KR101681426B1 - Site-directed analysis on protein hydrophobicity - Google Patents

Site-directed analysis on protein hydrophobicity Download PDF

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KR101681426B1
KR101681426B1 KR1020150136639A KR20150136639A KR101681426B1 KR 101681426 B1 KR101681426 B1 KR 101681426B1 KR 1020150136639 A KR1020150136639 A KR 1020150136639A KR 20150136639 A KR20150136639 A KR 20150136639A KR 101681426 B1 KR101681426 B1 KR 101681426B1
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함시현
정성호
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Abstract

The present invention relates to a method for measuring a change in free energy of hydration (? G hyd ) of a protein due to an amino acid mutation, a possibility of protein aggregation due to amino acid mutation, and a risk of a protein abnormal disorder. The method of the present invention allows quantification of the hydrophobicity of the amino acid residues as contained in the protein context through protein-hydrophobic position-orientation analysis, thereby providing a better understanding of the actual structural and thermodynamic changes in vivo compared to the normal hydrophobic scale of free amino acids Reliable information can be provided. The present invention makes it possible to predict the effect of the mutation on the protein aggregation propensity and to develop a medicament for treating or preventing various protein conformational disorders and to establish a strategy for designing a cohesion-resistant protein as a biological therapeutic agent Can be used.

Description

Site-directed analysis on protein hydrophobicity

The present invention relates to a method for analyzing the hydrophobicity of proteins by applying position-directed thermodynamic analysis.

Protein aggregation is causing many human diseases. Therefore, it is an important issue to develop a preventive and therapeutic drug for protein cohesive diseases such as Alzheimer's disease, Parkinson's disease, and type 2 diabetes by identifying the intrinsic factor of proteins promoting cohesion-oriented properties in water. Protein aggregation is considered to be associated with the hydrophobic nature of protein surfaces that tend to form clusters together in aqueous solutions. Traditionally, hydrophobic scales, determined by free amino acids or side-chain analogs, have been used to deduce the hydrophobic interactions between the side chains of proteins, and the changes in protein hydrophobicity due to mutations have been observed in wild type and mutant residues The difference in hydrophobic scale was measured.

But decades ago, these "biophysical" hydrophobic scales vary significantly, especially in the case of charged amino acids, by varying the peptide bond (flanking). Recently, there has been an attempt to predict the transmembrane helix from the amino acid sequence of a " biological " hydrophobic scale. The apparent dependence of the hydrophobicity at the charge of the flanking residues as well as at the positions according to the sequence proved and gave a new dimension to the protein hydrophobic concept. In addition, for the entire ensemble of E. coli proteins, traditional sequence-based hydrophobicity failed to explain whether proteins with negatively charged residues at higher levels tend to aggregate positively charged residues relative to proteins, This suggests that a rational analysis of intrinsic cohesive propensity requires new analytical methods beyond sequence-based analysis of proteins.

In the present invention, the protein hydrophobicity of wild type and 42-residue 21 variants of amyloid-beta (A [beta] 42) protein whose aggregation is known to be associated with Alzheimer's disease is essentially disordered. First, all atomic, water (explicit water) molecular dynamics simulations were performed to sample the equilibrium solution structure of the protein, and then the integral-equation calculation of the hydration free energy was performed and the hydration free energy was calculated as water The affinity of the entire protein toward the protein, i.e., the total hydrophobicity of the protein. After proving that the calculated protein hydrophobicity is in fact related to the experimental aggregation tendency, we conducted a positional thermodynamic analysis to find out the unique molecular factors that determine protein hydrophobicity. The novel analytical method according to the present invention makes it possible to solve macroscopic thermodynamic properties at the atomic level of the protein structure and hydration structure and to identify the role of hydrophobic and hydrophilic residues in protein misfolding and aggregation processes .

In the present invention, conventional biologic hydrophobic scales are not taken into account and show how protein hydrophobicity is affected by protein global factors, such as total charge and underlying protein structure. Identification of the factors that represent the hydrophobicity of the protein makes it possible to reasonably explain and predict the effect of the variation on the protein aggregation tendency and may provide a method of designing the cohesion-resistant protein.

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Based on the amino acid sequence information, the present inventors have made extensive efforts to develop a computational analysis method capable of quantifying protein hydrophobicity and consequent flocculation potential. As a result, the hydration energy reflecting the degree of hydrophobicity of the protein is not only partially influenced by the physicochemical properties of the individual amino acid units constituting the protein as free amino acids but also changes in the total charge of the protein molecule, The present inventors confirmed that it is possible to obtain highly reliable information on the coagulation potential of the protein through establishment of a formula reflecting these variables, .

Accordingly, it is an object of the present invention to provide a method for measuring the hydration free energy (G hyd ) change (? G hyd ) of a protein due to amino acid mutation.

It is another object of the present invention to provide a method for predicting the possibility of protein aggregation due to amino acid mutations.

It is another object of the present invention to provide an assay method for determining the risk of protein conformational disease in an individual having mutated amyloid beta protein.

According to one aspect of the present invention, the present invention provides a method for measuring the hydration free energy (G hyd ) change (? G hyd ) of a protein due to an amino acid mutation comprising the steps of:

(a) change in hydration free energy by mutated amino acid residues (ΔG mut ); Change in hydration energy by charged amino acid residues (ΔG ch ); And a change (? G n-ch ) of the hydration energy by an uncharged amino acid residue; And

(b) summing the ΔG mut , ΔG ch and ΔG ch values.

