A method for identifying and evaluating protein interface adhesion sites based on molecular dynamics trajectories

Abstract

The application provides a protein interface adhesion site recognition and evaluation method based on molecular dynamics trajectory, and belongs to the technical fields of computational biology, molecular dynamics trajectory analysis and biomaterial interface analysis. The application is based on molecular dynamics trajectory data of target protein and target interface, distance contact events are recognized according to a preset distance threshold after a protein side analysis atom set and an interface side analysis atom set are determined, and directional interaction events are recognized according to a preset angle threshold on the basis of the distance contact events; the distance contact events and the directional interaction events are mapped to protein residues, the protein residues are accumulated scored, candidate adhesion residues, candidate adhesion sites and / or protein-level adhesion descriptors are output, and the output results can be directly used for site mutation, peptide segment functionalization, single molecule tracking, force spectrum experiment and cell adhesion experiment design.

Description

Technical Field

[0001] This invention relates to the fields of computational biology, molecular dynamics trajectory analysis, and biomaterial interface analysis, specifically to a method, system, computer device, and storage medium for identifying protein interface adhesion residues, adhesion sites, and protein-level adhesion descriptors from the molecular dynamic trajectories of proteins and interfaces. Background Technology

[0002] Early contact between proteins and materials or biological interfaces can influence subsequent protein adsorption layer formation, cell adhesion, immune recognition, inflammatory responses, bacterial adhesion, and long-term integration of implant materials. Common applications include titanium or titanium oxide implant interfaces, dental hydroxyapatite interfaces, neural electrode material interfaces, and the formation of plasma protein crowns.

[0003] In existing technologies, interfacial protein behavior is typically evaluated using methods such as mass spectrometry, fluorescence imaging, single-molecule trajectory tracing, atomic force microscopy, cell adhesion experiments, or transcriptional level detection. These methods can usually reflect protein composition, motility, adhesion strength, or downstream cell phenotype, but they cannot directly identify which residues in the protein are responsible for stabilizing interfacial adhesion.

[0004] Molecular dynamics simulations provide atomic-level trajectory information and are an important tool for analyzing protein-interface interactions. Existing simulation analyses use total interaction energy, minimum distance, contact number, hydrogen bond number, or conformational observations to evaluate protein-interface interactions. However, in complex biomaterial interfaces, protein orientation, interfacial chemistry, and local contact states are highly heterogeneous, making it difficult to reliably determine the residue sites truly involved in adhesion using a single global energy or single-frame contact. Specifically:

[0005] (1) It is difficult to locate specific adhesion residues when relying solely on global interaction energy; the overall energy may vary greatly under different initial orientations, but the energy change itself cannot explain which residues contribute to interfacial adhesion.

[0006] (2) When only distance contact is used, it is easy to misjudge instantaneous spatial proximity as stable adhesion, lacking a comprehensive judgment of directional geometric relationship and time duration;

[0007] (3) When only counting the number of hydrogen bonds, it is usually difficult to summarize into comparable residue-level adhesion sites, and it is also difficult to form a unified descriptor among multiple proteins, multiple interfaces and multiple environmental conditions.

[0008] It is evident that existing experimental methods can observe changes in protein crown composition and phenotypic characteristics, but it is difficult to directly correlate the temporal trends of proteomics with atomic-scale residue contributions; moreover, existing simulation results are not readily convertible into candidate sites for mutation design, peptide design, or material interface optimization. Summary of the Invention

[0009] To address the shortcomings of existing technologies, this invention provides a method, system, computer device, and storage medium for identifying protein interface adhesion residues, adhesion sites, and protein-level adhesion descriptors from the molecular dynamics trajectories of proteins and interfaces. This invention extracts information possessing distance, directionality, and temporal persistence from the molecular dynamics trajectories of target proteins and target interfaces, and transforms this information into interpretable residue-level adhesion scores. This yields candidate adhesion residues, candidate adhesion sites, and protein-level adhesion descriptors, thereby enabling the evaluation of protein interface adhesion under different orientations, proteins, interfaces, and environmental conditions.

[0010] To achieve the above objectives, the specific technical solution of the present invention is as follows:

[0011] In a first aspect, the present invention provides a method for identifying and evaluating protein interface adhesion sites based on molecular dynamics trajectories, comprising the following steps:

[0012] Based on the molecular dynamics trajectory data of the target protein and the target interface, the sets of atoms for protein-side analysis and the sets of atoms for interface-side analysis are determined.

