Biomacromolecule binding efficiency evaluation method, device and system based on energy barrier topology theory

Abstract

The invention discloses a biomacromolecule binding efficiency evaluation method based on an energy barrier topology theory. By introducing dynamic weight factors alpha and beta to correct environmental dynamics interference, an evaluation operator of a forest remote index (LYI) is constructed. The operator quantifies the coupling effect of the physical adsorption phase energy level ([delta] Gadherence) and the chemical locked phase energy level ([delta] Glocking). The 3D potential energy landscape generated by using the operator can identify the 'Lin funnel' with irreversible locking characteristics, and the judgment standard is that the comprehensive score LYI is greater than or equal to 100 and the edge gradient Xi is greater than or equal to 15.0. The technical problem that traditional affinity evaluation neglects fluid dynamics interference and long-range capture efficiency is solved, and the industrialization success rate of antigen screening is remarkably increased.

Description

[Technical Field]

[0001] This invention belongs to the interdisciplinary field of biocomputation, artificial intelligence and molecular dynamics, and specifically relates to an evaluation operator for evaluating the coupling effect of multi-phase physical energy levels (long-range trapping energy and short-range locking energy) under non-ideal physiological conditions using computer computation—the Lin Yuanzhe Index (LYI), and a barrier topology analysis method based on this index. [Background Technology]

[0002] Current drug and vaccine screening primarily relies on Gibbs free energy (ΔG) or dissociation constant (Kd). However, in practical applications, the following technical blind spots exist:

[0003] 3.1. Ignoring environmental dynamics: Physical quantities measured in the laboratory cannot reflect the physical shielding effect of high ionic strength (such as seawater) or complex mucus layers (such as the intestine) on molecules, nor can they reflect the disruption of binding stability by dynamic fluid shear forces.

[0004] 3.2. Phase loss: Traditional algorithms focus on the steady state after the molecule enters the receptor pocket, ignoring the efficiency of the "long-range capture" before the molecule reaches the receptor, resulting in a large number of high-affinity peptides failing to land effectively in dynamic fluid environments. [Summary of the Invention]

[0005] This invention achieves a quantitative score of the efficiency of the entire molecular "from capture to locking" pathway through the "two-stage energy feedback model" constructed by inventor Mr. Lin Yuanzhe.

[0006] 4.1 Core Mathematical Model

[0007] The Lin Yuan-Tseh Index disclosed in this invention is calculated using the following core mathematical model:

[0008] LYI=[(α×|ΔG_adhesion|+β×|ΔG_locking|) / k(T)]×φ_env

[0009] in:

[0010] (1) ΔG_adhesion (physical adsorption phase energy level): describes the gravitational energy level generated by the ligand under the guidance of the electrostatic potential field at a long-range scale (5-15nm).

[0011] (2) ΔG_locking (chemically locked phase energy level): describes the short-range (2-5 Å) atomic-level locking energy generated by hydrogen bonds and salt bridges after the ligand enters the acceptor pocket.

[0012] (3) k(T) (Lin's temperature adaptive constant): Normalization operator characterizing background thermal noise.

[0013] (4) α, β (environmental dynamics weighting factors): compensation coefficients for dynamic fluid environments.

[0014] (5)φ_env (environmental gain factor): physical calibration coefficient for a specific dielectric environment.

[0015] 4.2 Underlying Physical Logic and Derivation Process

[0016] 4.2.1 Statistical Mechanical Derivation of Ringel's Temperature Adaptive Constant k(T)

[0017] In microscopic systems, the binding and desorption of molecules follow the Boltzmann distribution.

[0018] (1) Energy level transition probability: The probability P of a molecule escaping the acceptor pocket is proportional to exp(-ΔE / kB×T).

[0019] (2) Definition of reference thermal noise: The inventors define the single-degree-of-freedom thermal fluctuation energy at physiological room temperature (310.15K) as the reference unit. In the Ring coordinate system, in order to achieve dimensional normalization, the Boltzmann constant kB is mapped to the scalar 1.38.

[0020] (3) SNR conversion logic:

[0021] k(T)=1.38×(T_target / 310.15)

[0022] Physical meaning: k(T) essentially defines the "thermal noise horizon" at the current temperature. A higher LYI exponent means that the binding energy is better able to overcome the interference of random thermal motion. This invention converts the absolute value of energy into the signal-to-noise ratio (SNR).