Based on the amino acid sequence information, the present inventors have made extensive efforts to develop a computational analysis method capable of quantifying protein hydrophobicity and consequent flocculation potential. As a result, the hydration energy reflecting the degree of hydrophobicity of the protein is not only partially influenced by the physicochemical properties of the individual amino acid unit constituting the protein as a free amino acid but also by the total charge change of the protein molecule, (Ie, site-directed) to changes in the overall electrostatic and spatial properties, such as changes in the surface area of the substrate, And that it is possible to obtain highly reliable information about the

In order to identify the molecular factors that determine protein hydrophobicity, the present inventors have resolved the change (ΔG hyd ) of protein hydration free energy due to mutation to the residue contribution (ΔGi's) Respectively. This leads to the total intramolecular sum of hydration energy changes depending on the context of the protein, thereby enabling reliable quantification of the hydration free energy and the hydrophobic changes it reflects.

According to the present invention, the change in the free energy of hydration of a protein due to an amino acid mutation is a change in the free energy of hydration by a mutated amino acid residue; Changes in hydration energy due to charged amino acid residues; And a change in hydration energy due to an uncharged amino acid residue, which is represented by the following formula:

ΔG hyd = ΔG mut + ΔG ch + ΔG n -ch

As used herein, the term " measurement " encompasses a series of a-priori and deductive processes for deriving an unknown value utilizing specific data, and means the same as " calculation ", " prediction ", & . Thus, the term " measurement " in the present invention encompasses both experimental measurements, computational calculations on the in silico, and establishing relationships between a plurality of variables based thereon.

As used herein, the term " protein " refers to a series of macromolecules formed by peptide bonds that link together amino acid residues. Proteins are linear molecules composed of consecutive bonds of amino acid units, but the three-dimensional morphology and state change tendency are influenced by charge, hydrophobicity, formation of covalent and noncovalent bonds, overall size, total or constituent residues, And tendency to be abnormal may be the cause of various PCD (protein conformational disease) diseases.

According to a specific embodiment of the present invention, the protein to be analyzed of the present invention is an amyloid-beta protein.

According to a specific embodiment of the present invention, the change in the hydration energy (? G ch ) by said charged amino acid residues is measured using the following equation:

Figure 112015093901619-pat00001

Where Q is the change in total protein charge due to amino acid variation, Q (wt) is the total charge of the wild-type protein,

Figure 112015093901619-pat00002
Is the solvent accessible surface area change of the charged amino acid side chain due to amino acid variation,
Figure 112015093901619-pat00003
Is the solvent accessible surface area of the charged amino acid side chain of the wild-type protein, and A and B are dimensionless coefficients.

As used herein, the term " solvent accessible surface area (SASA) " refers to the surface area of biomolecules to which a solvent surrounding a biomolecule is spatially accessible. SASA is computationally computed using the rolling ball algorithm typically developed by Shrake & Rupley.

According to a specific embodiment of the present invention, the change in hydration free energy (ΔG mut ) by the mutated amino acid residue; Change in hydration energy by charged amino acid residues (ΔG ch ); And the change in hydration energy (? G n-ch ) due to the non-charged amino acid residues are measured by computer simulation.

As used herein, the term " computational simulation " refers to a simulation that predicts and reproduces behavior of a particular system using mathematical modeling using a plurality of computerized apparatuses or networks. Specifically, the computational simulation is Molecular Dynamic Simulation. Molecular dynamics simulations are computational simulations that numerically calculate the trajectory of an atom or molecule according to established physical laws and reproduce their physical motion. According to the present invention, the inventors analyzed the structural changes at the atomic level occurring through amino acid mutation by performing MD simulation for each of the wild type and 21 kinds of mutant proteins, and analyzed the thermodynamic change according to the structural change.

According to a specific embodiment of the present invention, the change in hydration energy (? G n-ch ) due to the uncharged amino acid residues is determined using the following equation:

Figure 112015093901619-pat00004

Where Q is the change in total protein charge due to amino acid variation, Q (wt) is the total charge of the wild-type protein, and?

Figure 112015093901619-pat00005
Is the solvent accessible surface area change of the main chain oxygen and nitrogen atoms of the non-charged residues due to amino acid variations,
Figure 112015093901619-pat00006
(wt) is the solvent accessible surface area of the main chain oxygen and nitrogen atoms of the non-charged residues, and C is the dimensionless coefficient.

According to another aspect of the present invention, the present invention provides a method for determining the amino acid sequence of a protein comprising the step of measuring the hydration free energy (G hyd ) change (? G hyd ) Lt; RTI ID = 0.0 > of protein < / RTI >

Hydration free energy is a quantification of the affinity of whole proteins for water, and reflects objectively the hydrophobicity of whole protein molecules. Conventional hydrophobic scales, determined from each free amino acid or side-chain structure that make up a protein, have been used to infer interphase hydrophobic interactions of proteins, but in the present invention protein global factors such as total charge and fundamental It is possible to provide a more objective measure of hydrophobicity change by quantifying hydrophobicity based on site-directed hydration free energy, which is objectively determined by the protein structure, the spatial arrangement of residues in proteins and the interactions between residues .

In accordance with another aspect of the present invention, the present invention provides a method for determining the amino acid sequence of a protein comprising the step of measuring the hydration free energy (G hyd ) change (? G hyd ) Lt; RTI ID = 0.0 > aggregation < / RTI >

As used herein, the term " protein aggregation " refers to the accumulation of misfolded proteins in a cell or extracellularly and aggregates into lumps. The term " misfolding " means that the polypeptide fails to fold normally so as to obtain a three-dimensional structure in which the protein has unique functions and activities. Since the misfolding and aggregation of proteins leads to the lack of normal proteins or the accumulation of abnormal proteins to increase the toxicity, which causes various PCD diseases, the method of the present invention can be used to predict the onset of such diseases, It can provide important information to establish.