[0013] In each trajectory frame, the distance between protein-side analysis atoms and interface-side analysis atoms is calculated, and distance contact events are identified based on a preset distance threshold.

[0014] Based on distance contact events, the donor, hydrogen atom and acceptor are identified, the donor-hydrogen-acceptor angle is calculated, and directional interaction events are identified according to a preset angle threshold.

[0015] Based on distance contact events and directional interaction events, protein residues are cumulatively scored to obtain residue-level adhesion scores;

[0016] Output candidate adhesion residues, candidate adhesion sites, and / or protein-level adhesion descriptors based on residue-level adhesion scores.

[0017] In the method of this invention, the target protein refers to a protein, protein fragment, mutant, or candidate peptide whose interfacial adhesion behavior needs to be analyzed; the target interface refers to a biological interface or non-biological material interface that comes into contact with the target protein, such as titanium dioxide, hydroxyapatite, or molybdenum-based neural interface materials; and the molecular dynamics trajectory data refers to the data on the change of atomic coordinates over time obtained by molecular dynamics simulation.

[0018] In the method of this invention, the molecular dynamics trajectory data includes: topology file, trajectory file, coordinate file, residue number, residue name, atom name, and atom coordinate information; the source of the molecular dynamics trajectory data includes molecular dynamics software, including but not limited to: GROMACS, AMBER, NAMD, CHARMM, LAMMPS, as long as it can provide the correspondence between atomic coordinates and topology.

[0019] In the method of this invention, the protein-side analysis atom set represents protein atoms that may participate in interfacial donor-acceptor interactions. This protein-side analysis atom set includes oxygen, nitrogen, sulfur, or other polar atoms in the protein that participate in donor-acceptor interactions. The interfacial-side analysis atom set represents atoms on the material surface or biological interface that can participate in short-range contact or directional interactions. This interfacial-side analysis atom set is set according to the actual target interface type. For example, the interfacial-side analysis atom set includes at least one of the following: interfacial atom type, atom name, residue or molecule name, spatial region, and surface layer thickness. In specific operation, after loading molecular dynamics trajectory data (e.g., trajectory files and topology files), the protein and material surface are defined according to atom selection rules, and solvent molecules are excluded from the analysis. To focus on chemically significant interactions, the statistics are mainly limited to polar atom sets: the protein side defaults to including polar atoms such as N / O / S; the material side selects the corresponding element set (e.g., oxides / phosphates / sulfides) based on the substrate composition, while allowing equivalent substitutions and customization as needed by the system.

[0020] In the method of this invention, the trajectory frame refers to the trajectory frame extracted for analysis based on a set start frame, end frame, sampling interval, or equilibrium interval.

[0021] In the method of this invention, the distance contact event refers to an event in which the distance between a protein-side atom and an interface-side atom is less than or equal to a preset threshold in a certain trajectory frame. That is, the determination condition of the distance contact event is: the distance between the protein-side analytical atom and the interface-side analytical atom is less than or equal to the preset distance threshold. The distance threshold can be set according to the interface chemical type, including: a fixed threshold, a hierarchical threshold, or an adaptive threshold. For example, the distance threshold is one or more of 0.35-0.50 nm. In specific operation, firstly, based on the nearest neighbor distance of the interface atom pairs, multi-level distance intervals are defined to characterize the continuous spectrum from strong contact to long-range interaction. In each frame, protein-interface atom pairs that satisfy the nearest neighbor search radius constraint are classified and accumulated to obtain (i) the interface contact intensity trajectory that changes over time, and (ii) the contact frequency / contribution spectrum summarized by residues, which are used to locate stable or transient adhesion regions.

[0022] Furthermore, the distance threshold employs a combination of a strict threshold and a lenient threshold; wherein the strict threshold is used to identify short-range contacts that are closer to the classical hydrogen bond scale, and the lenient threshold is used to identify weak interactions or wider interface neighborhoods.

