A sequence-based method and system for predicting the spring constant of an elastomeric protein

Abstract

This invention discloses a sequence-based method and system for predicting the spring constant of elastomeric proteins, belonging to the field of bioinformatics. The prediction method includes: obtaining the amino acid sequence of the protein to be analyzed; and calculating the spring constant of the protein. Starting from the amino acid sequence, this invention integrates motif identification and elastic mechanical property calculation into the same sequence analysis workflow, solving the problems faced by researchers studying elastomeric proteins, such as the lack of targeted analytical tools and the high cost and time-consuming nature of experimental determination of physicochemical properties. This improves the research efficiency of elastomeric proteins and reduces R&D costs.

Description

Technical Field

[0001] This invention belongs to the field of bioinformatics technology, specifically relating to a method and system for predicting the spring constant of an elastomer protein based on sequence. Background Technology

[0002] Elastomer proteins are a class of biomolecular materials with significant application value, including natural elastin, proelastin, and elastin-like peptides. Natural elastin is widely found in tissues such as skin, blood vessels, lungs, and ligaments, providing them with excellent elasticity and flexibility. Elastin-like peptides are typically composed of repetitive sequences derived from the hydrophobic domains of elastin, such as VPGXG pentapeptide repeat units, and generally exhibit temperature responsiveness, self-assembly, and reversible phase transition properties in aqueous solutions. Due to their good biocompatibility, designability, and environmental responsiveness, these materials have high application potential in drug delivery, tissue engineering, bioseparation and purification, thermosensitive hydrogels, biosensor materials, and regenerative medicine.

[0003] Currently, there is a lot of research on temperature-responsive elastomer protein materials. For example, the existing technology CN119331077A discloses an elastin-like polypeptide, its preparation method and application, and the amino acid sequence of the elastin-like polypeptide is (VPGXG). n Existing technology CN115724916A also discloses an elastin-like polypeptide (VPTGIG). 25 Its preparation method and applications, and the amino acid sequence of its elastin-like polypeptide is (VPTGIG). 25 Both elastomeric proteins and elastomers exhibit reversible phase transition behavior. However, the function of elastomers largely depends on specific sequences. For new candidate sequences, extensive experimentation is usually required to determine their phase transition temperature and elastic constant. Existing technology CN116102172A discloses a high-throughput computation-based method for predicting elastomeric proteins, which can use algorithms to predict whether a protein is an elastomeric protein. However, it can only achieve a qualitative judgment based on the amino acid sequence to determine whether a protein is an elastomeric protein; it still cannot provide a meaningful prediction of key performance parameters such as the phase transition temperature and elastic constant of elastomeric proteins. When faced with the problem of screening elastomeric proteins that meet the performance requirements, extensive experimental verification is still necessary, resulting in significant expenditure of human and material resources.

[0004] Therefore, there is an urgent need to develop a tool-based method that can directly identify motifs based on amino acid sequences and quantitatively calculate elastic constants during the candidate sequence design stage of elastomeric proteins, thereby providing a quantitative basis for the sequence design and high-throughput screening of elastomeric materials. Summary of the Invention

[0005] In order to overcome the above-mentioned shortcomings of the existing technology, the purpose of this invention is to provide a sequence-based method and system for predicting the features of elastomeric proteins.

[0006] The objective of this invention is achieved by at least one of the following technical solutions.

[0007] In a first aspect, the present invention provides a method for predicting the spring constant of an elastomer protein based on a sequence, the method comprising:

[0008] The spring constant includes the entropic elastic spring constant and the hydrophobic elastic spring constant;

[0009] The hydrophobic elastic spring constant k hyd Predicting rebound using a hydrophobic interaction-driven rebound model:

[0010] ,

[0011] Where γ is the surface tension constant; H is the average hydrophobicity score of the sequence; SASAmax is the maximum solvent-accessible surface area in the stretched state; Rg is the mean square radius of gyration; N is the total number of residues in the sequence; and Ree is the mean square end-to-end distance.

[0012] Furthermore, the entropy elastic spring constant k ent Predicted using the entropy spring effect model:

[0013] ,

[0014] Where, k B Boltzmann constant; T: absolute temperature; Rg: mean square radius of gyration; Ree: mean square end-to-end distance.