As the hydrophobic nature of the protein surface increases, clusters tend to form in aqueous solutions, so the increase in protein aggregation potential and the increase in hydrophobicity are closely related. Therefore, the method of the present invention can provide reliable information about the hydration free energy, hydrophobicity and the possibility of flocculation of protein due to mutation.

As used herein, the term " increase in the possibility of flocculation " means a case where the amount of aggregate produced by the monomer molecules of the same concentration is significantly increased as compared with the wild-type protein molecule in which no amino acid mutation occurs.

According to another aspect of the present invention, there is provided an assay method for determining the risk of a protein conformational disease in an individual having a mutated amyloid beta protein comprising the steps of: Lt; / RTI >

(a) obtaining sequence information of a coding nucleotide of an amyloid-beta protein from a separate biological sample containing genetic information;

(b) determining a hydration free energy (Ghyd) change (ΔG hyd ) of the protein due to amino acid mutation according to any one of claims 1 to 3, using the sequence information obtained in the step (a) Measuring the value.

As used herein, the term " nucleotide " is a deoxyribonucleotide or ribonucleotide present in single or double stranded form and includes analogs of natural nucleotides unless otherwise specifically indicated (Scheit, Nucleotide Analogs, John Wiley, New York (1980); Uhlman and Peyman, Chemical Reviews, 90: 543-584 (1990)).

When the starting material of the assay for obtaining the sequence information in the method of the present invention is gDNA, the separation of gDNA can be carried out according to the conventional methods known in the art (see Rogers & Bendich (1994)).

When the starting material is mRNA, the total RNA is isolated by a conventional method known in the art (see Sambrook, J. et al., Molecular Cloning, A Laboratory Manual, 3rd ed. Cold Spring Harbor Press (1987) and Chomczynski, et al., ≪ RTI ID = 0.0 > Ausubel, < / RTI > FM et al., Current Protocols in Molecular Biology, John Willey & P. et al., Anal. Biochem. 162: 156 (1987)). The isolated total RNA is synthesized by cDNA using reverse transcriptase. Since the total RNA is isolated from a human (for example, obesity or diabetic patients), it has a poly-A tail at the end of mRNA and can easily synthesize cDNA using oligo dT primers and reverse transcriptase using such sequence characteristics (1988); Libert F, et al., Science, 244: 569 (1989); and Sambrook, J. et al., Molecular Cloning, A Laboratory Manual, 3rd ed. Cold Spring Harbor Press (2001)).

In the method of the present invention, the identification of the specific sequence may be carried out by applying various methods known in the art. For example, techniques that may be applied to the present invention include fluorescence in situ hybridization (FISH), direct DNA sequencing, PFGE analysis, Southern blot analysis, single-strand conformational analysis (SSCA, Orita et al., PNAS, USA 86: 2776 (1989)), RNase protection analysis (Finkelstein et al., Genomics, 7: 167 (1990)), dot blot analysis, denaturing gradient gel electrophoresis (DGGE, Wartell et al., Nucl. Acids Res. (Modrich, Ann. Rev. Genet., 25: 229-253 (1991)) using a protein recognizing a nucleotide mismatch (e.g., mutS protein of E. coli ) But are not limited to, allelic-specific PCR.

Since the process of calculating the hydration free energy change (ΔG hyd ) value of the protein based on the amino acid sequence information has already been described above, the description thereof is omitted in order to avoid excessive redundancy.

According to a specific embodiment of the present invention, when the hydration free energy (G hyd ) change (ΔG hyd ) of the protein due to the amino acid mutation is a positive value, the protein conformational disease) is increasing.

As used herein, the term " increased risk of a protein disorder disease " means that the probability of developing a protein disorder disease is significantly higher than that of a control subject, where the value of ΔG hyd is not positive. As used herein, the term " subject " includes without limitation humans, mice, rats, guinea pigs, dogs, cats, horses, cows, pigs, monkeys, chimpanzees, baboons or rhesus monkeys. Specifically, the object of the present invention is human.

According to a specific embodiment of the present invention, the protein conformational disease is selected from the group consisting of Alzheimer's disease, Lewy body dementia, inclusion body myositis and amyloid cerebrovascular disease cerebral amyloid angiopathy).

The features and advantages of the present invention are summarized as follows:

(a) The present invention relates to a method for measuring the free energy change of hydration (? G hyd ) of a protein due to an amino acid mutation, a method for predicting the coagulation potential of proteins due to amino acid mutations and a method for detecting a protein having mutated amyloid- And provides an assay method for determining the risk of a protein disorder disease in an individual.

(b) The method of the present invention enables quantification of the hydrophobicity of amino acid residues as contained in the protein context through protein-hydrophobicity-based position-orientation analysis, thereby realizing structural, thermodynamic Reliable information about the change can be provided.

(c) The present invention provides a method for predicting the effect of a mutation on protein aggregation propensity, development of a medicament for treating or preventing various protein conformational disorders, and a strategy for designing a cohesion-resistant protein as a biological therapeutic agent As shown in FIG.

