Protein family comparison using statistical models and predicted structural information

Chung, Richard H.; Yona, Golan

doi:10.1186/1471-2105-5-183

Cited by 11 publications

(3 citation statements)

References 32 publications

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“…Similar to others ( 13 , 14 ), we find that considering SS prediction leads to significant improvement in both similarity detection ( Figure 2 ) and alignment accuracy ( Figure 3 ). As expected, this improvement is more pronounced for extremely distant homologs, where direct sequence signals are weak yet SS is conserved.…”

Section: Discussionsupporting

confidence: 87%

“…These patterns, dictated by structure and function, are often preserved better than the sequence and thus can help detecting protein similarity where individual sequence positions diverged beyond recognition. Currently, such ‘horizontal’ information is used by only a few methods ( 13 , 14 ), mainly in the form of secondary structure (SS) prediction.…”

Section: Introductionmentioning

confidence: 99%

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PROCAIN: protein profile comparison with assisting information

Wang

Sadreyev

Grishin

2009

Nucleic Acids Research

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Detection of remote sequence homology is essential for the accurate inference of protein structure, function and evolution. The most sensitive detection methods involve the comparison of evolutionary patterns reflected in multiple sequence alignments (MSAs) of protein families. We present PROCAIN, a new method for MSA comparison based on the combination of ‘vertical’ MSA context (substitution constraints at individual sequence positions) and ‘horizontal’ context (patterns of residue content at multiple positions). Based on a simple and tractable profile methodology and primitive measures for the similarity of horizontal MSA patterns, the method achieves the quality of homology detection comparable to a more complex advanced method employing hidden Markov models (HMMs) and secondary structure (SS) prediction. Adding SS information further improves PROCAIN performance beyond the capabilities of current state-of-the-art tools. The potential value of the method for structure/function predictions is illustrated by the detection of subtle homology between evolutionary distant yet structurally similar protein domains. ProCAIn, relevant databases and tools can be downloaded from: http://prodata.swmed.edu/procain/download. The web server can be accessed at http://prodata.swmed.edu/procain/procain.php.

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Section: Discussionsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

PROCAIN: protein profile comparison with assisting information

Wang

Sadreyev

Grishin

2009

Nucleic Acids Research

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“…Several sensitive methods have been proposed that involve the comparison of predicted SS, in addition to the residue content of the two MSAs ( 7 , 35 , 36 ). These methods are directly using the SS information in the construction and scoring of profile–profile or HMM–HMM alignments.…”

Section: Discussionmentioning

confidence: 99%

Accurate statistical model of comparison between multiple sequence alignments

Sadreyev

Grishin

2008

Nucleic Acids Research

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Comparison of multiple protein sequence alignments (MSA) reveals unexpected evolutionary relations between protein families and leads to exciting predictions of spatial structure and function. The power of MSA comparison critically depends on the quality of statistical model used to rank the similarities found in a database search, so that biologically relevant relationships are discriminated from spurious connections. Here, we develop an accurate statistical description of MSA comparison that does not originate from conventional models of single sequence comparison and captures essential features of protein families. As a final result, we compute E-values for the similarity between any two MSA using a mathematical function that depends on MSA lengths and sequence diversity. To develop these estimates of statistical significance, we first establish a procedure for generating realistic alignment decoys that reproduce natural patterns of sequence conservation dictated by protein secondary structure. Second, since similarity scores between these alignments do not follow the classic Gumbel extreme value distribution, we propose a novel distribution that yields statistically perfect agreement with the data. Third, we apply this random model to database searches and show that it surpasses conventional models in the accuracy of detecting remote protein similarities.

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Local Structure Prediction of Proteins

Simossis¹,

Heringa²

Biological and Medical Physics Biomedical Engineering

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Protein family comparison using statistical models and predicted structural information

Cited by 11 publications

References 32 publications

PROCAIN: protein profile comparison with assisting information

PROCAIN: protein profile comparison with assisting information

Accurate statistical model of comparison between multiple sequence alignments

Local Structure Prediction of Proteins

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