The Experts below are selected from a list of 243 Experts worldwide ranked by ideXlab platform
James C. Phillips - One of the best experts on this subject based on the ideXlab platform.
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Scaling and self-organized criticality in proteins I
Proceedings of the National Academy of Sciences of the United States of America, 2009Co-Authors: James C. PhillipsAbstract:The complexity of proteins is substantially simplified by regarding them as archetypical examples of self-organized criticality (SOC). To test this idea and elaborate on it, this article applies the Moret-Zebende SOC Hydrophobicity scale to the large-scale scaffold repeat protein of the HEAT superfamily, PR65/A. Hydrophobic plasticity is defined and used to identify docking platforms and hinges from repeat sequences alone. The difference between the MZ scale and conventional Hydrophobicity Scales reflects long-range conformational forces that are central to protein functionality.
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a stringent test for Hydrophobicity Scales two proteins with 88 sequence identity but different structure and function
Proceedings of the National Academy of Sciences of the United States of America, 2008Co-Authors: Alexander E. Kister, James C. PhillipsAbstract:Protein–protein interactions (protein functionalities) are mediated by water, which compacts individual proteins and promotes close and temporarily stable large-area protein–protein interfaces. In their classic article, Kyte and Doolittle (KD) concluded that the “simplicity and graphic nature of Hydrophobicity Scales make them very useful tools for the evaluation of protein structures.” In practice, however, attempts to develop Hydrophobicity Scales (for example, compatible with classical force fields (CFF) in calculating the energetics of protein folding) have encountered many difficulties. Here, we suggest an entirely different approach based on the idea that proteins are self-organized networks, subject to evolving finite-scale criticality (like some network glasses). We test this proposal against two small proteins that are delicately balanced between α and α/β structures, with different functions encoded with only 12% of their amino acids. This example explains why protein structure prediction is so challenging, and it provides a severe test for the accuracy and content of Hydrophobicity Scales. This method confirms KD's evaluation and at the same time suggests that protein structure, dynamics, and function can be best discussed without using CFF.
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A stringent test for Hydrophobicity Scales: Two proteins with 88% sequence identity but different structure and function
Proceedings of the National Academy of Sciences of the United States of America, 2008Co-Authors: Alexander E. Kister, James C. PhillipsAbstract:Protein-protein interactions (protein functionalities) are mediated by water, which compacts individual proteins and promotes close and temporarily stable large-area protein-protein interfaces. In their classic article, Kyte and Doolittle (KD) concluded that the "simplicity and graphic nature of Hydrophobicity Scales make them very useful tools for the evaluation of protein structures." In practice, however, attempts to develop Hydrophobicity Scales (for example, compatible with classical force fields (CFF) in calculating the energetics of protein folding) have encountered many difficulties. Here, we suggest an entirely different approach based on the idea that proteins are self-organized networks, subject to evolving finite-scale criticality (like some network glasses). We test this proposal against two small proteins that are delicately balanced between alpha and alpha/beta structures, with different functions encoded with only 12% of their amino acids. This example explains why protein structure prediction is so challenging, and it provides a severe test for the accuracy and content of Hydrophobicity Scales. This method confirms KD's evaluation and at the same time suggests that protein structure, dynamics, and function can be best discussed without using CFF.
Erwin London - One of the best experts on this subject based on the ideXlab platform.
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Strong Correlation Between Statistical Transmembrane Tendency and Experimental Hydrophobicity Scales for Identification of Transmembrane Helices
Journal of Membrane Biology, 2009Co-Authors: Gang Zhao, Erwin LondonAbstract:Direct physical chemistry measurements of the Hydrophobicity of amino acids or their derivatives have often been used to estimate the propensity of amino acids to participate in transmembrane helices. In this short note, it is found that there is a very high degree of correlation ( r = 0.944–0.965) between an average physical chemistry Hydrophobicity scale (an average of Scales derived, e.g., from the solubility of amino acid derivatives in organic solvents versus water or their binding to hydrophobic particles) and the statistically based transmembrane tendency scale (derived from the relative abundance of residues in known transmembrane and soluble protein sequences (Zhao and London, Protein Sci 15:1987–2001, 2006)). This correlation indicates that, other than Hydrophobicity, amino acid properties/interactions that promote or inhibit transmembrane helix formation in a specific membrane protein largely cancel out when averaged over all transmembrane sequences. In other words, other than Hydrophobicity, there are no properties of a specific amino acid residue within a hydrophobic segment that have a strong systematic effect upon transmembrane helix formation independent of the remainder of the sequence in that hydrophobic segment. However, proline is an exception to this rule.