Figure 1 shows the correlation between experimental protein aggregation propensity and protein hydrophobicity as determined by hydration free energy. Experimental aggregation tendency change at the time of mutation, log (f mut / f wt ) And the change in hydration free energy of the wild type (wt), ΔG hyd = G hyd (mut) -G hyd (wt). Pearson's correlation coefficient (R, pearson correlation coefficient) and statistical significance (P value) is also shown together.
Figure 2 shows the contribution of each residue to the change in free energy of hydration at the time of mutation. Representative variants (shown in each panel) (Figure 2a) in which hydrophobic residues are mutated into negatively charged residues (Figure 2a) and neutral hydrophilic residues (Fig. 2b), where the contribution (ΔG mut ) from the mutated site is green, the contribution (ΔG ch ) from the positively charged moiety is blue, and the negatively charged residues contribution (ΔG ch) is a red color, if it is noticeable a charge (ΔG n-ch) are expressed from the black.
FIG. 3 shows the contribution of each residue to the hydration free energy change at the time of mutagenesis, wherein representative variants (FIG. 3a) in which the hydrophobic residues are mutated into positively charged residues and variants (FIG. 3b) in which the negative charge residues are mutated positively Respectively. Contribution from the mutated region (ΔG mut) is in green, the contribution (ΔG ch) from the positively charged residues in blue, if the contribution (ch ΔG) from a negative charge moiety is a red color, that is noticeable to the charge (ΔG n- ch ) was black. In Figure 3a, in the RR (I41R, A42R) mutant residues 42, a positive change in ΔG mut is COO - is a result reflecting the neutralization of the C- terminus containing a. Fig. 3c is a re-illustration of the results of Figs. 3a-3c, together with dashed vertical bars at residues 41 and 22 based on Gi for the free amino acid.
Figure 4 shows the rationalization of the contribution of charged residues (ΔG ch ) and non-charged residues (ΔG n -ch), which is modeled by ΔG ch according to Figure 4a, Represents a dimensionless change in protein total charge,

Figure 112015093901619-pat00007
,
Figure 112015093901619-pat00008
Dimensional change of the solvent accessible surface area (SASA) of the side chain oxygen and nitrogen atoms in the charged moiety, and Figure 4b shows the corresponding dimensionless change of the solvent accessible surface area
Figure 112015093901619-pat00009
Modeling by < RTI ID = 0.0 >
Figure 112015093901619-pat00010
Represents the dimensionless change of the SASA of the main chain oxygen and nitrogen atoms of the non-charged residues, and the A, B and C parameters (in kcal / mol) determined by the least squares fit method, the Pearson correlation coefficient, R), the P value and the slope of the graph.
Figure 5 shows the effect of each residue on the change in free energy of hydration at the time of mutation. The results showed that the hydrophobic residues were mutated to negatively charged residues, and the contribution from mutated sites (ΔG mut ) was green , The contribution from the positively charged moiety (ΔG ch ) is blue, the contribution from the negatively charged moiety (ΔG ch ) is red, and the charge (ΔG n-ch ) is black. The N terminal (D1) is not believed to be charged, because it is sufficiently neutralized by the presence of the NH 3 + group.
FIG. 6 shows the effect of each residue on the change in free energy of hydration at the time of mutation, showing the results of mutants in which the hydrophobic residues were mutated into negatively charged residues, and the contribution (ΔG mut ) , The contribution from the positively charged moiety (ΔG ch ) is blue, the contribution from the negatively charged moiety (ΔG ch ) is red, and the charge (ΔG n-ch ) is black. The N terminal (D1) is not believed to be charged, because it is sufficiently neutralized by the presence of the NH 3 + group. On the other hand, the C terminal (A42) is considered to be charged because it has COO - group.
FIG. 7 shows the effect of each residue on the change of hydration free energy in the mutation, showing the results of mutants in which the hydrophobic residues were mutated to negatively charged residues, and the contribution (ΔG mut ) from the mutated sites was green , The contribution from the positively charged moiety (ΔG ch ) is blue, the contribution from the negatively charged moiety (ΔG ch ) is red, and the charge (ΔG n-ch ) is black. The N terminal (D1) is not believed to be charged, because it is sufficiently neutralized by the presence of the NH 3 + group. On the other hand, the C terminal (A42) is considered to be charged because it has COO - group.
Figure 8 shows the effect of each residue on the change in free energy of hydration at the time of mutation, showing the results of mutants in which the hydrophobic residues were mutated into negatively charged residues, and the contribution (ΔG mut ) from the mutated sites was green , The contribution from the positively charged moiety (ΔG ch ) is blue, the contribution from the negatively charged moiety (ΔG ch ) is red, and the charge (ΔG n-ch ) is black. The N terminal (D1) is not believed to be charged, because it is sufficiently neutralized by the presence of the NH 3 + group. On the other hand, the C terminal (A42) is considered to be charged because it has COO - group.
Figure 9 shows a representative structure of the wild-type A? 42 and RR (I41R, A42R) variants, wherein each structure was color-coded according to the sequence and the N and C terminals were blue to red respectively, The residues E11 and R41 of the forming RR variants are shown as spheres (C, N, O, H: orange, blue, red, white).

Hereinafter, the present invention will be described in more detail with reference to Examples and Experimental Examples. It should be understood, however, that the following Examples and Experimental Examples are provided to assist understanding of the present invention and are not intended to limit the scope of the present invention.

Example

Calculation method

1. systems

Experiments were performed on wild type and 21 variants of the A [beta] 42 protein (Table 1: experimental cohesive propensity and changes in free energy of hydration).