[0023] 4.2.2 Derivation of Fluid Collision for Long-Range Capture Weight α

[0024] In a flowing medium, the approach of a polypeptide antigen to a receptor is influenced by the Pelet number (Pe), which is the competition between convection and diffusion.

[0025] (1) Effective collision cross section: As the Reynolds number (Re) increases, the laminar momentum increases, and the lateral capture probability Phi caused by diffusion decreases.

[0026] (2) Logarithmic Compensation Model: According to boundary layer theory, in order to maintain the same capture efficiency, the effective power component of electrostatic attraction needs to be enhanced. The derivation is as follows:

[0027] α = 1 + ln(1 + Re / Rec)

[0028] Where Rec is the critical Reynolds number. This factor compensates for the capture energy loss caused by insufficient "residence time" of molecules near the receptor due to excessively high flow rates.

[0029] 4.2.3 Derivation of the kinetic bond energy of the chemical locking weight β (based on the Bell model)

[0030] Once a molecule is locked in place, it is subjected to shear force γ, and its desorption rate constant koff increases exponentially with the external force.

[0031] (1) Application of Bell theory: External force F will reduce the binding energy barrier ΔG_double_dagger.

[0032] (2) Shear work compensation: In order to offset the work W done by the fluid shear force, a second-order compensation factor is derived:

[0033] β=sqrt(1+μ×γ^2)

[0034] Where μ is the viscoelastic coefficient. This factor ensures that only molecules with higher energy level "deep-locking" characteristics can remain stable under high-speed scouring conditions.

[0035] 4.2.4 Derivation of the electrostatic potential of the physical adsorption phase energy level ΔG_adhesion

[0036] This energy level describes the work done by molecules moving from infinity (or outside the effective capture radius) to the surface of the acceptor.

[0037] (1) Electrostatic work integral: In an electrical environment, its physical essence is the gradient integral of electrostatic potential energy.

[0038] (2) Debye shielding correction: In physiological media containing electrolytes, the Coulomb force is affected by the Debye-Huckel shielding effect. This invention establishes the energy basis of "long-range ballistics" by deriving the effective capture energy level in the 5-15nm scale through integration.

[0039] 4.2.5 Derivation of the potential energy trap for chemically locked phase energy level ΔG_locking

[0040] This energy level describes the potential depth of a molecule after it enters the equilibrium position of the acceptor pocket.

[0041] (1) Superposition of multiple force fields: is the sum of the energy of multiple non-covalent interactions (salt bridge, hydrogen bond, van der Waals force).

[0042] (2) Potential energy trap depth: Based on the Lennard-Jones potential model, this invention defines it as the minimum potential energy trap at atomic level contact (2-5 Å).

[0043] Physical meaning: The "Ling funnel" effect can only be formed when the energy level is much higher than the thermal noise reference set by k(T).

[0044] 4.2.6 Derivation of Physical Compensation for Environmental Gain Factor φ_env

[0045] The environmental gain factor φ_env is a systematic correction for the binding energy coupling efficiency caused by non-ideal physiological environments. Its derivation is based on the following physical compensation logic:

[0046] (1) Dielectric polarization compensation: The relative permittivity of different media directly affects the Coulomb potential. φ_env contains the permittivity ratio, which is used to correct the electric field attenuation from standard aqueous solution to complex body fluids (such as blood plasma).

[0047] (2) Debye length compensation: In high ion intensity environments (such as seawater), the reduction in Debye length leads to a decrease in the effective capture radius. φ_env restores the physical adsorption energy efficiency affected by shielding through an inverse proportional compensation operator.

[0048] (3) Viscoelastic dissipation compensation: In non-Newtonian fluids (such as viscous layers), the conformational search of molecules is hindered. Based on the Stokes-Einstein diffusion correction, φ_env introduces a weighted average of the effective viscosity factor to compensate for the extra energy required to overcome environmental resistance.

[0049] 4.3 Judgment Criteria: Lin's Funnel Theory

[0050] This invention discloses a physical morphological standard for determining binding effectiveness: when LYI ≥ 100 and an edge gradient is formed in the 3D potential energy landscape map. At this point, the receptor is determined to have entered the "Lincoln funnel" state. In this state, the energy required for desorption far exceeds the random thermal fluctuations under physiological conditions, achieving atomic-level irreversible locking. [Attached Image Description]

[0051] Figure 1 A flowchart of the LYI algorithm based on energy barrier topology theory is provided for embodiments of the present invention.

