A practical guide for the computational selection of residues to be experimentally characterized in protein families

Benı́tez-Páez, Alfonso; Cárdenas-Brito, Sonia; Gutiérrez, Andrés Julián

doi:10.1093/bib/bbr052

Cited by 14 publications

(12 citation statements)

References 49 publications

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“…In recent years, dozens of algorithms have been developed to identify "important" amino acid positions and/or to predict harmful amino acid changes (Addington et al, 2013;Adzhubei et al, 2010;Ashkenazy, Erez, Martz, Pupko, & Ben-Tal, 2010;Benítez-Páez, Cárdenas-Brito, & Gutiérrez, 2012;Yana Bromberg et al, 2008;Brown & Brown, 2010;Gray, Kukurba, & Kumar, 2012;Halabi, Rivoire, Leibler, & Ranganathan, 2009;Kc & Livesay, 2011;Mazin et al, 2010;Ng & Henikoff, 2003;Radivojac et al, 2013;Suel, Lockless, Wall, & Ranganathan, 2003;Wilkins, Bachman, Erdin, & Lichtarge, 2012;Ye et al, 2008). However, the reliability of these programs has significant room for improvement (Borras et al, 2012;Dare, Vasta, Penn, Tran, & Hahn, 2013;Domchek & Weber, 2008;Gray et al, 2012;Mauer, Pirzadeh-Miller, Robinson, & Euhus, 2013;Radivojac et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

Identification of biochemically neutral positions in liver pyruvate kinase

Martin

Tang

et al. 2019

Preprint

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In the goal of interpreting human exomes, when predictive programs assign functional importance to some positions, they implicitly assume the existence of non-important positions -those that accommodate many side chain chemistries without altering function ("neutral"). However, very few (if any) experimental studies have demonstrated the existence of neutral positions. We sought experimental evidence for neutral positions using human liver pyruvate kinase (hLPYK) as a model system. To that end, we used multiple evolutionary criteria to identify 20 possibly neutral positions. Nine positions were further tested with a total of 117 amino acid substitutions. Although "all" potential hLPYK functions can never be explored, we measured effects on 5 parameters associated with substrate/ligand affinities and allosteric coupling. At each position, the aggregate outcomes of multiple variants were used to quantify "neutrality" scores. Three of the nine positions showed perfect neutral scores in all 5 parameters; a fourth position had high neutral scores. Although our strategy for predicting positions had low predictive power for the identification of neutral positions, all positions had neutral scores that were much higher than positions in functional sites. Given this evidence for the existence of neutral positions, similar studies should be carried out for other proteins to generate a database of well characterized neutral positions that can then be available to benchmark and validate predictions about amino acid substitutions.

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Section: Discussionmentioning

confidence: 99%

Identification of biochemically neutral positions in liver pyruvate kinase

Martin

Tang

et al. 2019

Preprint

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“…The LacI/GalR and aldolase protein alignments used in this study are available upon request. As a final check, we considered the number of sequences and phylogenetic sampling in these MSAs, which has been shown to affect MSA analyses . For example, coevolution analyses might return biased results if one lineage of the family were oversampled.…”

Section: Methodsmentioning

confidence: 99%

“…S1). Trees for both families have a stellate appearance, indicating that many lineages are represented and that no one lineage dominated the calculation …”

Section: Methodsmentioning

confidence: 99%

Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores

2015

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As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for co-evolution between pairs of positions. Co-evolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of co-evolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly-used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6-bisphosphate aldolase protein families as models. Calculations used unthresholded co-evolution scores from which column-specific properties such as sequence entropy and random noise were subtracted; “central” positions were identified by calculating various network centrality scores. When compared among algorithms, network centrality methods, particularly eigenvector centrality, showed markedly better agreement than comparisons of the top pairwise scores. Positions with large centrality scores occurred at key structural locations and/or were functionally sensitive to mutations. Further, the top central positions often differed from those with top pairwise co-evolution scores: Instead of a few strong scores, central positions often had multiple, moderate scores. We conclude that eigenvector centrality calculations reveal a robust evolutionary pattern of constraints – detectable by divergent algorithms – that occur at key protein locations. Finally, we discuss the fact that multiple patterns co-exist in evolutionary data that, together, give rise to emergent protein functions.

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“…A general procedure for detecting functional residues in protein families based on sequence analysis was used (Benítez-Páez et al 2011). Briefly, 27 protein sequences belonging to organisms of the most representative eubacterial groups were retrieved from Uniprot database (Uniprot Consortium 2010) and aligned using the MUSCLE program and default parameters (Edgar 2004).…”

Section: Sequence and Comparative Structural Analysismentioning

confidence: 99%

Regulation of expression and catalytic activity of Escherichia coli RsmG methyltransferase

Benı́tez-Páez¹,

Villarroya²,

Armengod³

2012

RNA

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RsmG is an AdoMet-dependent methyltransferase responsible for the synthesis of m 7 G527 in the 530 loop of bacterial 16S rRNA. This loop is universally conserved, plays a key role in ribosomal accuracy, and is a target for streptomycin binding. Loss of the m 7 G527 modification confers low-level streptomycin resistance and may affect ribosomal functioning. Here, we explore the mechanisms controlling RsmG expression and activity, which may somehow respond to the demand set by the amount of rRNA. We confirm that rsmG is the second member in a bicistronic operon and demonstrate that rsmG also has its own promoter, which appears, in actively growing cells, as a control device to offset both the relatively low stability of RsmG and inhibition of the operon promoter. RsmG levels decrease under conditions that down-regulate rRNA synthesis. However, coordination between rRNA and RsmG expression does not seem to occur at the level of transcription initiation. Instead, it might depend on the activity of an inverted repeated region, located between the rsmG promoter and ribosome binding site, which we show to work as a weak transcriptional terminator. To gain insights into the enzymatic mechanism of RsmG, highly conserved residues were mutated and the abilities of the resulting proteins to confer streptomycin resistance, to modify rRNA, and to bind AdoMet were explored. Our data demonstrate for the first time the critical importance of some residues located in the active site of Escherichia coli RsmG for the m 7 G modification process and suggest a role for them in rRNA binding and catalysis.

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A practical guide for the computational selection of residues to be experimentally characterized in protein families

Cited by 14 publications

References 49 publications

Identification of biochemically neutral positions in liver pyruvate kinase

Identification of biochemically neutral positions in liver pyruvate kinase

Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores

Regulation of expression and catalytic activity of Escherichia coli RsmG methyltransferase

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