Figure 112015093901619-pat00011

The wild-type protein has the sequence DAEFRHDSGY EVHHQKLVFF AEDVGSNKGA IIGLMVGGVVIA. Variants include synthetic variants as well as pathogenic family variants such as Flemish (A21G), Arctic (E22G), Dutch (E22Q), Italian (E22K), and Iowa (D23N), and two C- And A42) are mutated into hydrophilic residues. All five types can be categorized based on the hydrophobicity / hydrophilicity of the mutated moieties (Table 1).

What is important in the present invention is a large difference in the experimental aggregation tendency of the mutants. Differences in the aggregation tendency of the mutant variant Aβ42 (fmut) and is quantified by log (f mut / f wt) of the wild-type Aβ42 (f wt), where f (or 1 / f) is available agglomerated in the literature It is a measure of the trend (or solubility). In the present invention, the inverse of the in vivo soluble protein levels of Flemish, Arctic, Dutch, and Italian variants for f (Ref. 24, Table 1); in vitro thio flavin -T fluorescence intensity (Ref 25 of Fig 3B..) obtained from lowa variant; And in vivo , the inverse of the fluorescence intensity when the synthetic mutant and the green fluorescent protein were fused (Ref. 23 of Ref. As a result, the log (f mut / f wt ) value is as shown in Table 1.

2. Molecular dynamics simulation

For each of the wild type and 21 variant proteins, all atomic, water-molecular dynamics simulations were performed using the AMBER11 simulation package at temperature conditions of T5300 K and pressure of P51 bar. Independent product runs of 100 ns long (i.e., 1 μs cohesive simulation time) were performed for each system. In the present invention, the ff99SB force field and the TIP4P-Ew model were used for water. The simulation was performed under neutral pH, where Lys and Arg were positively charged and Glu and Asp were negatively charged. Wild-type A [beta] 42 had a -3 charge, while the total protein charge of the mutants varied according to mutants (Table 1). The particle mesh Ewald method was applied to long-range electrostatic interactions, and a 10 Å cutoff was applied to short-range non-bonding interactions. The hydrogen atoms were constrained to the equilibrium bond length using the SHAKE algorithm and simulated in 2 fs time steps. Temperature and pressure were controlled with a Berendsen thermostat and pressure regulator with 1.0 and 2.0 ps coupling constants, respectively.

Because the A.beta.42 protein in its monomeric state is inherently disordered, there is no atomic structure experimentally possible in the aqueous environment, and the initial protein structure of the 10 independent product runs was produced through heating / annealing simulations See literature). High temperature (600 K) simulations were performed to generate 10 independent protein forms and annealed stepwise to 300 K. The starting form in simulating the heating / annealing of wild-type A? 42 was obtained from the NMR structure in a non-polar solvent (Protein Data Bank (PDB) ID: 1IYT). The starting form of the A [beta] 42 variant was generated in the Swiss PDB viewer based on the 1IYT structure. The inventors have found that the simulated structures obtained for wild-type A? 42 are consistent with experimentally obtained NMR J-coupling constants, CD spectra, NMR chemical-shift-index analysis, and NOE (nuclear Overhauser effect) strength analysis.

3. Hydration Free Energy and Position Orientation Analysis

For each simulation system, the present invention takes 20,000 protein forms at 50 ps time intervals from 1 μs (10 × 100 ns) length product runs. In the present invention, the 3D-RISM (three-dimensional reference interaction site model) theory is applied to each type of protein to be simulated for hydration free energy calculation. The 3D-RISM theory is an integral equation theory based on statistical mechanics to obtain the 3D distribution function g? (R) at the position r of the water region? Surrounding the molecular solute such as protein. In infinite dilution, the 3D-RISM theory for a solute-solvent system is given by:

Figure 112015093901619-pat00012
(One)

Here, h ? (R) and c ? (R) respectively represent a global and direct correlation function of 3D in the water region?; The asterisk is a convolution integral;

Figure 112015093901619-pat00013
And
Figure 112015093901619-pat00014
Represents the intramolecular and total correlation function of the site-site molecules of water; and ρ is the average number density of water. The above equation can be supplemented by an approximate closure relation, and in the present invention the one developed by Kovalenko and Hirata is applied:

Figure 112015093901619-pat00015
(2)

d γ (r) = - u γ (r) / K B T + h γ (r) represents the Boltzmann constant K B is in the -c γ (r). U γ (r) represents the interaction potential acting on the water moiety γ produced by an atom in the protein, and Lennard-Jones (LJ) and Coulomb electrostatic terms in the protein interaction site α center of position r α , ≪ / RTI >

Figure 112015093901619-pat00016
to be. From here,
Figure 112015093901619-pat00017
ego,
Figure 112015093901619-pat00018
Lt;
Figure 112015093901619-pat00019
,
Figure 112015093901619-pat00020
,
Figure 112015093901619-pat00021
And
Figure 112015093901619-pat00022
The
Figure 112015093901619-pat00023
Parameter and atomic charge. In the present invention, a numerical method as described in reference 38 was used to consistently solve equations (1) and (2). The water distribution function
Figure 112015093901619-pat00024
Lt; / RTI >

The contribution of the hydration free energy Ghyd and its contribution from the atomic [ alpha] to G [alpha] can be calculated from the number distribution function based on the Kirkwood charge equation:

Figure 112015093901619-pat00025
(3)

In this formula,

Figure 112015093901619-pat00026
(4)

Figure 112015093901619-pat00027
(5)

Here,? 1 and? 2 are the LJ parameters (

Figure 112015093901619-pat00028
) And protein atomic charge (
Figure 112015093901619-pat00029
), And the resulting interaction potential is a parameter for scaling
Figure 112015093901619-pat00030
Respectively,
Figure 112015093901619-pat00031
Refers to the radiation distribution function and is associated with a 3D distribution function for the parameters [lambda] 1 and [lambda] 2 .
Figure 112015093901619-pat00032
)
Figure 112015093901619-pat00033
ego,
Figure 112015093901619-pat00034
,
Figure 112015093901619-pat00035
to be.