[0015] Furthermore, the elastomeric proteins include natural elastomeric proteins, extrin, elastomeric polypeptides, natural elastomeric fragments or variants, extrin fragments or variants, elastomeric polypeptide variants, and fusion proteins containing elastomeric repeat sequences.

[0016] Secondly, the present invention also provides a sequence-based prediction system for the spring constant of elastomeric proteins, the system comprising:

[0017] The calculation module is used to calculate the spring constant of the elastomer protein;

[0018] The spring constant includes the entropic elastic spring constant and the hydrophobic elastic spring constant;

[0019] The hydrophobic elastic spring constant khyd is predicted by the rebound model driven by hydrophobic interaction:

[0020] ,

[0021] Where γ is the surface tension constant; H is the average hydrophobicity score of the sequence; SASAmax is the maximum solvent-accessible surface area in the stretched state; Rg is the mean square radius of gyration; N is the total number of residues in the sequence; and Ree is the mean square end-to-end distance.

[0022] The entropy elastic spring constant k ent Predicted using the entropy spring effect model:

[0023] ,

[0024] Where, k B Boltzmann constant; T: absolute temperature; Rg: mean square radius of gyration; Ree: mean square end-to-end distance.

[0025] Thirdly, the present invention also provides an apparatus comprising at least one storage medium and at least one processor, the at least one storage medium being used to store computer instructions, and the at least one processor being used to execute the computer instructions to implement the sequence-based method for predicting the spring constant of elastomeric proteins as described in the first aspect.

[0026] Fourthly, the present invention also provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the sequence-based method for predicting the spring constant of an elastomer protein as described in the first aspect.

[0027] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0028] This invention starts with amino acid sequences to automatically identify motifs related to elastomeric proteins and further calculates spring parameters. It integrates motif identification and mechanical property (spring constant) calculation into the same sequence analysis process, which can provide multi-dimensional evaluation for the design of elastomeric proteins.

[0029] This invention enables the prediction of the spring constant of elastin, providing a prediction range for the spring constant of elastin for the first time. The prediction range can accurately cover the true spring constant of elastin, which can significantly reduce the experimental cost in the research and development stage, thereby improving research and development efficiency. Attached Figure Description

[0030] Figure 1 For example, the duration L of Example 1 p Comparison chart (based on entropy, elastic spring constant k) ent Hydrophobic elastic spring constant k hyd The predicted value is converted into the duration L. p The following diagram is drawn, where L is the number of digits. p,expL is the experimental value for the duration. p，ent For predicting the duration of entropy elasticity, L p，hyd (Predicting the duration of hydrophobic elasticity).

[0031] Figure 2 L, as in Example 1 p Predicted value and L p Comparison chart of experimental value trends (based on entropy, elastic spring constant k) ent Hydrophobic elastic spring constant k hyd The predicted value is converted into the duration L. p The following diagram is drawn, where L is the number of digits. p,exp L is the experimental value for the duration. p，hyd Figure A shows the predicted duration of hydrophobic elasticity; Figure B shows the trend synchronization analysis; Figure B shows the bivariate linear correlation analysis. Detailed Implementation

[0032] The specific implementation of the present invention will be further described below with reference to the accompanying drawings and examples, but the implementation and protection of the present invention are not limited thereto. It should be noted that any processes not specifically described in detail below are those that can be implemented or understood by those skilled in the art by referring to the prior art. Reagents or instruments whose manufacturers are not specified are considered to be conventional products that can be purchased commercially.

[0033] In this invention, "elastin-like polypeptide" refers to an engineered, recombinant, synthetic, or semi-synthetic polypeptide comprising one or more amino acid repeating sequence units derived from, mimicking, or modified from natural elastin or protoelastin. The elastin-like polypeptide includes, but is not limited to, elastin-like repeating polypeptides, elastin-like block polypeptides, silk-elastin-like polypeptides, collagen-elastin-like fusion polypeptides, elastin-like polypeptides containing cell adhesion sequences, elastin-like polypeptides containing enzyme cleavage sites, elastin-like polypeptides containing cross-linking sites, as well as fragments, mutants, variants, derivatives, fusions, covalently modified products, or cross-linked products of the above polypeptides. The elastin-like polypeptide preferably possesses at least one elastin-like characteristic, including elastic recovery, flexibility, reversible phase transition, temperature responsiveness, self-assembly, cross-linkability, biocompatibility, the ability to form an elastic network, or a combination thereof.

