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Register a new userHow knots influence properties of proteins
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Added by
Piotr Su{\\l}kowski
Publication date
2008
fields
Biology
and research's language is
English
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Molecular dynamics studies within a coarse-grained structure based model were used on two similar proteins belonging to the transcarbamylase family to probe the effects in the native structure of a knot. The first protein, N-acetylornithine transcarbamylase, contains no knot whereas human ormithine transcarbamylase contains a trefoil knot located deep within the sequence. In addition, we also analyzed a modified transferase with the knot removed by the appropriate change of a knot-making crossing of the protein chain. The studies of thermally- and mechanically-induced unfolding processes suggest a larger intrinsic stability of the protein with the knot.
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We perform theoretical studies of stretching of 20 proteins with knots within a coarse grained model. The knots ends are found to jump to well defined sequential locations that are associated with sharp turns whereas in homopolymers they diffuse around and eventually slide off. The waiting times of the jumps are increasingly stochastic as the temperature is raised. Larger knots do not return to their native locations when a protein is released after stretching.
Knots in proteins have been proposed to resist proteasomal degradation. Ample evidence associates proteasomal degradation with neurodegeneration. One interesting possibility is that indeed knotted conformers stall this machinery leading to toxicity. However, although the proteasome is known to unfold mechanically its substrates, at present there are no experimental methods to emulate this particular traction geometry. Here, we consider several dynamical models of the proteasome in which the complex is represented by an effective potential with an added pulling force. This force is meant to induce translocation of a protein or a polypeptide into the catalytic chamber. The force is either constant or applied periodically. The translocated proteins are modelled in a coarse-grained fashion. We do comparative analysis of several knotted globular proteins and the transiently knotted polyglutamine tracts of length 60 alone and fused in exon 1 of the huntingtin protein. Huntingtin is associated with Huntington disease, a well-known genetically-determined neurodegenerative disease. We show that the presence of a knot hinders and sometimes even jams translocation. We demonstrate that the probability to do so depends on the protein, the model of the proteasome, the magnitude of the pulling force, and the choice of the pulled terminus. In any case, the net effect would be a hindrance in the proteasomal degradation process in the cell. This would then yield toxicity textit{via} two different mechanisms: one through toxic monomers compromising degradation and another by the formation of toxic oligomers. Our work paves the way to the mechanistic investigation of the mechanical unfolding of knotted structures by the proteasome and its relation to toxicity and disease.
Proteins tend to bury hydrophobic residues inside their core during the folding process to provide stability to the protein structure and to prevent aggregation. Nevertheless, proteins do expose some sticky hydrophobic residues to the solvent. These residues can play an important functional role, for example in protein-protein and membrane interactions. Here, we investigate how hydrophobic protein surfaces are by providing three measures for surface hydrophobicity: the total hydrophobic surface area, the relative hydrophobic surface area, and - using our MolPatch method - the largest hydrophobic patch. Secondly, we analyse how difficult it is to predict these measures from sequence: by adapting solvent accessibility predictions from NetSurfP2.0, we obtain well-performing prediction methods for the THSA and RHSA, while predicting LHP is more difficult. Finally, we analyse implications of exposed hydrophobic surfaces: we show that hydrophobic proteins typically have low expression, suggesting cells avoid an overabundance of sticky proteins.
The total conformational energy is assumed to consist of pairwise interaction energies between atoms or residues, each of which is expressed as a product of a conformation-dependent function (an element of a contact matrix, C-matrix) and a sequence-dependent energy parameter (an element of a contact energy matrix, E-matrix). Such pairwise interactions in proteins force native C-matrices to be in a relationship as if the interactions are a Go-like potential [N. Go, Annu. Rev. Biophys. Bioeng. 12. 183 (1983)] for the native C-matrix, because the lowest bound of the total energy function is equal to the total energy of the native conformation interacting in a Go-like pairwise potential. This relationship between C- and E-matrices corresponds to (a) a parallel relationship between the eigenvectors of the C- and E-matrices and a linear relationship between their eigenvalues, and (b) a parallel relationship between a contact number vector and the principal eigenvectors of the C- and E-matrices; the E-matrix is expanded in a series of eigenspaces with an additional constant term, which corresponds to a threshold of contact energy that approximately separates native contacts from non-native ones. These relationships are confirmed in 182 representatives from each family of the SCOP database by examining inner products between the principal eigenvector of the C-matrix, that of the E-matrix evaluated with a statistical contact potential, and a contact number vector. In addition, the spectral representation of C- and E-matrices reveals that pairwise residue-residue interactions, which depends only on the types of interacting amino acids but not on other residues in a protein, are insufficient and other interactions including residue connectivities and steric hindrance are needed to make native structures the unique lowest energy conformations.
Protein molecules can be approximated by discrete polygonal chains of amino acids. Standard topological tools can be applied to the smoothening of the polygons to introduce a topological classification of proteins, for example, using the self-linking number of the corresponding framed curves. In this paper we add new details to the standard classification. Known definitions of the self-linking number apply to non-singular framings: for example, the Frenet framing cannot be used if the curve has inflection points. Meanwhile in the discrete proteins the special points are naturally resolved. Consequently, a separate integer topological characteristics can be introduced, which takes into account the intrinsic features of the special points. For large number of proteins we compute integer topological indices associated with the singularities of the Frenet framing. We show how a version of the Calugareanus theorem is satisfied for the associated self-linking number of a discrete curve. Since the singularities of the Frenet framing correspond to the structural motifs of proteins, we propose topological indices as a technical tool for the description of the folding dynamics of proteins.
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