[0023] In the method of this invention, the determination criteria for the directional interaction event include: based on the distance contact event, the donor-hydrogen-acceptor angle formed by the donor atom, the hydrogen atom connected to the donor atom, and the acceptor atom is greater than or equal to a preset angle threshold; the angle threshold can be set according to the hydrogen bond / weak hydrogen bond determination requirements. For example, the angle threshold is 120-150 degrees. o One or more of them.

[0024] Furthermore, the angle threshold is 120°. o Or 150 o This is used to distinguish between looser and stricter directional interactions.

[0025] In the method of this invention, the donor atoms come from the target protein and / or the target interface. When the donor atoms come only from the target protein, it is called the protein donor mode; when the donor atoms come only from the target interface, it is called the interface donor mode; when the donor atoms come from both the target protein and the target interface, it is called the bidirectional donor mode. The bidirectional donor mode calculates the interaction events of the protein as a donor and the interface as a donor respectively, and combines, weights, or outputs the results separately.

[0026] Furthermore, the scoring operation includes: accumulating the number of protein residues that satisfy distance contact events and directional interaction events, i.e.:

[0027] Residue level score = .

[0028] The residue-level adhesion score described in this invention refers to a score obtained by quantifying the degree to which a residue participates in interfacial interactions in a trajectory after attributing distance contact events and directional interaction events to their corresponding residues. The approach to cumulatively scoring protein residues in this invention is as follows: For a given residue *r*, the number of distance contact events and directional interaction events involving that residue are counted across all sampled trajectory frames, and these are accumulated according to event type and threshold level to obtain a distance score, an angle score, and a total score.

[0029] In this invention, the candidate adhesion sites are obtained by screening high-scoring residues based on residue-level adhesion scores and merging them according to sequence proximity and / or three-dimensional spatial proximity. Compared to outputting only a single residue, the sites output by this invention after merging based on sequence / three-dimensional spatial proximity are more suitable for subsequent mutation design, peptide design, and functional verification. The output includes residue number, residue name, sequence fragment, score, score percentage, and three-dimensional structural position. High-scoring candidate sites that repeatedly appear in multiple initial orientations, multiple thresholds, or multiple trajectories are considered stable adhesion sites.

[0030] In the method of this invention, the adhesion descriptor is a protein-level index obtained by summarizing the residue score distribution, which is used for multi-protein or multi-condition comparison.

[0031] In the method of the present invention, the output result format includes, but is not limited to, at least one of the following: table, heatmap, three-dimensional structural marker, residue ranking, protein descriptor matrix or interactive result interface.

[0032] Furthermore, to assess the sensitivity of the conclusions to the selection of geometric thresholds, this invention performs gridded scanning of distance and angle thresholds within a reasonable range and simultaneously outputs the corresponding time series and residue-level statistical tables to verify the consistency of "hotspot site ranking / main conclusions" under different thresholds, thereby improving the robustness of the result interpretation.

[0033] The method of the present invention further includes: calculating residue-level adhesion scores for multiple initial orientation trajectories of the same target protein and the same target interface, and determining site stability based on the repetition of candidate residues or candidate sites in multiple initial orientations.

[0034] The method of the present invention further includes: generating protein-level adhesion descriptors for multiple target proteins respectively, and sorting, classifying or clustering the relative adhesion tendencies of multiple target proteins on the same target interface based on the descriptors.

[0035] The method of the present invention further includes: performing correlation analysis between protein-level adhesion descriptors and time-resolved proteomics data or protein crown data to evaluate the retention trend, enrichment trend or category-level correspondence of target proteins at the target interface.

[0036] In a second aspect, the present invention provides a protein interface adhesion site identification system based on molecular dynamics trajectories, including a data acquisition module, an atom set determination module, a distance contact event identification module, a directional interaction event identification module, a residue scoring module, a site output module, a multi-trajectory consistency evaluation module, and / or a multi-protein comparison module.

[0037] Furthermore, the data acquisition module is used to acquire molecular dynamics trajectory data of the target protein and the target interface.

[0038] Furthermore, the atom set determination module is used to determine the protein-side polar atom set and the interface-side analytical atom set. The interface-side analytical atom set is determined based on the interface material type or user-defined atom names, and can adapt to different interface chemistry such as titanium dioxide, hydroxyapatite, and molybdenum-based interfaces.

[0039] Furthermore, the distance contact event recognition module is used to calculate the distance between protein-side analysis atoms and interface-side analysis atoms frame by frame, and to recognize distance contact events according to a distance threshold.