[0052] Figure 2 A 3D energy landscape comparison image of Candidate A and Candidate B provided in an embodiment of the present invention;

[0053] Figure 3 This is a diagram of a cloud-based distributed computing architecture that supports large-scale LYI filtering, provided in an embodiment of the present invention.

[0054] Figure 4 The parameter table of the all-species environmental gain matrix (φ_env) provided for embodiments of the present invention.

Detailed Implementation Methods

[0055] In this embodiment, a polypeptide fragment was selected as a ligand to simulate its entry into the receptor pocket in the human bloodstream environment (Re = 1200, cleavage rate γ = 2500 s^-1).

[0056] 6.1. Calculation of the physisorption phase: The electrostatic adsorption energy ΔG_adhesion is -45.5 kcal / mol. Considering hemodynamics, the calculated value is α = 1.05, and the corrected contribution is 47.775 kcal / mol.

[0057] 6.2. Calculation of chemically locked phase: The structural locking energy ΔG_locking is -72.4 kcal / mol. Based on the shear force compensation model, β = 1.08 is calculated, and the corrected contribution is 78.192 kcal / mol.

[0058] 6.3. Comprehensive Evaluation: Substituting the values ​​into the formula of this invention, the LYI index is calculated to be 95.84. At this point, the 3D landscape shows an edge gradient of only 12.8, and a stable "Lincoln funnel" has not yet formed.

[0059] 6.4 Sequence Evolution Experiment: A strong salt bridging effect was introduced by mutating the P4 site to aspartic acid (D). The calculation results for Candidate B in the experimental group are as follows: ΔG_adhesion increased to -52.5 kcal / mol, and ΔG_locking increased to -82.4 kcal / mol. The final calculated LYI = 110.52, with a marginal gradient of... Depend on Figure 2 It is evident that Candidate B exhibits a dramatic downward collapse at the identification center, forming a "Lin's funnel," and is thus determined to be a highly efficient locking sequence with industrialization value.

[0060] 7. Embodiments of the present invention also provide a cloud system, such as... Figure 3 As shown, real-time processing is achieved through distributed nodes. Figure 4 The environmental correction matrix shown supports high-throughput screening of trillions of sequences.

[0061] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention.

Claims

1. A method for evaluating the binding efficiency of biological macromolecules, characterized in that: Its evaluation logic was set by the inventor and is calculated by computer using the Lin Yuanzhe Index (LYI) based on multi-phase energy coupling. The formula is as follows: LYI = [(α × |ΔG_adhesion| + β × |ΔG_locking|) / k(T)] × φ_env Where ΔG_adhesion is the physical adsorption phase energy level, ΔG_locking is the chemically locked phase energy level, k(T) is the thermal noise adaptive constant normalized based on the physiological reference temperature, and φ_env is the environmental gain factor.

2. The method according to claim 1, characterized in that: The baseline value of k(T) is set to 1.38, and it is dynamically normalized according to the target species temperature T_target. Its calculation logic follows the statistical thermodynamic signal-to-noise ratio (SNR) conversion model.

3. The method according to claim 1, characterized in that: The weighting factor α is logarithmically corrected based on the Reynolds number (Re) and Peckley number of the environmental fluid to compensate for momentum disturbances in long-range capture. The weighting factor β is corrected by second-order energy compensation based on the environmental shear rate and the Bell bond lifetime model, in order to offset the work done by the fluid shear force.

4. The method according to claim 1, characterized in that: The φ_env contains a set of preset physiological environment correction matrices for different biological phyla (such as marine fish and mammalian mucus layers), which are stored in an encrypted database on a cloud server.

5. A method for screening highly efficient vaccine antigens based on the Lin Yuanzhe Index, characterized in that: The candidate sequences are input into the evaluation model, and the criteria for determining whether an edge gradient ∇Ξ ≥ 15.0 is formed in the 3D potential energy landscape as a "Lin's funnel" shape, and the comprehensive score LYI ≥ 100 are used as the criteria for determining the target of industrial production.

6. A cloud computing system implementing the method of claim 1, characterized in that: It includes a dynamic parameter scheduling layer, distributed parallel computing nodes, and a secure container; the system executes the algorithm logic through a non-transitory computer-readable storage medium and uses a high-performance tensor computing cluster to render the Lin funnel topology in real time.

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