Through the formulas (3) to (5), it is possible to decompose into the contribution from the group of atoms (i.e., residues) of G hyd and decompose them into respective components of potential energy terms (i.e., electrostatic terms). The main limitation of the 3D-RISM theory is that it uses an approximate closure relation. In the present invention, there is a main focus on the change in hydration free energy during mutation, and as evidenced above, the change in free energy is dependent on electrostatic factors. The present invention also showed that the electrostatic contributions were consistent with those calculated by the 3D-RISM theory. The analytical method according to the present invention has an advantageous effect that it is not stale because of the limitations of the integral-equations theory.

Experiment result

1. Protein hydrophobicity and aggregation tendency

For the wild type and 21 variants of the A? 42 protein described in Table 1, an explicit water-molecular dynamics simulation was performed to sample their equilibrium solution structure. The hydration free energy G hyd was calculated by solving the integral equation separately for each shape and assigned to the integral equation theory for the simulated protein form and the derived mean G hyd was identified as the protein total hydrophobicity: The more positive G hyd values are associated with increased protein hydrophobicity, and the inverse is also the same. The change in protein hydrophobicity in the mutants was quantified as a change in the hydration free energy of the mutant (mut) and wild-type (wt) proteins, ΔG hyd = G hyd (mut) -G hyd (wt). As shown in Fig. 1, the present invention shows that there is a statistically significant correlation between the calculated hydration free energy change? G hyd and the experimental aggregation tendency change in the mutants. The matched results were also derived from the N-terminal domain of the acyl phosphatase and the E. coli protein HypF: experimentally higher (lower) aggregation tendencies in mutants were found to be associated with increased (reduced) hydration free energy Respectively. From these results, it can be seen that the protein hydrophobicity quantified by the hydration free energy can act as a protein aggregation tendency value in the aqueous environment.

2. Hydrophobicity of residues in protein constructs

To characterize the molecular factors that determine protein hydrophobicity, the change in hydration free energy (ΔG hyd ) in variants was resolved into residue contribution (ΔGi's) (ΔG hyd =

Figure 112015093901619-pat00036
, Figures 2 and 3). In the present invention, Gi is the hydration free energy of the i-th residue in the presence of other residues in the protein, and is generally different from that for free amino acids. In fact, ΔGi = Gi (mut) -Gi (wt) will be zero if the Gi for the free amino acid is used, except for mutated residues, and substantially change ΔGi values for residues other than the mutated site Is present indicates that Gi is dependent on the protein context. ΔGi thus represents a change in "residue hydrophobicity" in the variant. Each ΔG i can be grouped into contributions from the mutated residue ΔG mut , the charged residue ΔG ch and the non-charged remainder ΔG n-ch , (6): < RTI ID = 0.0 >

ΔG hyd = ΔG mut + ΔG ch + ΔG n -ch (6)

The results of the division are summarized in Table 1. [

From the results in Table 1, it was found that the mutated region (ΔG mut ) has a major contribution to the protein hydrophobicity change (ΔG hyd ) in most cases. The ΔG mut in most variant types can be understood qualitatively in terms of conventional hydropathic scales: a decrease in the hydrophobicity of the mutated site or an increase in hydrophilicity leads to a more favorable hydration (ΔG Mut is related to the negative change, and vice versa.

For example, if ΔG mut of DQ (I41D, A42Q), EL (I41E, A42L), HN (I41H, A42N), and TN (I41T, A42N) mutants show a negative change, As shown in Fig. At residue 41 of DQ (I41D, A42Q) and EL (I41E, A42L) ΔG mut showed a very large decrease (Figure 2a), reflecting the fact that charged residues are much more hydrated than neutral residues do. Conversely, ΔG mut was significantly increased when the charged residue was changed to a neutral residue (Supporting Information Figure S4 for Arctic (E22G), Iowa (D23N), and Dutch (E22Q) mutants).

3. Effect of total-charge on residue hydrophobicity

On the other hand, ΔG mut in the variant types shown in Table 1, including positively charged residues, can not be explained solely by the side chain characteristics. According to conventional hydrophobic scales, hydrophilicity of positively charged residues (Lys and Arg under neutral pH) and negatively charged (Asp and Glu) residues are compared. However, the hydrophobic moiety (I41) is, KL (I41K, A42L) and RR (I41R, A42R) reduction in ΔG mut at residue 41 in the mutant (Fig. 3a) to be mutated to a residue (K or R) positively charged, the free (Fig. 3C) than that predicted from the hydrophobicity of the amino acids.