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an amino acid transmembrane tendency scale that approaches the theoretical limit to accuracy for prediction of transmembrane helices relationship to biological Hydrophobicity
Protein Science, 2006Co-Authors: Gang Zhao, Erwin LondonAbstract:Hydrophobicity analyses applied to databases of soluble and transmembrane (TM) proteins of known structure were used to resolve total genomic Hydrophobicity profiles into (helical) TM sequences and mainly "subhydrophobic" soluble components. This information was used to define a refined "Hydrophobicity"-type TM sequence prediction scale that should approach the theoretical limit of accuracy. The refinement procedure involved adjusting scale values to eliminate differences between the average amino acid composition of populations TM and soluble sequences of equal Hydrophobicity, a required property of a scale having maximum accuracy. Application of this procedure to different Hydrophobicity Scales caused them to collapse to essentially a single TM tendency scale. As expected, when different Scales were compared, the TM tendency scale was the most accurate at predicting TM sequences. It was especially highly correlated (r = 0.95) to the biological Hydrophobicity scale, derived experimentally from the percent TM conformation formed by artificial sequences passing though the translocon. It was also found that resolution of total genomic sequence data into TM and soluble components could be used to define the percent probability that a sequence with a specific Hydrophobicity value forms a TM segment. Application of the TM tendency scale to whole genomic data revealed an overlap of TM and soluble sequences in the "semihydrophobic" range. This raises the possibility that a significant number of proteins have sequences that can switch between TM and non-TM states. Such proteins may exist in moonlighting forms having properties very different from those of the predominant conformation.
Gang Zhao - One of the best experts on this subject based on the ideXlab platform.
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Strong Correlation Between Statistical Transmembrane Tendency and Experimental Hydrophobicity Scales for Identification of Transmembrane Helices
Journal of Membrane Biology, 2009Co-Authors: Gang Zhao, Erwin LondonAbstract:Direct physical chemistry measurements of the Hydrophobicity of amino acids or their derivatives have often been used to estimate the propensity of amino acids to participate in transmembrane helices. In this short note, it is found that there is a very high degree of correlation ( r = 0.944–0.965) between an average physical chemistry Hydrophobicity scale (an average of Scales derived, e.g., from the solubility of amino acid derivatives in organic solvents versus water or their binding to hydrophobic particles) and the statistically based transmembrane tendency scale (derived from the relative abundance of residues in known transmembrane and soluble protein sequences (Zhao and London, Protein Sci 15:1987–2001, 2006)). This correlation indicates that, other than Hydrophobicity, amino acid properties/interactions that promote or inhibit transmembrane helix formation in a specific membrane protein largely cancel out when averaged over all transmembrane sequences. In other words, other than Hydrophobicity, there are no properties of a specific amino acid residue within a hydrophobic segment that have a strong systematic effect upon transmembrane helix formation independent of the remainder of the sequence in that hydrophobic segment. However, proline is an exception to this rule.
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an amino acid transmembrane tendency scale that approaches the theoretical limit to accuracy for prediction of transmembrane helices relationship to biological Hydrophobicity
Protein Science, 2006Co-Authors: Gang Zhao, Erwin LondonAbstract:Hydrophobicity analyses applied to databases of soluble and transmembrane (TM) proteins of known structure were used to resolve total genomic Hydrophobicity profiles into (helical) TM sequences and mainly "subhydrophobic" soluble components. This information was used to define a refined "Hydrophobicity"-type TM sequence prediction scale that should approach the theoretical limit of accuracy. The refinement procedure involved adjusting scale values to eliminate differences between the average amino acid composition of populations TM and soluble sequences of equal Hydrophobicity, a required property of a scale having maximum accuracy. Application of this procedure to different Hydrophobicity Scales caused them to collapse to essentially a single TM tendency scale. As expected, when different Scales were compared, the TM tendency scale was the most accurate at predicting TM sequences. It was especially highly correlated (r = 0.95) to the biological Hydrophobicity scale, derived experimentally from the percent TM conformation formed by artificial sequences passing though the translocon. It was also found that resolution of total genomic sequence data into TM and soluble components could be used to define the percent probability that a sequence with a specific Hydrophobicity value forms a TM segment. Application of the TM tendency scale to whole genomic data revealed an overlap of TM and soluble sequences in the "semihydrophobic" range. This raises the possibility that a significant number of proteins have sequences that can switch between TM and non-TM states. Such proteins may exist in moonlighting forms having properties very different from those of the predominant conformation.
Alexander E. Kister - One of the best experts on this subject based on the ideXlab platform.
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a stringent test for Hydrophobicity Scales two proteins with 88 sequence identity but different structure and function
Proceedings of the National Academy of Sciences of the United States of America, 2008Co-Authors: Alexander E. Kister, James C. PhillipsAbstract:Protein–protein interactions (protein functionalities) are mediated by water, which compacts individual proteins and promotes close and temporarily stable large-area protein–protein interfaces. In their classic article, Kyte and Doolittle (KD) concluded that the “simplicity and graphic nature of Hydrophobicity Scales make them very useful tools for the evaluation of protein structures.” In practice, however, attempts to develop Hydrophobicity Scales (for example, compatible with classical force fields (CFF) in calculating the energetics of protein folding) have encountered many difficulties. Here, we suggest an entirely different approach based on the idea that proteins are self-organized networks, subject to evolving finite-scale criticality (like some network glasses). We test this proposal against two small proteins that are delicately balanced between α and α/β structures, with different functions encoded with only 12% of their amino acids. This example explains why protein structure prediction is so challenging, and it provides a severe test for the accuracy and content of Hydrophobicity Scales. This method confirms KD's evaluation and at the same time suggests that protein structure, dynamics, and function can be best discussed without using CFF.
