Comparison of the predicted and observed secondary structure of T4 phage lysozyme

Matthews, Brian W.

doi:10.1016/0005-2795(75)90109-9

Cited by 4,519 publications

(2,807 citation statements)

References 22 publications

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“…As indicated in [21], considerable caution must be exercised when using amino acid sequence information to predict the secondary structural characteristics of proteins. The accuracy of the predictions for both P-sheet regions and for turns are generally lower than for the helices, and in a number of instances the agreement between prediction and observation is no better than would be expected for a random selection of residues.…”

Section: Resultsmentioning

confidence: 99%

Amino acid sequence of pilin isolated from Pseudomonas aeruginosa PAK

et al. 1983

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Section: Resultsmentioning

confidence: 99%

Amino acid sequence of pilin isolated from Pseudomonas aeruginosa PAK

et al. 1983

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“…Standard benchmarking statistics were employed to evaluate performance such as the true-positive rate (sensitivity), the false-positive rate and the Matthew's Correlation Coefficient (MCC). 28 The MCC was employed as it represents one of the best available measures of prediction quality. It returns a value between − 1 and +1; a coefficient of − 1 represents the worst possible prediction, 0 a random prediction and +1 a perfect prediction.…”

Section: Functional Prediction Of Compensated Variants L Azevedo Et Almentioning

confidence: 99%

Improving the in silico assessment of pathogenicity for compensated variants

et al. 2016

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Understanding the functional sequelae of amino-acid replacements is of fundamental importance in medical genetics. Perhaps, the most intuitive way to assess the potential pathogenicity of a given human missense variant is by measuring the degree of evolutionary conservation of the substituted amino-acid residue, a feature that generally serves as a good proxy metric for the functional/ structural importance of that residue. However, the presence of putatively compensated variants as the wild-type alleles in orthologous proteins of other mammalian species not only challenges this classical view of amino-acid essentiality but also precludes the accurate evaluation of the functional impact of this type of missense variant using currently available bioinformatic prediction tools. Compensated variants constitute at least 4% of all known missense variants causing human-inherited disease and hence represent an important potential source of error in that they are likely to be disproportionately misclassified as benign variants. The consequent under-reporting of compensated variants is exacerbated in the context of next-generation sequencing where their inappropriate exclusion constitutes an unfortunate natural consequence of the filtering and prioritization of the very large number of variants generated. Here we demonstrate the reduced performance of currently available pathogenicity prediction tools when applied to compensated variants and propose an alternative machine-learning approach to assess likely pathogenicity for this particular type of variant.

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“…This measures the expected accuracy of predicting an unknown protein. The accuracy of prediction for the three types of secondary structure was also measured, and, in addition, the Matthews' correlation coefficient (Matthews, 1975) was calculated for each secondary structure type:…”

Section: Prediction Measurementsmentioning

confidence: 99%

Identification and application of the concepts important for accurate and reliable protein secondary structure prediction

1996

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A protein secondary structure prediction method from multiply aligned homologous sequences is presented with an overall per residue three-state accuracy of 70.1 %. There are two aims: to obtain high accuracy by identification of a set of concepts important for prediction followed by use of linear statistics; and to provide insight into the folding process. The important concepts in secondary structure prediction are identified as: residue conformational propensities, sequence edge effects, moments of hydrophobicity, position of insertions and deletions in aligned homologous sequence, moments of conservation, auto-correlation, residue ratios, secondary structure feedback effects, and filtering. Explicit use of edge effects, moments of conservation, and auto-correlation are new to this paper. The relative importance of the concepts used in prediction was analyzed by stepwise addition of information and examination of weights in the discrimination function. The simple and explicit structure of the prediction allows the method to be reimplemented easily. The accuracy of a prediction is predictable a priori. This permits evaluation of the utility of the prediction: 10% of the chains predicted were identified correctly as having a mean accuracy of >80%. Existing high-accuracy prediction methods are "black-box" predictors based on complex nonlinear statistics (e.g., neural networks in PHD: Rost & Sander, 1993a). For medium-to short-length chains ( 2 9 0 residues and

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Comparison of the predicted and observed secondary structure of T4 phage lysozyme

Cited by 4,519 publications

References 22 publications

Amino acid sequence of pilin isolated from Pseudomonas aeruginosa PAK

Amino acid sequence of pilin isolated from Pseudomonas aeruginosa PAK

Improving the in silico assessment of pathogenicity for compensated variants

Identification and application of the concepts important for accurate and reliable protein secondary structure prediction

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