sarina Ma ◽  
Meili Zhang ◽  
Yanbin Shi ◽  
Hongli Wang ◽  
Huan Chu
Keyword(s):  
Protein Structure ◽  
Ultrahigh Pressure ◽  
Eating Quality ◽  
Pressure Treatment

The multi-model approach for fractional-order systems modelling

2016 ◽  
Vol 40 (1) ◽  
pp. 331-340 ◽  
Author(s):  
Samia Talmoudi ◽  
Moufida Lahmari
Keyword(s):  
Transfer Function ◽  
Fractional Order ◽  
Global Model ◽  
Fractional Order Systems ◽  
New Approach ◽  
Physical Systems ◽  
Integer Order ◽  
Systems Modelling ◽  
Model Approach

Currently, fractional-order systems are attracting the attention of many researchers because they present a better representation of many physical systems in several areas, compared with integer-order models. This article contains two main contributions. In the first one, we suggest a new approach to fractional-order systems modelling. This model is represented by an explicit transfer function based on the multi-model approach. In the second contribution, a new method of computation of the validity of library models, according to the frequency [Formula: see text], is exposed. Finally, a global model is obtained by fusion of library models weighted by their respective validities. Illustrative examples are presented to show the advantages and the quality of the proposed strategy.

scholarly journals Zoomqa: Residue-Level Single-Model QA Support Vector Machine Utilizing Sequential and 3D Structural Features

2021 ◽  
Author(s):  
Kyle Hippe ◽  
Cade Lilley ◽  
William Berkenpas ◽  
Kiyomi Kishaba ◽  
Renzhi Cao
Keyword(s):  
Protein Complex ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
State Of The Art ◽  
Chemical Properties ◽  
Structural Features ◽  
Residue Level ◽  
Support Vector ◽  
Single Model

ABSTRACTMotivationThe Estimation of Model Accuracy problem is a cornerstone problem in the field of Bioinformatics. When predictions are made for proteins of which we do not know the native structure, we run into an issue to tell how good a tertiary structure prediction is, especially the protein binding regions, which are useful for drug discovery. Currently, most methods only evaluate the overall quality of a protein decoy, and few can work on residue level and protein complex. Here we introduce ZoomQA, a novel, single-model method for assessing the accuracy of a tertiary protein structure / complex prediction at residue level. ZoomQA differs from others by considering the change in chemical and physical features of a fragment structure (a portion of a protein within a radius r of the target amino acid) as the radius of contact increases. Fourteen physical and chemical properties of amino acids are used to build a comprehensive representation of every residue within a protein and grades their placement within the protein as a whole. Moreover, ZoomQA can evaluate the quality of protein complex, which is unique.ResultsWe benchmark ZoomQA on CASP14, it outperforms other state of the art local QA methods and rivals state of the art QA methods in global prediction metrics. Our experiment shows the efficacy of these new features, and shows our method is able to match the performance of other state-of-the-art methods without the use of homology searching against database or PSSM matrix.Availabilityhttp://[email protected]

‘Pragmatic Evaluation’

2012 ◽  
pp. 45-56
Author(s):  
Richard E. Scott
Keyword(s):  
Real World ◽  
Evidence Base ◽  
Healthcare Organisation ◽  
Health Evaluation ◽  
Single Model ◽  
Evaluation Team ◽  
Real World Setting ◽  
Staged Approach ◽  
Evaluation Approaches

E-Health continues to be implemented despite continued demonstration that it lacks value. Specific guidance regarding research approaches and methodologies would be beneficial due to the value in identifying and adopting a single model or framework for any one ‘entity’ (healthcare organisation, sub-national region, country, etc.) so that the evidence-base accumulates more rapidly and interventions can be more meaningfully compared. This paper describes a simple and systematic approach to e-health evaluation in a real-world setting, which can be applied by an evaluation team and raises the quality of e-health evaluations. The framework guides and advises users on evaluation approaches at different stages of e-health development and implementation. Termed ‘Pragmatic Evaluation,’ the approach has five principles that unfold in a staged approach that respects the collective need for timely, policy relevant, yet meticulous research.

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