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A stringent test for Hydrophobicity Scales: Two proteins with 88% sequence identity but different structure and function
Proceedings of the National Academy of Sciences of the United States of America, 2008Co-Authors: Alexander E. Kister, James C. PhillipsAbstract:Protein-protein interactions (protein functionalities) are mediated by water, which compacts individual proteins and promotes close and temporarily stable large-area protein-protein interfaces. In their classic article, Kyte and Doolittle (KD) concluded that the "simplicity and graphic nature of Hydrophobicity Scales make them very useful tools for the evaluation of protein structures." In practice, however, attempts to develop Hydrophobicity Scales (for example, compatible with classical force fields (CFF) in calculating the energetics of protein folding) have encountered many difficulties. Here, we suggest an entirely different approach based on the idea that proteins are self-organized networks, subject to evolving finite-scale criticality (like some network glasses). We test this proposal against two small proteins that are delicately balanced between alpha and alpha/beta structures, with different functions encoded with only 12% of their amino acids. This example explains why protein structure prediction is so challenging, and it provides a severe test for the accuracy and content of Hydrophobicity Scales. This method confirms KD's evaluation and at the same time suggests that protein structure, dynamics, and function can be best discussed without using CFF.
Robert S. Hodges - One of the best experts on this subject based on the ideXlab platform.
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Intrinsic Amino Acid Side-Chain Hydrophilicity/Hydrophobicity Coefficients Determined by Reversed-Phase High-Performance Liquid Chromatography of Model Peptides: Comparison with Other Hydrophilicity/Hydrophobicity Scales
Biopolymers, 2009Co-Authors: Colin T. Mant, James M. Kovacs, Hyunmin Kim, David D. Pollock, Robert S. HodgesAbstract:An accurate determination of the intrinsic hydrophilicity/Hydrophobicity of amino acid side-chains in peptides and proteins is fundamental in understanding many area of research, including protein folding and stability, peptide and protein function, protein-protein interactions and peptide/protein oligomerization, as well as the design of protocols for purification and characterization of peptides and proteins. Our definition of intrinsic hydrophilicity/Hydrophobicity of side-chains is the maximum possible hydrophilicity/Hydrophobicity of side-chains in the absence of any nearest-neighbor effects and/or any conformational effects of the polypeptide chain that prevent full expression of side-chain hydrophilicity/Hydrophobicity. In this review, we have compared an experimentally derived intrinsic side-chain hydrophilicity/Hydrophobicity scale generated from RP-HPLC retention behavior of de novo designed synthetic model peptides at pH 2 and pH 7 with other RP-HPLC-derived Scales, as well as Scales generated from classic experimental and calculation-based methods of octanol/water partitioning of Nalpha-acetyl-amino-acid amides or free energy of transfer of free amino acids. Generally poor correlation was found with previous RP-HPLC-derived Scales, likely due to the random nature of the peptide mixtures in terms of varying peptide size, conformation and frequency of particular amino acids. In addition, generally poor correlation with the classical approaches served to underline the importance of the presence of a polypeptide backbone when generating intrinsic values. We have shown that the intrinsic scale determined here is in full agreement with the structural characteristics of amino acid side-chains.
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intrinsic amino acid side chain hydrophilicity Hydrophobicity coefficients determined by reversed phase high performance liquid chromatography of model peptides comparison with other hydrophilicity Hydrophobicity Scales
Biopolymers, 2009Co-Authors: Colin T. Mant, James M. Kovacs, Hyunmin Kim, David D. Pollock, Robert S. HodgesAbstract:An accurate determination of the intrinsic hydrophilicity/Hydrophobicity of amino acid side-chains in peptides and proteins is fundamental in understanding many area of research, including protein folding and stability, peptide and protein function, protein-protein interactions and peptide/protein oligomerization, as well as the design of protocols for purification and characterization of peptides and proteins. Our definition of intrinsic hydrophilicity/Hydrophobicity of side-chains is the maximum possible hydrophilicity/Hydrophobicity of side-chains in the absence of any nearest-neighbor effects and/or any conformational effects of the polypeptide chain that prevent full expression of side-chain hydrophilicity/Hydrophobicity. In this review, we have compared an experimentally derived intrinsic side-chain hydrophilicity/Hydrophobicity scale generated from RP-HPLC retention behavior of de novo designed synthetic model peptides at pH 2 and pH 7 with other RP-HPLC-derived Scales, as well as Scales generated from classic experimental and calculation-based methods of octanol/water partitioning of Nalpha-acetyl-amino-acid amides or free energy of transfer of free amino acids. Generally poor correlation was found with previous RP-HPLC-derived Scales, likely due to the random nature of the peptide mixtures in terms of varying peptide size, conformation and frequency of particular amino acids. In addition, generally poor correlation with the classical approaches served to underline the importance of the presence of a polypeptide backbone when generating intrinsic values. We have shown that the intrinsic scale determined here is in full agreement with the structural characteristics of amino acid side-chains.