[0034] In this invention, "motif identification" refers to the process of matching, scanning, comparing, and statistically analyzing the amino acid sequence of the protein to be analyzed based on preset motif rules or a motif database to determine whether an elastin motif exists in the amino acid sequence, and to obtain the type, quantity, location, repetition, significance parameters, matching score, and confidence level of the elastin motif. Elastin motifs include, but are not limited to, hydrophobic motifs, receptor-binding motifs, cross-linking motifs, cell adhesion motifs, and structural organization motifs.

[0035] In this invention, "guest residue" refers to a variable amino acid residue in the repeating unit of an elastomeric protein, such as the X1 amino acid residue in VPGX1G.

[0036] In this invention, "solvent-accessible surface area" refers to the total surface area of ​​a protein molecule that can be contacted by water molecules or solvent molecules.

[0037] In this invention, "hydrophobic solvent-accessible surface area" refers to the surface area of ​​a protein surface molecule that is accessible to a solvent, contributed by hydrophobic amino acid residues.

[0038] In this invention, "surface charge distribution" refers to the spatial distribution of positive charge, negative charge, and neutral regions on the surface of a protein's three-dimensional structure, characterized by net surface charge, positive charge surface area, negative charge surface area, the proportion of positive charge surface area, the proportion of negative charge surface area, surface electrostatic potential, positive charge patch area, negative charge patch area, and / or the number of charge patches.

[0039] In this invention, the total length N of the polypeptide chain (i.e., the total number of amino acid residues) is dimensionless and has no unit.

[0040] In this invention, the spring constant k (pN / nm) includes the entropic elastic spring constant and the hydrophobic elastic spring constant, wherein... ;k B Boltzmann constant, in pN·nm·K -1 k B ≈1.3806×10 −23 J / K = 0.013806 pN·nm·K -1 It is a proportionality constant that relates the average thermal kinetic energy of microscopic particles to macroscopic absolute temperature; T: absolute temperature, unit is K; L c Outline length, in nm, is the maximum theoretical physical length (total geometric length of the backbone chain) of a polypeptide chain when fully stretched without breaking covalent bonds. This invention uses L... c =0.38N, where N is the total number of residues in the amino acid sequence; L p : Duration length, in nm, is the physical characteristic length that characterizes the bending stiffness (flexibility) of a polypeptide chain, i.e., the characteristic distance at which the correlation along the chain tangent decreases exponentially with distance.

[0041] In this invention, the root-mean-square radius of gyration (Rg), measured in nm, is the root-mean-square distance from the mass element of each residue to the center of mass of the chain in all conformations of the polypeptide chain, used to measure the compactness of the polymer spatial scale. In this invention, it is calculated directly from the input amino acid sequence using the AFRC (Analytical FRC) engine.

[0042] In this invention, the mean square end-to-end distance (Ree), measured in nm, is the root mean square distance of the straight line from the start point (N-terminus) to the end point (C-terminus) of the polymer chain in three-dimensional space, reflecting the degree of chain extension in the relaxed state. It is also calculated directly by the AFRC engine through the analysis of the input amino acid sequence.

[0043] In this invention, γ: surface tension constant, in pN / nm, is the free energy cost required to generate a unit area of ​​water-nonpolar solute interface. The interfacial tension between water and typical nonpolar organic liquids (such as alkanes) is typically 20-30 mJ / m. 2 In this invention, γ=25pN / nm is a constant.

[0044] In this invention, H is the average hydrophobicity score of the sequence, which is dimensionless and has a value between 0 and 1.

[0045] In this invention, SASAmax: the maximum solvent-accessible surface area in the stretched state, in nm. 2 The maximum solvent-accessible surface area (SASA) of a polypeptide chain in its fully unfolded and stretched conformation is theoretically the largest that can be exposed to water molecules.

[0046] This invention provides a sequence-based method for predicting the spring constant of an elastomer protein. This prediction method can be deployed on a server, personal computer, cloud computing platform, laboratory information management system, protein design platform, or local workstation and executed by one or more processors.

[0047] The spring constant includes the entropic elastic spring constant and the hydrophobic elastic spring constant;

[0048] The hydrophobic elastic spring constant k hyd Predicting rebound using a hydrophobic interaction-driven rebound model:

[0049] ,

[0050] Where γ: surface tension constant; H: average hydrophobicity score of the sequence; SASA max : Maximum solvent-accessible surface area in the stretched state; Rg: Mean square radius of gyration; N: Total number of residues in the sequence; Ree: Mean square end-to-end distance.