[0040] Furthermore, the directional interaction event identification module is used to determine the donor, hydrogen atom, and acceptor based on distance contact events, calculate the donor-hydrogen-acceptor angle, and filter out directional interaction events according to an angle threshold. This invention incorporates geometric directionality into the adhesion determination, enhancing the interpretability of the mechanism.

[0041] Furthermore, the residue scoring module is used to count the number of times an event occurs, the length of consecutive occurrences, and the repetition under multiple thresholds, and assign it to a residue. This invention distinguishes between continuous adhesion and instantaneous proximity through a time-cumulative scoring method, thereby reducing misjudgments caused by instantaneous proximity in a single frame.

[0042] Furthermore, the site output module is used to sort high-scoring residues and merge them into candidate adhesion sites according to sequence or spatial proximity, and output candidate regions that can be used for mutation, peptide design and experimental verification.

[0043] Furthermore, the multi-trajectory consistency evaluation module or multi-protein comparison module is used to output and compare adhesion descriptors for multiple orientations, multiple proteins, or multiple environmental conditions, so as to achieve relative evaluation across proteins, interfaces, and environmental conditions.

[0044] Thirdly, the present invention provides a computer device for identifying protein interface adhesion sites based on molecular dynamics trajectories, including a processor, a memory, and a computer program, wherein the computer program, when executed by the processor, implements the method for identifying and evaluating protein interface adhesion sites based on molecular dynamics trajectories.

[0045] Fourthly, the present invention provides a computer-readable storage medium or computer program product, wherein the computer instructions stored therein, when executed by a processor, implement the method for identifying and evaluating protein interface adhesion sites based on molecular dynamics trajectories.

[0046] Compared with the prior art, the advantages of the present invention are:

[0047] (1) Improved residue-level localization capability: By mapping events to residues and performing cumulative scoring, the present invention provides a method that can locate specific adhesive residues and adhesion sites, compared to the prior art which only outputs global energy or total number of contacts.

[0048] (2) Distinguishing between stable adhesion and instantaneous contact: By accumulating the number of repetitions and duration, this invention can reduce misjudgment caused by instantaneous proximity in a single frame.

[0049] (3) Directional geometric constraints improve interpretability: Based on distance contact, this invention adopts donor-hydrogen-acceptor angle determination, making the output result closer to the physicochemical meaning of directional interactions such as hydrogen bonds or weak hydrogen bonds.

[0050] (4) Applicable to different interface chemistry: In the method of the present invention, the interface side analysis atom set can be customized or selected according to the chemical composition of the actual target interface, and can be adapted to different interfaces such as titanium dioxide, hydroxyapatite, and molybdenum-based materials.

[0051] (5) Support for multi-orientation robustness evaluation: The method of the present invention analyzes multiple initial orientations separately, which can screen stable adhesion sites that repeat across orientations and reduce the bias caused by a single initial conformation.

[0052] (6) Support for multi-protein comparison: The method of the present invention can establish a unified and comparable interface adhesion tendency index among multiple proteins through the adhesion descriptor at the protein level.

[0053] (7) Facilitates experimental translation: The candidate sites output by the method of this invention can be directly used for site mutation, peptide functionalization, single molecule tracking, force spectrum experiments and cell adhesion experiment design. Attached Figure Description

[0054] Figure 1 The flowchart of the method of the present invention illustrates the main steps from molecular dynamics trajectory data to candidate adhesion sites and adhesion descriptors.

[0055] Figure 2 This is a schematic diagram of the implementation environment of the method of the present invention. The diagram shows the relationship between the terminal device, server or workstation, input file, analysis parameters and analysis results.

[0056] Figure 3 This diagram illustrates the identification of distance contact events and directional interaction events, showing the criteria for determining the distance threshold d and the angle threshold θ.

[0057] Figure 4 This diagram illustrates the determination of residue-level scores and candidate adhesion sites, showing trajectory event statistics, residue score ranking, and candidate site output.

[0058] Figure 5 This is a schematic diagram of the consistency evaluation of multiple initial orientations. The diagram shows that multiple initial orientations output high-scoring residues / sites and are compared for consistency.

[0059] Figure 6 This is a schematic diagram for multi-protein comparison and time-resolved proteomics association analysis.