In addition, ΔG mut was significantly increased in the Italian (E22K) variants, in which negatively charged residues (E) were mutated to positively charged residues (K) (FIG. 3b). Based on the conventional hydrophobic scale, the ΔG mutt of the mutant will not be as pronounced as the hydrophilicity of E22 and is comparable to K22 (FIG. 3c). In fact, the sequence-based model only predicts small changes in the aggregation tendency of the Italian (E22K) variant of the A [beta] 42 protein (see Figure 2b in Ref. 4). The " abnormal " behavior of mutants containing such positively charged moieties can be understood in terms of a long-distance hydration structure that reflects the protein total charge. Due to the long-range nature of the electrostatic interactions, the long-range hydration structure of charged residues is also affected by nearby charged residues: the equilibrium water distribution is the net charge generated by these residues The net charge determines the leading order. The net net charge of A? 42 (? 3 in the case of wild type) is calculated as an equilibrium orientational distribution of these surrounding water molecules, and the hydrogen in the water molecule is directed to the protein. This result in unfavorable electrostatic interaction between positively charged residues and water molecules suggests that the hydration free energy in the positively charged residues of A? 42 is much more positive than that for free amino acids As shown in Fig. This shows the effect of net protein charge on residual hydrophobicity of the charged moiety.

4. Effects of structural features on residue hydrophobicity

So far, we have focused on the contribution to protein hydrophobicity (ΔG mut ) at the mutation site, but the contribution from other moieties (ΔG ch and ΔG n -ch ) also greatly affect protein hydrophobicity (Table 1). As noted above, non-zero ΔG ch and ΔG n -ch reflect the fact that the residues are embedded in the protein context. Theoretical explanations of non-zero variations of ΔG ch and ΔG n -ch include the change in protein shape at the time of mutation and the protein total charge effect considered above .

ΔG ch values are susceptible to systematic variations due to changes in protein total charge (ΔQ) at the time of mutation (Table 1): when the total protein charge at mutation decreases (ΔQ <0), positive Negatively) charged residues always provide a positive (negative) contribution to ΔG ch (Fig. 2a), and the opposite tendency is observed when protein net charge increases at mutation (Fig. 3a-3b) 0). Thus, this contribution to? G ch can be modeled as proportional to? Q.

Changes in protein structure, particularly the formation of salt-bridges or hydrogen bonds in charged side chains, cause dehydration and have a significant effect on the hydration free energy. Here, the solvent accessible surface area of the charged side chain (

Figure 112015093901619-pat00037
), The structural effect of the protein on? G ch was modeled:

Figure 112015093901619-pat00038
(7)

Here, the change in protein total charge at the time of mutation is Q = Q (mut) -Q (wt), and the change in solvent accessible surface area

Figure 112015093901619-pat00039
=
Figure 112015093901619-pat00040
, And the change value was normalized to the value of the wild type protein, so that the coefficients A and B became dimensionless. The minus sign of the second term is dehydration (
Figure 112015093901619-pat00041
) Is associated with an increase in hydrophobicity (a positive variation of? G ch ). ΔG ch is in fact ΔQ and
Figure 112015093901619-pat00042
(I.e., A < B), and the latter provides a greater contribution.

This shows the relevance of the structural effects of proteins to determine residue hydrophobicity, ie, protein hydrophobicity. At non-change (ΔQ = 0) variation of total protein charge, the non-charged residue contribution (ΔG n -ch ) becomes relatively important (Table 1). As shown in Figure 4b, the solvent accessible surface area of the? G n -ch and main chain oxygen and nitrogen atoms

Figure 112015093901619-pat00043
), And the equation is as follows: &lt; RTI ID = 0.0 &gt;

Figure 112015093901619-pat00044
(8)

Figure 112015093901619-pat00045
Is sensitive to the content of the backbone hydrogen bond, i.e., the secondary structure of the protein. Although the A [beta] 42 protein is inherently disordered in the aquatic environment, it is not a homogeneous statistical random coil polymer and instead represents a substantial amount of residue secondary structure, the content of which varies with variation. From the results of FIG. 4 (b), it can be seen that protein hydrophobicity can also be influenced by the protein secondary structure.

Additional discussion

The hydrophobic effect is considered as one of the major traction factors for protein folding and biological tissue. In a broad sense, protein aggregation may be thought of as a "phobia" of water, just as aggregated proteins prefer to be next to each other rather than fully surrounded by water. However, protein surfaces usually contain both hydrophobic and hydrophilic moieties, and it remains a fundamental challenge to determine how to determine hydrophobicity, and how to engage in actual biological processes. In fact, on average about 70% protein-protein interfaces are found in hydrophilic residues, about 37% including charged residue contributions, and in protein-protein interactions, hydrophilic residues are more relevant. The total protein hydrophobicity quantified by hydration free energy indicates the affinity of the entire protein towards water affected by both the hydrophobic and hydrophilic component residues. Because of this, the surface is commonly applied to proteins that exhibit a wide range of chemical heterogeneity and has been found to be a crucial factor in understanding protein aggregation tendencies. Here, through the positional orientation analysis of protein hydrophobicity, the hydrophobicity of the residue - the hydrophobicity of the amino acid residues contained in the protein context - has proven to be largely deviated from the usual hydrophobic scale of the corresponding free amino acid. In particular, the hydrophobicity of the charged residues on the surface of the protein is very different from that of conventional biologically charged free amino acids. Also, for positive and negatively charged residues, contrasting behavior has been observed, which can be explained in terms of a long-distance hydration structure that reflects the net charge of the protein. This can rationalize the asymmetric role of positively and negatively charged residues in describing protein coagulation properties in E. coli proteins because the net charge of these proteins is usually negative in physiological states. Protein hydrophobicity is also affected by the underlying protein structure. In particular, salt-bridges formed between charged moieties on the protein surface effectively neutralize and cause dehydration of such salt-bridged residues. This causes the residue-water interaction in the short-distance regime to be significantly attenuated and to increase the hydration free energy of the salt-bridged moiety on the protein surface. Structural changes and related hydration structural effects of these proteins are not considered in a sequence-based model for predicting protein aggregation propensity. For example, we found that the charged side chain of Arg41 of the RR (I41R, A42R) variant forms a salt-bridge in a simulated structure of about 33% (see FIG. 9). This leads to a significant increase in the protein hydrophobicity of the RR variants, and the experimental observations show that the RR variants exhibit much higher agglomeration tendencies than predicted from the increased biophysical hydrophobicity at the C-terminal end . Structural effects on protein hydrophobicity affect the interaction between protein hydration and protein-protein interactions during the aggregation process. The inventors of the present invention have recently demonstrated that water-mediated attraction, which can be quantified by free hydration energy, is largely isolated from the two cohesive proteins and is therefore primarily responsible for approaching the contact distance (See Reference 21). After the two monomers begin to atomic contact, direct protein-protein interactions play a role, leading to intermonomer salt-bridge, hydrogen bonding and van der Waals contacts. This structural change inevitably entails dehydration of the interface region (i.e., reduction in solvent accessible surface area), which increases the hydrophobicity of the dimer formed (see Equations 7 and 8). The increased hydrophobicity of the dimer will eventually serve as a driving force for attracting other proteins in subsequent oligomerization processes.

