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Unmasking determinants of specificity in the human kinome.

Creixell P, Palmeri A, Miller CJ, Lou HJ, Santini CC, Nielsen M, Turk BE, Linding R - Cell (2015)

Bottom Line: Here, we systematically discover several DoS and experimentally validate three of them, named the αC1, αC3, and APE-7 residues.We demonstrate that DoS form sparse networks of non-conserved residues spanning distant regions.Our results reveal a likely role for inter-residue allostery in specificity and an evolutionary decoupling of kinase activity and specificity, which appear loaded on independent groups of residues.

View Article: PubMed Central - PubMed

Affiliation: Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark. Electronic address: creixell@mit.edu.

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Related to Figure 1(A) Experimental Determination of the Peptide Specificity of a Kinase Domain. Peptide specificity is determined experimentally by Positional Scanning Peptide Library (PSPL) screening (Hutti et al., 2004), where purified kinases are exposed to random peptides where only specific positions are fixed to one particular amino acid residue, thus determining substrate molecular preferences for every given kinase. The experimental results can be turned into Position-Specific Scoring Matrices (PSSM) or motif logos. NetPhorest (Miller et al., 2008) is a comprehensive collection of PSSMs (obtained from PSPL as well as phosphorylation motifs obtained by training artificial neural networks) for different domains in different species and the full human kinome collection covering 166 kinases was used in our study. Note that the data, PSSM, and logo were shown and included for illustration purposes only, and thus its values should not be treated as actual data.(B) Kinase Domain Similarity Does Not Correlate With Substrate Similarity. After collecting all human kinases for which substrate information (i.e., Position-Specific Scoring Matrices or PSSMs) is available, the domain similarity and substrate specificity similarity have been computed as the BLOSUM distance (from the BLOSUM62 matrix [Henikoff and Henikoff, 1992]) and, in order to measure similarity instead of dissimilarity, the negative of the Frobenius distance, respectively. As shown in the figure, strong direct correlation between sequence similarity at the whole domain level and substrate specificity similarity does not exist, indicating that substrate specificity is unlikely to be encoded by the entire domain. This observation prompted the introduction of specificity masks (different combinations of residues with different degrees of contributions to domain specificity) used subsequently in this study.
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figs1: Related to Figure 1(A) Experimental Determination of the Peptide Specificity of a Kinase Domain. Peptide specificity is determined experimentally by Positional Scanning Peptide Library (PSPL) screening (Hutti et al., 2004), where purified kinases are exposed to random peptides where only specific positions are fixed to one particular amino acid residue, thus determining substrate molecular preferences for every given kinase. The experimental results can be turned into Position-Specific Scoring Matrices (PSSM) or motif logos. NetPhorest (Miller et al., 2008) is a comprehensive collection of PSSMs (obtained from PSPL as well as phosphorylation motifs obtained by training artificial neural networks) for different domains in different species and the full human kinome collection covering 166 kinases was used in our study. Note that the data, PSSM, and logo were shown and included for illustration purposes only, and thus its values should not be treated as actual data.(B) Kinase Domain Similarity Does Not Correlate With Substrate Similarity. After collecting all human kinases for which substrate information (i.e., Position-Specific Scoring Matrices or PSSMs) is available, the domain similarity and substrate specificity similarity have been computed as the BLOSUM distance (from the BLOSUM62 matrix [Henikoff and Henikoff, 1992]) and, in order to measure similarity instead of dissimilarity, the negative of the Frobenius distance, respectively. As shown in the figure, strong direct correlation between sequence similarity at the whole domain level and substrate specificity similarity does not exist, indicating that substrate specificity is unlikely to be encoded by the entire domain. This observation prompted the introduction of specificity masks (different combinations of residues with different degrees of contributions to domain specificity) used subsequently in this study.

Mentions: Cellular signaling fidelity is maintained essentially through two coupled mechanisms. At a macro-molecular level, protein specificity ensures that each protein kinase will reach and interact with its protein substrates. At a micro-molecular or atomic level, peptide specificity defines the ability of a given kinase domain present in all active protein kinases to recognize and phosphorylate a specific peptide within the protein substrate (Turk, 2008) (Figure 1A). A variety of experimental techniques have been developed to elucidate the peptide specificity for many modular signaling domains and obtain specificity profiles (e.g., the so-called Position-Specific Scoring Matrices, PSSMs), as a quantitative measure of the preference of each kinase domain for each amino acid residue at every peptide substrate position (Figure S1). While other factors contributing to protein interaction specificity at a macro-molecular level (such as co-localization, co-expression, docking motifs, and scaffold or adaptor proteins) have been described (Bhattacharyya et al., 2006, Linding et al., 2007, Reményi et al., 2005, Scott and Pawson, 2009), the combination of residues in the kinase domain that encode peptide substrate specificity, the so-called determinants of specificity (DoS), have remained largely elusive (Figure 1B). Even though some structural studies have helped identify residues that are in close contact with the substrate peptide which likely influence specificity (Brinkworth et al., 2003, Ellis and Kobe, 2011, Hanks and Hunter, 1995, Mok et al., 2010, Nolen et al., 2004), these studies were largely focused on specific kinase families and/or non-human species as well as limited in scope by the small number of kinase-peptide structures currently available and an inability to capture potentially long-range DoS.


Unmasking determinants of specificity in the human kinome.

