Information theory analysis of the relationship between primary sequence structure and ligand recognition among a class of facilitated transporters

Williamson, Rufus M.

doi:10.1006/jtbi.1995.0090

Cited by 27 publications

(22 citation statements)

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“…To this end, we used the "property entropy" method (Capra and Singh 2007), which scores the variation (Shannon entropy) at each position in a multiple sequence alignment with respect to the stereochemical similarity between the amino acids that populate it (Williamson 1995;Mirny and Shakhnovich 1999;Capra and Singh 2007). This measure allowed us to assess the conservation of natural as well as engineered variants by applying identical criteria for the two data sets without introducing corrections that are commonly applied by other methods to score conservation of natural sequences (such as phylogenetic tree construction or amino acid background frequencies).…”

Section: A Comparison Of Functional Data To Evolutionary Conservationmentioning

confidence: 99%

Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae poly(A)-binding protein

Melamed

Young

Gamble

et al. 2013

RNA

226

260

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The RNA recognition motif (RRM) is the most common RNA-binding domain in eukaryotes. Differences in RRM sequences dictate, in part, both RNA and protein-binding specificities and affinities. We used a deep mutational scanning approach to study the sequence-function relationship of the RRM2 domain of the Saccharomyces cerevisiae poly(A)-binding protein (Pab1). By scoring the activity of more than 100,000 unique Pab1 variants, including 1246 with single amino acid substitutions, we delineated the mutational constraints on each residue. Clustering of residues with similar mutational patterns reveals three major classes, composed principally of RNA-binding residues, of hydrophobic core residues, and of the remaining residues. The first class also includes a highly conserved residue not involved in RNA binding, G150, which can be mutated to destabilize Pab1. A comparison of the mutational sensitivity of yeast Pab1 residues to their evolutionary conservation reveals that most residues tolerate more substitutions than are present in the natural sequences, although other residues that tolerate fewer substitutions may point to specialized functions in yeast. An analysis of ∼40,000 double mutants indicates a preference for a short distance between two mutations that display an epistatic interaction. As examples of interactions, the mutations N139T, N139S, and I157L suppress other mutations that interfere with RNA binding and protein stability. Overall, this study demonstrates that living cells can be subjected to a single assay to analyze hundreds of thousands of protein variants in parallel.

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Section: A Comparison Of Functional Data To Evolutionary Conservationmentioning

confidence: 99%

Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae poly(A)-binding protein

Melamed

Young

Gamble

et al. 2013

RNA

226

260

View full text Add to dashboard Cite

show abstract

“…9 Some of them are based on combinatorics and information theory, including different variations of Shannon entropy and frequency scores. [10][11][12][13][14] Others take into account amino acid stereochemical properties [15][16][17][18][19] and amino acid substitution matrices. 20,21 Since there is heterogeneity in evolutionary rates between sites, models, which account for the difference in rates and amino acid substitution probabilities among different sites can be very valuable as well.…”

Section: Introductionmentioning

confidence: 99%

Functional Specificity Lies within the Properties and Evolutionary Changes of Amino Acids

Chakrabarti

Bryant

Panchenko

2007

Journal of Molecular Biology

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The rapid increase in the amount of protein sequence data has created a need for automated identification of sites that determine functional specificity among related subfamilies of proteins. A significant fraction of subfamily specific sites are only marginally conserved, which makes it extremely challenging to detect those amino acid changes that lead to functional diversification. To address this critical problem we developed a method named SPEER (specificity prediction using amino acids' properties, entropy and evolution rate) to distinguish specificity determining sites from others. SPEER encodes the conservation patterns of amino acid types using their physico-chemical properties and the heterogeneity of evolutionary changes between and within the subfamilies. To test the method, we compiled a test set containing 13 protein families with known specificity determining sites. Extensive benchmarking by comparing the performance of SPEER with other specificity site prediction algorithms has shown that it performs better in predicting several categories of subfamily specific sites.

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“…Shannon entropy has also been used to measure the structural conservation in the proteinfolding dynamics [24,25]; see Valdar [26] for a detailed review of the applications of Shannon entropy. On the other hand, relative entropy measures gain of sequence information at each position and requires a background amino acid frequency distribution [27]. Relative entropy was also used as a sequence conservation measure to detect functional protein sites ( [28]; see the supplemental data for the derivation of eqn 7 in Halabi et al [29]).…”

mentioning

confidence: 99%

Quantifying selection and diversity in viruses by entropy methods, with application to the haemagglutinin of H3N2 influenza

Pan

Deem

2011

J. R. Soc. Interface.

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Many viruses evolve rapidly. For example, haemagglutinin (HA) of the H3N2 influenza A virus evolves to escape antibody binding. This evolution of the H3N2 virus means that people who have previously been exposed to an influenza strain may be infected by a newly emerged virus. In this paper, we use Shannon entropy and relative entropy to measure the diversity and selection pressure by an antibody in each amino acid site of H3 HA between the 1992 -1993 season and the 2009-2010 season. Shannon entropy and relative entropy are two independent state variables that we use to characterize H3N2 evolution. The entropy method estimates future H3N2 evolution and migration using currently available H3 HA sequences. First, we show that the rate of evolution increases with the virus diversity in the current season. The Shannon entropy of the sequence in the current season predicts relative entropy between sequences in the current season and those in the next season. Second, a global migration pattern of H3N2 is assembled by comparing the relative entropy flows of sequences sampled in China, Japan, the USA and Europe. We verify this entropy method by describing two aspects of historical H3N2 evolution. First, we identify 54 amino acid sites in HA that have evolved in the past to evade the immune system. Second, the entropy method shows that epitopes A and B on the top of HA evolve most vigorously to escape antibody binding. Our work provides a novel entropy-based method to predict and quantify future H3N2 evolution and to describe the evolutionary history of H3N2.

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Information theory analysis of the relationship between primary sequence structure and ligand recognition among a class of facilitated transporters

Cited by 27 publications

References 0 publications

Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae poly(A)-binding protein

Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae poly(A)-binding protein

Functional Specificity Lies within the Properties and Evolutionary Changes of Amino Acids

Quantifying selection and diversity in viruses by entropy methods, with application to the haemagglutinin of H3N2 influenza

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