[0051] The entropy elastic spring constant k ent Predicted using the entropy spring effect model:

[0052] ,

[0053] Where, k B Boltzmann constant; T: absolute temperature; Rg: mean square radius of gyration; Ree: mean square end-to-end distance.

[0054] In some embodiments, the elastomeric proteins include natural elastomeric proteins, extrin, elastomeric polypeptides, fragments or variants of natural elastomeric proteins, fragments or variants of extrin, variants of elastomeric polypeptides, and fusion proteins containing repeating sequences of elastomeric proteins.

[0055] Furthermore, the average hydrophobic score of the sequence is the average value of the hydrophobicity parameters of each amino acid residue in the amino acid sequence of the protein to be analyzed.

[0056] Furthermore, the average hydrophobicity score of the sequence is characterized by the Kyte-Doolittle hydrophobicity index:

[0057] ,

[0058] Where H: average hydrophobicity score of the protein sequence (refer to Table 1), N: total number of amino acid residues (i.e., total length of the polypeptide chain), h o : The Kyte-Doolittle hydrophobic coefficient value corresponding to the oth amino acid of the protein to be analyzed (Kyte J, A simple method for displaying the hydropathic character of a protein. J Mol Biol. 1982 May 5;157(1):105-132).

[0059] Table 1. Hydrophobicity Score of Amino Acids (h) o )

[0060]

[0061] In some implementations, the entropy elastic spring constant k ent (pN / nm) is approximated based on the worm-like chain (WLC) model:

[0062] ,

[0063] Where, k B Boltzmann constant, in pN·nm·K -1 kB≈0.013806 pN·nm·K -1 T: Absolute temperature, in K; Rg: Mean square radius of gyration, in nm; Ree: Mean square end-to-end distance, in nm.

[0064] In some preferred embodiments, the mean square radius of gyration Rg and the mean square end distance Ree are calculated using the AFRC (Analytical FRC) engine through amino acid sequence analysis (Alston JJ, Ginell GM, Soranno A, Holehouse AS. The Analytical Flory Random Coil Is a Simple-to-Use Reference Model for Unfolded and Disordered Proteins. Journal of Physical Chemistry B, 2023, 127(21): 4746–4760).

[0065] In some implementations, the spring constant is predicted by the rebound model through hydrophobic interaction:

[0066] Hydrophobic elastic spring constant k hyd (pN / nm):

[0067]

[0068] Where γ is the surface tension constant, measured in pN / nm, which is the free energy cost required to generate a unit area of ​​water-nonpolar solute interface. The interfacial tension between water and typical nonpolar organic liquids (such as alkanes) is typically 20-30 mJ / m. 2 H: Average hydrophobicity score of the sequence (see Table 1), unitless, dimensionless, and ranging from 0 to 1. SASA max : Maximum solvent-accessible surface area in the stretched state, in nm 2 Summing and accumulating the entire sequence. Rg: mean square radius of gyration, in nm; N: total number of amino acid residues (i.e., total length of the polypeptide chain); Ree: mean square end-to-end distance, in nm.

[0069] In some preferred embodiments, the surface tension constant γ is obtained through user input, preset default values, calculations based on protein structure, calculations based on molecular simulation, or machine learning.

[0070] Furthermore, the default value for the surface tension constant γ is 25 pN / nm.

[0071] Example 1

[0072] The spring constants of elastins ELP120, ELP1-180, ELP4-120, ELP2-64, and Tropoelastin-698, and mucin-mini1, mucin-mini2, and mucin-mini1plus2 were calculated and predicted. Mucin-mini1, mucin-mini2, and mucin-mini1plus2 are mucins and can be used as controls for elastin (disordered but hydrophilic, while elastin is disordered and hydrophobic). The spring constant k (pN / nm) includes the entropic elastic spring constant k. ent and the hydrophobic elastic spring constant k hyd ,according to The predicted spring constant is converted into the duration L. p Plot the graph, where k ent Convert to entropy elasticity prediction duration L p，ent k hyd Converted to hydrophobic elastic prediction of duration L p，hyd The results are shown Figure 1 , Figure 2 .