Creixell P, Palmeri A, Miller CJ, Lou HJ, Santini CC, Nielsen M, Turk BE, Linding R - Cell (2015)

Related to Figure 1(A) Experimental Determination of the Peptide Specificity of a Kinase Domain. Peptide specificity is determined experimentally by Positional Scanning Peptide Library (PSPL) screening (Hutti et al., 2004), where purified kinases are exposed to random peptides where only specific positions are fixed to one particular amino acid residue, thus determining substrate molecular preferences for every given kinase. The experimental results can be turned into Position-Specific Scoring Matrices (PSSM) or motif logos. NetPhorest (Miller et al., 2008) is a comprehensive collection of PSSMs (obtained from PSPL as well as phosphorylation motifs obtained by training artificial neural networks) for different domains in different species and the full human kinome collection covering 166 kinases was used in our study. Note that the data, PSSM, and logo were shown and included for illustration purposes only, and thus its values should not be treated as actual data.(B) Kinase Domain Similarity Does Not Correlate With Substrate Similarity. After collecting all human kinases for which substrate information (i.e., Position-Specific Scoring Matrices or PSSMs) is available, the domain similarity and substrate specificity similarity have been computed as the BLOSUM distance (from the BLOSUM62 matrix [Henikoff and Henikoff, 1992]) and, in order to measure similarity instead of dissimilarity, the negative of the Frobenius distance, respectively. As shown in the figure, strong direct correlation between sequence similarity at the whole domain level and substrate specificity similarity does not exist, indicating that substrate specificity is unlikely to be encoded by the entire domain. This observation prompted the introduction of specificity masks (different combinations of residues with different degrees of contributions to domain specificity) used subsequently in this study.
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4644237&req=5

figs1: Related to Figure 1(A) Experimental Determination of the Peptide Specificity of a Kinase Domain. Peptide specificity is determined experimentally by Positional Scanning Peptide Library (PSPL) screening (Hutti et al., 2004), where purified kinases are exposed to random peptides where only specific positions are fixed to one particular amino acid residue, thus determining substrate molecular preferences for every given kinase. The experimental results can be turned into Position-Specific Scoring Matrices (PSSM) or motif logos. NetPhorest (Miller et al., 2008) is a comprehensive collection of PSSMs (obtained from PSPL as well as phosphorylation motifs obtained by training artificial neural networks) for different domains in different species and the full human kinome collection covering 166 kinases was used in our study. Note that the data, PSSM, and logo were shown and included for illustration purposes only, and thus its values should not be treated as actual data.(B) Kinase Domain Similarity Does Not Correlate With Substrate Similarity. After collecting all human kinases for which substrate information (i.e., Position-Specific Scoring Matrices or PSSMs) is available, the domain similarity and substrate specificity similarity have been computed as the BLOSUM distance (from the BLOSUM62 matrix [Henikoff and Henikoff, 1992]) and, in order to measure similarity instead of dissimilarity, the negative of the Frobenius distance, respectively. As shown in the figure, strong direct correlation between sequence similarity at the whole domain level and substrate specificity similarity does not exist, indicating that substrate specificity is unlikely to be encoded by the entire domain. This observation prompted the introduction of specificity masks (different combinations of residues with different degrees of contributions to domain specificity) used subsequently in this study.
Mentions: Cellular signaling fidelity is maintained essentially through two coupled mechanisms. At a macro-molecular level, protein specificity ensures that each protein kinase will reach and interact with its protein substrates. At a micro-molecular or atomic level, peptide specificity defines the ability of a given kinase domain present in all active protein kinases to recognize and phosphorylate a specific peptide within the protein substrate (Turk, 2008) (Figure 1A). A variety of experimental techniques have been developed to elucidate the peptide specificity for many modular signaling domains and obtain specificity profiles (e.g., the so-called Position-Specific Scoring Matrices, PSSMs), as a quantitative measure of the preference of each kinase domain for each amino acid residue at every peptide substrate position (Figure S1). While other factors contributing to protein interaction specificity at a macro-molecular level (such as co-localization, co-expression, docking motifs, and scaffold or adaptor proteins) have been described (Bhattacharyya et al., 2006, Linding et al., 2007, Reményi et al., 2005, Scott and Pawson, 2009), the combination of residues in the kinase domain that encode peptide substrate specificity, the so-called determinants of specificity (DoS), have remained largely elusive (Figure 1B). Even though some structural studies have helped identify residues that are in close contact with the substrate peptide which likely influence specificity (Brinkworth et al., 2003, Ellis and Kobe, 2011, Hanks and Hunter, 1995, Mok et al., 2010, Nolen et al., 2004), these studies were largely focused on specific kinase families and/or non-human species as well as limited in scope by the small number of kinase-peptide structures currently available and an inability to capture potentially long-range DoS.

Bottom Line: Here, we systematically discover several DoS and experimentally validate three of them, named the αC1, αC3, and APE-7 residues.We demonstrate that DoS form sparse networks of non-conserved residues spanning distant regions.Our results reveal a likely role for inter-residue allostery in specificity and an evolutionary decoupling of kinase activity and specificity, which appear loaded on independent groups of residues.

View Article: PubMed Central - PubMed

Affiliation: Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark. Electronic address: creixell@mit.edu.

Show MeSH
Related in: MedlinePlus