conclusion

Understanding the molecular determinants of protein hydrophobicity is crucial to rationalizing and predicting protein aggregation propensity. The inventors of the present invention have explored how the hydrophobicity of the amino acid residues depends on the context impregnated with the protein, which was not a consideration in the conventional hydrophobic scale. It has been found that residue hydrophobicity is significantly affected not only by protein global factors such as total charge, but also by the underlying protein form, and the resulting protein hydrophobicity can not be completely addressed by the amino acid sequence alone.

The positional orientation analysis method according to the present invention can predict the effect of the mutation on the protein aggregation propensity by simultaneously treating not only the three-dimensional structure of the protein but also its hydration thermodynamics, and can be applied to a wide range of fields such as protein science and biotherapeutics .

Claims (11)

A method for measuring the hydration free energy (G hyd ) change (? G hyd ) of a protein due to an amino acid mutation comprising the steps of:
(a) change in hydration free energy by mutated amino acid residues (ΔG mut ); Change in hydration energy by charged amino acid residues (ΔG ch ); And a change (? G n-ch ) of the hydration energy by an uncharged amino acid residue; And
(b) the step of adding the mut ΔG, ΔG and ΔG ch n-ch value.
The method according to claim 1, wherein the change (? G ch ) of the hydration energy due to the charged amino acid residues is measured using the following equation:
Figure 112015093901619-pat00046

Where Q is the change in total protein charge due to amino acid variation, Q (wt) is the total charge of the wild-type protein,
Figure 112015093901619-pat00047
Is the solvent accessible surface area change of the charged amino acid side chain due to amino acid variation,
Figure 112015093901619-pat00048
Is the solvent accessible surface area of the charged amino acid side chain of the wild-type protein, and A and B are dimensionless coefficients.
The method according to claim 1, wherein the change (? G n -ch ) of the hydration energy by the non-charged amino acid residue is measured using the following equation:
Figure 112015093901619-pat00049

Where Q is the change in total protein charge due to amino acid variation, Q (wt) is the total charge of the wild-type protein, and?
Figure 112015093901619-pat00050
Is the solvent accessible surface area change of the main chain oxygen and nitrogen atoms of the non-charged residues due to amino acid variations,
Figure 112015093901619-pat00051
(wt) is the solvent accessible surface area of the main chain oxygen and nitrogen atoms of the non-charged residues, and C is the dimensionless coefficient.
The method of claim 1, wherein the change in free energy of hydration (? Gmut ) by the mutated amino acid residue; Change in hydration energy by charged amino acid residues (ΔG ch ); And the change of the hydration energy (? G n-ch ) due to the non-charged amino acid residues is performed using computer simulation.
5. The method of claim 4, wherein the computational simulation is a Molecular Dynamic Simulation.
A method for detecting a protein due to an amino acid mutation comprising measuring a hydration free energy (G hyd ) change (ΔG hyd ) value of a protein due to an amino acid mutation using the method of any one of claims 1 to 5, Lt; RTI ID = 0.0 &gt; hydrophobicity &lt; / RTI &gt;
A method for detecting a protein due to an amino acid mutation comprising measuring a hydration free energy (G hyd ) change (ΔG hyd ) value of a protein due to an amino acid mutation using the method of any one of claims 1 to 5, Lt; RTI ID = 0.0 &gt; aggregation &lt; / RTI &gt;
8. The method of claim 7, wherein the protein is an amyloid beta protein.
An analytical method for determining the risk of a protein conformational disease in an individual having a mutated amyloid beta protein comprising the steps of:
(a) obtaining sequence information of a coding nucleotide of an amyloid-beta protein from a separate biological sample containing genetic information; And
(b) a hydration free energy (G hyd ) change (ΔG hyd ) of the protein due to amino acid mutation according to any one of claims 1 to 3, using the sequence information obtained in the step (a) ) &Lt; / RTI &gt;
The method according to claim 9, wherein, when the hydration free energy (G hyd ) change (ΔG hyd ) of the protein due to the amino acid mutation is a positive value, the risk of the protein conformational disease Is determined to be increased.
11. The method of claim 10, wherein the protein conformational disease is selected from the group consisting of Alzheimer ' s disease, Lewy body dementia, inclusion body myositis, and cerebral amyloid angiopathy ). &Lt; / RTI &gt;
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