[0060] Figure 7 The diagram shows the structural block diagram of the system of the present invention, which includes a data acquisition module, an atom set determination module, an event recognition module, a scoring module, and a result output module.

[0061] Figure 8 This is a structural block diagram of the computer device of the present invention, showing a processor, memory, communication interface, and computer program / instructions for implementing the method of the present invention.

[0062] Figure 9 The images show confocal microscopy results of the adhesion function of fibronectin, its mutants, and mutant peptides to fibroblasts. The first row shows confocal microscopy results of fibroblasts incubated with fibronectin and fibronectin knockout mutant sites SKST and TVR, with a scale bar of 63.2 μm. The second row shows confocal microscopy results of fibroblasts incubated with RGD peptides and SKST-TVR peptides, with a scale bar of 100 μm.

[0063] Figure 10 The statistical results of cell fluorescence intensity and cell density after incubation of RGD peptide and SKST-TVR peptide are given, N=5. Detailed Implementation

[0064] To enable those skilled in the art to clearly and completely understand the technical solution of the present invention, the present invention will be further described in detail below with reference to embodiments. Obviously, the embodiments described herein are only for explaining the present invention and are not intended to limit the scope of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0065] This invention provides a method for identifying and evaluating protein interface adhesion sites based on molecular dynamics trajectories, the flowchart of which is shown below. Figure 1 As shown in the diagram, the implementation environment is as follows: Figure 2 As shown. The method includes the following steps:

[0066] S1. Obtain molecular dynamics trajectory data of the target protein and the target interface.

[0067] The molecular dynamics trajectory data includes: topology file, trajectory file, coordinate file, residue number, residue name, atom name, and atom coordinate information. The source of the molecular dynamics trajectory data includes molecular dynamics software, including but not limited to: GROMACS, AMBER, NAMD, CHARMM, and LAMMPS, as long as it can provide the correspondence between atomic coordinates and topology. The topology file path (e.g., .pdb or .gro) defines the structure of the molecular system, and the trajectory file path (e.g., .xtc or .trr) contains the time-series data from the molecular dynamics simulation.

[0068] S2. Based on the molecular dynamics trajectory data of the target protein and the target interface, determine the set of atoms for protein-side analysis and the set of atoms for interface-side analysis.

[0069] The protein-side analysis atom set is used to represent protein atoms that may participate in interfacial donor-acceptor interactions. The protein-side analysis atom set includes oxygen (O), nitrogen (N), sulfur (S), or other polar atoms in proteins that participate in donor-acceptor interactions. The interface-side analysis atom set is used to represent atoms on the material surface or biological interface that can participate in short-range contact or directional interactions. The interface-side analysis atom set is set according to the actual target interface type. For example, the analysis atom set of the titanium dioxide interface includes O and Ti.

[0070] S3. In each trajectory frame, calculate the distance between protein-side analysis atoms and interface-side analysis atoms, and identify distance contact events based on a preset distance threshold.

[0071] The trajectory frame refers to the trajectory frame extracted for analysis based on the set start frame, end frame, sampling interval, or equilibrium interval.

[0072] like Figure 3 As shown, the criteria for determining the distance contact event are: the distance between the protein-side analytical atom and the interface-side analytical atom is less than or equal to a preset distance threshold; the distance threshold can be set according to the interface chemistry type, including: a fixed threshold, a hierarchical threshold, or an adaptive threshold. For example, the distance threshold is one or more of 0.35-0.50 nm, or the distance threshold can also be a combination of a strict threshold and a lenient threshold; wherein, the strict threshold is used to identify short-range contacts that are closer to the classical hydrogen bond scale, and the lenient threshold is used to identify weak interactions or wider interface neighborhoods.

[0073] S4. Based on the distance contact event, determine the donor, hydrogen atom and acceptor, calculate the donor-hydrogen-acceptor angle, and identify directional interaction events according to the preset angle threshold.

[0074] like Figure 3As shown, the criteria for determining the directional interaction event include: the donor-hydrogen-acceptor angle formed by the donor atom, the hydrogen atom bonded to the donor atom, and the acceptor atom is greater than or equal to a preset angle threshold; the angle threshold can be set according to the hydrogen bond / weak hydrogen bond determination requirements, for example, the angle threshold is 120-150 degrees. o One or more of the following, for example, the angle threshold is 120. o Or 150 o This is used to distinguish between looser and stricter directional interactions.

