Multi-state proteins: approach allowing experimental determination of the formation order of structure elements in the green fluorescent protein.

The most complex problem in studying multi-state protein folding is the determination of the sequence of formation of protein intermediate states. A far more complex issue is to determine at what stages of protein folding its various parts (secondary structure elements) develop. The structure and properties of different intermediate states depend in particular on these parts. An experimental approach, named μ-analysis, which allows understanding the order of formation of structural elements upon folding of a multi-state protein was used in this study. In this approach the same elements of the protein secondary structure are "tested" by substitutions of single hydrophobic amino acids and by incorporation of cysteine bridges. Single substitutions of hydrophobic amino acids contribute to yielding information on the late stages of protein folding while incorporation of ss-bridges allows obtaining data on the initial stages of folding. As a result of such an μ-analysis, we have determined the order of formation of beta-hairpins upon folding of the green fluorescent protein

Substitutions of Amino Acids with Large Number of Contacts in the Native State Have No Effect on the Rates of Protein Folding

Various effects of amino acid substitutions on properties of globular proteins have been described in a large number of research papers. Nevertheless, no definite “rule” has been formulated as of yet that could be used by experimentalists to introduce desirable changes in the properties of proteins. Herein we attempt to establish such a “rule”. To this end, a hypothesis is proposed on the effects of substitutions of hydrophobic residues with large number of contacts on free energies of different states of a globular protein. The hypothesis states: Substitutions of hydrophobic residues engaged in a large number of residue-residue contacts would not change the folding rate of a protein but could affect its unfolding rate. This hypothesis was verified by both theoretical and experimental analyses, generating a general rule that can facilitate the work of experimentalists on constructing mutant forms of proteins

Sequential Melting of Two Hydrophobic Clusters Within The Green Fluorescent Protein Gfp-cycle3

The analysis of the three-dimensional structure of green fluorescent protein (GFP-cycle3) revealed the presence of two well-defined hydrophobic clusters located on the opposite sides of the GFP β-can that might contribute to the formation of partially folded intermediate(s) during GFP unfolding. The microcalorimetric analysis of the nonequilibrium melting of GFP-cycle3 and its two mutants, I14A and I161A, revealed that due to the sequential melting of the mentioned hydrophobic clusters, the temperature-induced denaturation of this protein most likely occurs in three stages. The first and second stages involve melting of a smaller hydrophobic cluster formed around the residue I161, whereas a larger hydrophobic cluster (formed around the residues I14) is melted only at the last GFP-cycle3 denaturation step or remains rather structured even in the denatured state

Ss-stabilizing Proteins Rationally: Intrinsic Disorder-based Design of Stabilizing Disulphide Bridges in GFP

The most attractive and methodologically convenient way to enhance protein stability is via the introduction of disulphide bond(s). However, the effect of the artificially introduced SS-bond on protein stability is often quite unpredictable. This raises the question of how to choose the protein sites in an intelligent manner, so that the ‘fastening’ of these sites by the SS-bond(s) would provide maximal protein stability. We hypothesize that the successful design of a stabilizing SS-bond requires finding highly mobile protein regions. Using GFP as an illustrative example, we demonstrate that the knowledge of the peculiarities of the intramolecular hydrophobic interactions, combined with the understanding of the local intrinsic disorder propensities (that can be evaluated by various disorder predictors, e.g., PONDRFIT), is sufficient to find the candidate sites for the introduction of stabilizing SS-bridge(s). In fact, our analysis revealed that the insertion of the engineered SS-bridge between two highly flexible regions of GFP noticeably increased the conformational stability of this protein toward the thermal and chemical unfolding. Therefore, our study represents a novel approach for the rational design of stabilizing disulphide bridges in proteins

Arrhenius plots of GFP<i>-</i>cycle3 and its mutant forms.

<p>Dependencies of logarithms of rate constants of the first (<i>k</i>₁) (solid line in the figures) and second (<i>k</i>₂) (dashed line) stages of GFP<i>-</i>cycle3 heat denaturation versus inverse temperature calculated from melting curves of GFP<i>-</i>cycle3 (gray lines) and its mutant forms (colored lines). <b>A</b>, the plots are related to singular substitutions of hydrophobic amino acids. <b>B</b>, the plots are related to double substitutions for cysteines with an ss-bridge between them. <b>C</b>, the plots are related to double substitutions for cysteines modified with iodoacetamide (an ss-bridge is not formed).</p

GFP<i>-</i>cycle3 structure formation.

<p>Sequence of formation/distortion of secondary structure elements of GFP<i>-</i>cycle3 based on the results of multimutational analysis. <i>N, I₁, I₂, D</i>, and <i>U</i> are native, two intermediate, denatured and unfolded states of the protein, respectively. At the first stage of unfolding (<i>N</i>→<i>I₁</i>) the packing of amino acids on the protein surface is impaired, but the packing of the hydrophobic nucleus as well as the entire packing of the protein chain are not distorted. During the following stage (I<i>₁</i>→<i>I₂</i>) the structure of β-strands (shown in yellow color) is changed (in the region of amino acids 90–130). After that the protein unfolds almost completely (<i>I₂</i>→<i>D</i>), excluding three β-strands in the region of amino acids 10–50 which at “mild” denaturation remain structured in the unfolding state. The last stage (<i>D</i>→<i>U</i>), when the total protein acquires a coil-like conformation, is probable only under the action of strong denaturants.</p

Rate constants of GFP-cycle3 unfolding obtained with the fluorescence method is well compatible with the same obtained with the calorimetry method.

<p>(<b>A</b>) Typical kinetic unfolding curves of GFP-cycle3 at pH 6.2 caused by a temperature jump from 293.2 K to 346.5 K, 349.2 K and 352.6 K, accordingly. The curves (noisy lines) were well fitted to two exponentials (continuous lines). Residual plot for fitting is shown in the upper panel. (<b>B</b>) Dependences of the logarithm of rate constants (<i>k₁</i> and <i>k₂</i>) of unfolding of GFP-cycle3 versus reverse temperature. Rate constants obtained with the fluorescence method are shown by symbols. Rate constants obtained from calorimetric experiments are shown by lines.</p

Choice of mutations in GFP-cycle3.

<p>End view (A) and side view (B) of the voluminous model of the GFP-can. Four structure elements are shown individually: (C–E) three β-sheets and (F) β-hairpin. Balls denote amino acids substituted for alanine (I14, V112, I161, L201) and pairs of amino acids substituted for cysteines (V11 and D36, V93 and Q111, K162 and Q184, S202 and T225). Plot G shows the amount of residue-residue contacts of each amino acid residue (a contact distance is 6 Å. Black columns denote hydrophobic amino acids. Coloured lines at the bottom of plot G denote the position of β-strands in structure elements C–F. Coloured circles in plot G show columns referring to amino acids substituted for alanine. Coloured circles connected by a line at the bottom of the plot mark pairs of amino acids substituted for cysteines.</p

Effect of single amino acids substitutions on GFP<i>-</i>cycle3 unfolding rate constants.

<p>Change of logarithms of unfolding rate constants for GFP<i>-</i>cycle3 mutant proteins with single amino acids substitutions as compared to the WT (GFP<i>-</i>cycle3) protein: ΔLn(<i>k</i>_1,2) = ΔLn(<i>k</i>_1,2)_mut− ΔLn(<i>k</i>_1,2)_WT.</p