[0073] according to Figure 1 It can be seen that the experimental value of duration L p，exp The fact that the duration of the predicted entropic elasticity lies between the predicted duration of the hydrophobic elasticity indicates that the true elastic spring constant of elastin (i.e., the experimental values ​​of ELP120, ELP1-180, ELP4-120, ELP2-64, and Tropoelastin-698) lies between the predicted duration of the entropic elasticity and the predicted duration of the hydrophobic elasticity. ent and the hydrophobic elastic spring constant k hyd Between the two, and the predicted value k ent and predicted value k hyd The difference range is relatively narrow, which can provide a more accurate reference range for the elasticity prediction of elastin, and can significantly improve R&D efficiency; however, the present invention cannot accurately predict the elastic spring constant of non-elastin (mucin-mini1, mucin-mini2, mucin-mini1plus2), which shows that the method described in the present invention can specifically and accurately predict the spring constant of elastin.

[0074] according to Figure 2 It can be seen that the experimental values ​​L of elastin (ELP120, ELP1-180, ELP4-120, ELP2-64 and Tropoelastin-698) are... p，exp Compared with the predicted value L p,hyd The trend of change remains basically consistent. Figure 2A), the trend lines almost coincide; further bivariate correlation analysis shows that r = 0.9389 ( Figure 2 (B) The linear relationship is good. This indicates that the method described in this invention can meet the prediction requirements of the spring constants of different elastins, and can provide reliable predictive data support for the research and development of elastins.

[0075] The above embodiments are merely preferred embodiments of the present invention and are only used to explain the present invention, not to limit the present invention. Any changes, substitutions, modifications, etc., made by those skilled in the art without departing from the spirit and essence of the present invention should be within the protection scope of the present invention.

Claims

1. A method for predicting the spring constant of an elastomer protein based on sequence, characterized in that, The prediction method includes: The spring constant includes the entropic elastic spring constant and the hydrophobic elastic spring constant; The hydrophobic elastic spring constant k hyd Predicting rebound using a hydrophobic interaction-driven rebound model: ， Where γ is the surface tension constant; H is the average hydrophobicity score of the sequence; SASAmax is the maximum solvent-accessible surface area in the stretched state; Rg is the mean square radius of gyration; N is the total number of residues in the sequence; and Ree is the mean square end-to-end distance.

2. The prediction method according to claim 1, characterized in that, The elastin proteins include natural elastin, extrin, elastin-like peptides, natural elastin fragments or variants, extrin fragments or variants, elastin-like peptide variants, and fusion proteins containing elastin-like repeat sequences.

3. The prediction method according to claim 1, characterized in that, The entropy elastic spring constant k ent Predicted using the entropy spring effect model: ， Where, k B Boltzmann constant; T: absolute temperature; Rg: mean square radius of gyration; Ree: mean square end-to-end distance.

4. A sequence-based system for predicting the spring constant of an elastomer protein, characterized in that, The system includes: The calculation module is used to calculate the spring constant of the elastomer protein; The spring constant includes the entropic elastic spring constant and the hydrophobic elastic spring constant; The hydrophobic elastic spring constant k hyd Predicting rebound using a hydrophobic interaction-driven rebound model: ， Where γ is the surface tension constant; H is the average hydrophobicity score of the sequence; SASAmax is the maximum solvent-accessible surface area in the stretched state; Rg is the mean square radius of gyration; N is the total number of residues in the sequence; and Ree is the mean square end-to-end distance.

5. The prediction system according to claim 4, characterized in that, The entropy elastic spring constant k ent Predicted using the entropy spring effect model: ， Where, k B Boltzmann constant; T: absolute temperature; Rg: mean square radius of gyration; Ree: mean square end-to-end distance.

6. The prediction system according to claim 4, characterized in that, The elastin proteins include natural elastin, extrin, elastin-like peptides, natural elastin fragments or variants, extrin fragments or variants, elastin-like peptide variants, and fusion proteins containing elastin-like repeat sequences.

7. An apparatus, characterized in that, The device includes at least one storage medium and at least one processor, the at least one storage medium being used to store computer instructions, and the at least one processor being used to execute the computer instructions to implement the sequence-based method for predicting the spring constant of elastomeric proteins as described in any one of claims 1-3.

8. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions, which, when executed by a processor, implement the sequence-based method for predicting the spring constant of an elastomer protein as described in any one of claims 1-3.

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