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The optimization of protein-solvent interactions: thermostability and the role of hydrophobic and electrostatic interactions.

ABSTRACT: Protein-solvent interactions were analyzed using an optimization parameter based on the ratio of the solvent-accessible area in the native and the unfolded protein structure. The calculations were performed for a set of 183 nonhomologous proteins with known three-dimensional structure available in the Protein Data Bank. The dependence of the total solvent-accessible surface area on the protein molecular mass was analyzed. It was shown that there is no difference between the monomeric and oligomeric proteins with respect to the solvent-accessible area. The results also suggested that for proteins with molecular mass above some critical mass, which is about 28 kDa, a formation of domain structure or subunit aggregation into oligomers is preferred rather than a further enlargement of a single domain structure. An analysis of the optimization of both protein-solvent and charge-charge interactions was performed for 14 proteins from thermophilic organisms. The comparison of the optimization parameters calculated for proteins from thermophiles and mesophiles showed that the former are generally characterized by a high degree of optimization of the hydrophobic interactions or, in cases where the optimization of the hydrophobic interactions is not sufficiently high, by highly optimized charge-charge interactions.

SUBMITTER: Spassov VZ

PROVIDER: S-EPMC2143201 | biostudies-other | 1995 Aug

REPOSITORIES: biostudies-other

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The optimization of protein-solvent interactions: thermostability and the role of hydrophobic and electrostatic interactions.

Spassov V Z VZ Karshikoff A D AD Ladenstein R R

Protein science : a publication of the Protein Society 19950801 8

Protein-solvent interactions were analyzed using an optimization parameter based on the ratio of the solvent-accessible area in the native and the unfolded protein structure. The calculations were performed for a set of 183 nonhomologous proteins with known three-dimensional structure available in the Protein Data Bank. The dependence of the total solvent-accessible surface area on the protein molecular mass was analyzed. It was shown that there is no difference between the monomeric and oligome ...[more]

PMID: 8520477

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Project description:P0 glycoprotein is the major structural protein of peripheral nerve myelin where it is thought to modulate inter-membrane adhesion at both the extracellular apposition, which is labile upon changes in pH and ionic strength, and the cytoplasmic apposition, which is resistant to such changes. Most studies on P0 have focused on structure-function correlates in higher vertebrates. Here, we focused on its role in the structure and interactions of frog (Xenopus laevis) myelin, where it exists primarily in a dimeric form. As part of our study, we deduced the full sequence of X. laevis P0 (xP0) from its cDNA. The xP0 sequence was found to be similar to P0 sequences of higher vertebrates, suggesting that a common mechanism of PNS myelin compaction via P0 interaction might have emerged through evolution. As previously reported for mouse PNS myelin, a similar change of extracellular apposition in frog PNS myelin as a function of pH and ionic strength was observed, which can be explained by a conformational change of P0 due to protonation-deprotonation of His52 at P0's putative adhesive interface. On the other hand, the cytoplasmic apposition in frog PNS myelin, like that in the mouse, remained unchanged at different pH and ionic strength. The contribution of hydrophobic interactions to stabilizing the cytoplasmic apposition was tested by incubating sciatic nerves with detergents. Dramatic expansion at the cytoplasmic apposition was observed for both frog and mouse, indicating a common hydrophobic nature at this apposition. Urea also expanded the cytoplasmic apposition of frog myelin likely owing to denaturation of P0. Removal of the fatty acids that attached to the single Cys residue in the cytoplasmic domain of P0 did not change PNS myelin structure of either frog or mouse, suggesting that the P0-attached fatty acyl chain does not play a significant role in PNS myelin compaction and stability. These results help clarify the present understanding of P0's adhesion role and the role of its acylation in compact PNS myelin.

Project description:BACKGROUND:Prediction and analysis of protein-protein interactions (PPI) and specifically types of PPIs is an important problem in life science research because of the fundamental roles of PPIs in many biological processes in living cells. In addition, electrostatic interactions are important in understanding inter-molecular interactions, since they are long-range, and because of their influence in charged molecules. This is the main motivation for using electrostatic energy for prediction of PPI types. RESULTS:We propose a prediction model to analyze protein interaction types, namely obligate and non-obligate, using electrostatic energy values as properties. The prediction approach uses electrostatic energy values for pairs of atoms and amino acids present in interfaces where the interaction occurs. The main features of the complexes are found and then the prediction is performed via several state-of-the-art classification techniques, including linear dimensionality reduction (LDR), support vector machine (SVM), naive Bayes (NB) and k-nearest neighbor (k-NN). For an in-depth analysis of classification results, some other experiments were performed by varying the distance cutoffs between atom pairs of interacting chains, ranging from 5Å to 13Å. Moreover, several feature selection algorithms including gain ratio (GR), information gain (IG), chi-square (Chi2) and minimum redundancy maximum relevance (mRMR) are applied on the available datasets to obtain more discriminative pairs of atom types and amino acid types as features for prediction. CONCLUSIONS:Our results on two well-known datasets of obligate and non-obligate complexes confirm that electrostatic energy is an important property to predict obligate and non-obligate protein interaction types on the basis of all the experimental results, achieving accuracies of over 98%. Furthermore, a comparison performed by changing the distance cutoff demonstrates that the best values for prediction of PPI types using electrostatic energy range from 9Å to 12Å, which show that electrostatic interactions are long-range and cover a broader area in the interface. In addition, the results on using feature selection before prediction confirm that (a) a few pairs of atoms and amino acids are appropriate for prediction, and (b) prediction performance can be improved by eliminating irrelevant and noisy features and selecting the most discriminative ones.

Dataset Information

The optimization of protein-solvent interactions: thermostability and the role of hydrophobic and electrostatic interactions.

Publications

The optimization of protein-solvent interactions: thermostability and the role of hydrophobic and electrostatic interactions.

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