[0075] The donor atoms originate from the target protein and / or the target interface. When the donor atoms originate only from the target protein, it is called the protein donor mode; when the donor atoms originate only from the target interface, it is called the interface donor mode; when the donor atoms originate from both the target protein and the target interface, it is called the bidirectional donor mode. The bidirectional donor mode calculates the interaction events of the protein as a donor and the interface as a donor, respectively, and combines, weights, or outputs the results separately.

[0076] S5. Map distance contact events and directional interaction events to protein residues, accumulate scores for protein residues, and obtain residue-level adhesion scores.

[0077] Specifically, the scoring and statistical methods are as follows:

[0078] 1. Distance-based interaction (residue_distance_only_profile):

[0079] Calculate the minimum distance between polar atoms of a protein and polar atoms on its surface;

[0080] Classified by distance range (e.g., strong_dist: 2.2-2.8 Å, weak_dist: 3.5-4.0 Å).

[0081] The number of interaction frames for each residue is recorded in residue_distance_only_profile[(resid,resname)][int_type];

[0082] Counting rule: When a residue has multiple polar atoms (such as multiple N or O atoms) that satisfy the distance condition in the same frame, each polar atom that satisfies the condition will be counted independently once, which may cause the interaction count of the residue in the frame to exceed 1.

[0083] 2. Angle-based hydrogen bonding (residue_interaction_profile and residue_interaction_profile_reverse):

[0084] (1) Positive hydrogen bond (protein donor):

[0085] Examine the distance and angle between protein donor atoms (N, O, S) and surface acceptor atoms;

[0086] Hydrogen bonds that meet the conditions (distance and angle) are recorded in residue_interaction_profile[(resid,resname)][int_type];

[0087] Counting rule: When a residue has multiple hydrogen atoms (such as H1, H2) that satisfy the hydrogen bond condition (DH...A) in the same frame, each hydrogen atom that satisfies the condition will be counted independently once, which may cause the hydrogen bond count of that residue in that frame to exceed 1.

[0088] (2) Reverse hydrogen bonding (surface donor):

[0089] Examine the distance and angle between the surface donor atoms and the protein acceptor atoms;

[0090] The (resid, resname) of the protein atom is used as the key and recorded in residue_interaction_profile_reverse;

[0091] The same rules for counting hydrogen atoms apply.

[0092] (3) Single hydrogen bond logic: Each donor atom and hydrogen atom pair selects the best acceptor (minimum distance, maximum angle).

[0093] S6. Output candidate adhesion residues, candidate adhesion sites, and / or protein-level adhesion descriptors based on protein residue-level adhesion scores.

[0094] A schematic diagram of residue-level scoring and candidate adhesion site determination is shown below. Figure 4 As shown. The candidate adhesion sites are selected based on residue-level adhesion scores, with high-scoring residues merged according to sequence proximity and / or three-dimensional spatial proximity to form candidate adhesion sites. Compared to outputting only a single residue, the sites output by merging based on sequence / three-dimensional spatial proximity are more suitable for subsequent mutation design, peptide design, and functional verification. The output includes residue number, residue name, sequence fragment, score, score percentage, and three-dimensional structural position.

[0095] The adhesion descriptor is a protein-level index obtained by summarizing the residue score distribution, used for multi-protein or multi-condition comparisons.

[0096] The output results may be in the following formats, including but not limited to: tables, heatmaps, three-dimensional structural markers, residue rankings, protein descriptor matrices, or interactive results interfaces.

[0097] like Figure 5 As shown, the method of the present invention further includes: calculating residue-level adhesion scores for multiple initial orientation trajectories of the same target protein and the same target interface, and determining site stability based on the repetition of candidate residues or candidate sites in multiple initial orientations.

[0098] The method of the present invention further includes: generating protein-level adhesion descriptors for multiple target proteins respectively, and sorting, classifying or clustering the relative adhesion tendencies of multiple proteins on the same target interface based on the descriptors.

[0099] like Figure 6 As shown, the method of the present invention further includes: performing correlation analysis between protein-level adhesion descriptors and time-resolved proteomics data or protein crown data to evaluate the retention trend, enrichment trend or category-level correspondence of proteins at the interface.

[0100] This invention also provides a protein interface adhesion site recognition system based on molecular dynamics trajectories, such as... Figure 7 As shown, the system includes: a data acquisition module 701, an atom set determination module 702, an event recognition module 703 (the event recognition module includes a distance contact event recognition module and a directional interaction event recognition module), a residue scoring module 704, and a site output module 705.

[0101] Optionally, the system further includes: a multi-trajectory consistency evaluation module and / or a multi-protein comparison module.

[0102] The data acquisition module acquires molecular dynamics trajectory data of the target protein and its interface. The atom set determination module determines the set of polar atoms on the protein side and the set of analytical atoms on the interface side. The distance contact event identification module calculates the distance between analytical atoms on the protein side and analytical atoms on the interface side frame by frame and identifies distance contact events according to a distance threshold. The directional interaction event identification module determines the donor, hydrogen atom, and acceptor based on the distance contact events, calculates the donor-hydrogen-acceptor angle, and filters out directional interaction events according to an angle threshold. The residue scoring module counts the number of occurrences, the length of consecutive occurrences, and the repetition under multiple thresholds, and maps them to residues. The site output module sorts high-scoring residues and merges them into candidate adhesion sites according to sequence or spatial proximity, outputting candidate regions that can be used for mutation, peptide design, and experimental verification. The multi-trajectory consistency evaluation module or multi-protein comparison module outputs and compares adhesion descriptors for multiple orientations, multiple proteins, or multiple environmental conditions, achieving relative evaluation across proteins, interfaces, and environmental conditions.

[0103] This invention also provides a computer device for identifying protein interface adhesion sites based on molecular dynamics trajectories, such as... Figure 8 As shown, the computer device includes a processor 801, a memory 802, a communication interface 803, and a computer program. When executed by the processor, the computer program can implement the method for identifying and evaluating protein interface adhesion sites based on molecular dynamics trajectories. Based on this, the present invention also provides a computer-readable storage medium or computer program product, the computer instructions stored therein, when executed by a processor, implement the method for identifying and evaluating protein interface adhesion sites based on molecular dynamics trajectories.

[0104] Example 1: Identification and evaluation of fibronectin (FN)-titanium dioxide interfacial adhesion sites

[0105] This embodiment uses the fibronectin-titanium dioxide interface as the target system. First, a molecular dynamics system of fibronectin and titanium dioxide surface is constructed, and trajectories with multiple different initial orientations are obtained. Different initial orientations are used to simulate the conformational and contact surface differences that may occur when proteins contact material interfaces.

[0106] In the analysis, polar atoms in fibronectin were used as the protein-side analytical atom set, and surface oxygen atoms or hydroxyl-related atoms at the titanium dioxide interface were used as the interface-side analytical atom set. Distance contact events were statistically analyzed using distance thresholds of 0.35 nm, 0.40 nm, 0.45 nm, and 0.50 nm, respectively, and further statistical analysis was conducted using a 120 nm distance threshold. o and 150 o Angle thresholds are used to identify directional interaction events.

[0107] Because the global interaction energies of the system vary significantly across multiple initial orientations, relying solely on global energy is insufficient to stably determine adhesion sites. Therefore, this invention normalizes contact events in the trajectory to specific residues, performing cumulative scoring to obtain residue-level scores. Exemplary results show that, near a reference distance threshold, interfacial adhesion contributions are concentrated in a few high-scoring residues, rather than being uniformly contributed by the entire protein surface.

[0108] Furthermore, recurring high-scoring residues are merged according to sequence fragments or three-dimensional spatial proximity to obtain candidate adhesion sites. For the fibronectin-titanium dioxide system, the method of this invention can output candidate sites consistent with known adhesion-related regions and can simultaneously propose new candidate adhesion fragments, such as SKST-related sites and TVR-related sites.

[0109] The adhesion state of fibronectin at the titanium dioxide interface can reshape the subsequent cell adhesion focal assembly process at the interface, thereby affecting the cell adhesion phenotype. To test the biological function relevance of the predicted adhesion sites, in this embodiment, wild-type and site-mutant fibronectin were pre-adsorbed onto the titanium dioxide surface, and then fibroblasts were cultured on it and the adhesion-related phenotypes were evaluated.

[0110] Figure 9 The confocal microscopy results show the adhesion function of fibronectin, its mutants, and mutant peptides to fibroblasts. The first row shows the confocal microscopy results of fibroblasts incubated with fibronectin and fibronectin knockout mutant sites SKST and TVR. The second row shows the confocal microscopy results of fibroblasts incubated with RGD peptide and SKST-TVR peptide. Figure 10 Statistical results of cell fluorescence intensity and cell density after incubation with RGD and SKST-TVR peptides are presented. The results show that knocking out adhesion sites (SKST and TVR) in fibronectin significantly reduced fibronectin-mediated focal adhesion indices, and fibroblast adhesion ability decreased synchronously, indicating that the predicted adhesion sites SKST and TVR substantially contribute to interfacial adhesion function. Further incubation of these adhesion site peptides individually with a titanium dioxide interface and culturing fibroblasts in a plasma environment produced an enhancement effect in functional phenotype similar to that of the classic adhesion-promoting peptide RGD. This trend was also replicated in endothelial cell systems, demonstrating that the predicted adhesion sites have consistent adhesion-promoting effects and potential transformative value across different cell types.

[0111] Example 2: Analysis of the hydroxyapatite interface and under different pH conditions

[0112] This embodiment illustrates that the method of the present invention can be used for oral cavity-related interfaces. This embodiment uses the hydroxyapatite interface and salivary / plasma-related proteins as examples, constructing protonated states under different pH conditions and performing molecular dynamics simulations.

[0113] During analysis, the protein-side analytical atom set is still dominated by polar atoms, while the interface-side analytical atom set includes phosphate oxygen, hydroxyl oxygen, or other surface atoms related to donor-acceptor interactions on the hydroxyapatite surface. Since the hydroxyapatite interface may also participate in directional interactions as either a donor or acceptor, a bidirectional donor mode is preferred.

[0114] Residue-level adhesion scores were calculated for trajectories under different pH conditions to compare the effects of environmental changes on adhesion site composition, score distribution, and site hierarchy. For example, the same protein may exhibit different sets of high-scoring residues under acidic conditions, near-neutral conditions, or other defined pH conditions, indicating that pH changes do not simply enhance or weaken adhesion as a whole, but may rearrange the interfacial adhesion structure.

[0115] Example 3: Evaluation of protein adhesion of molybdenum-based neural interface materials

[0116] This embodiment illustrates that the present invention can be used for the evaluation of protein adsorption in neural interface materials. In this embodiment, molybdenum-based material interfaces with different surface chemical states were selected as target interfaces, and fibronectin, immunoglobulins, or other cerebrospinal fluid-related proteins were selected as target proteins. Molecular dynamics simulations and trajectory analyses were performed on each.

[0117] For molybdenum-based material interfaces, the interface-side analytical atom set is defined based on the surface coordinated oxygen content or surface oxidation state. Using the method of this invention, high-scoring residues, candidate adhesion sites, and protein-level adhesion descriptors for each protein on different material surfaces can be output.

[0118] By comparing residue scores and adhesion descriptors under different interfacial chemical states, it is possible to determine whether changes in the surface chemistry of a material lead to enhanced, weakened, or rearranged adhesion of a particular protein. This result can be used to help evaluate the potential protein selectivity of neural interface materials after long-term exposure to a protein environment.

[0119] The above detailed embodiments describe the implementation of the present invention; however, the present invention is not limited to the specific details described in the above embodiments. Within the scope of the claims and technical concept of the present invention, various simple modifications and changes can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

Claims

1. A method for protein interface adhesion site identification and evaluation based on molecular dynamics trajectory, characterized in that, Includes the following steps: Based on the molecular dynamics trajectory data of the target protein and the target interface, the sets of atoms for protein-side analysis and interface-side analysis are determined. In each trajectory frame, the distance between protein-side analysis atoms and interface-side analysis atoms is calculated, and distance contact events are identified based on a preset distance threshold. Based on distance contact events, the donor, hydrogen atom and acceptor are identified, the donor-hydrogen-acceptor angle is calculated, and directional interaction events are identified according to a preset angle threshold. Protein residues are scored based on distance contact events and directional interaction events; Based on the scoring results, candidate adhesion residues, candidate adhesion sites, and / or protein-level adhesion descriptors are output.

2. The method of claim 1, wherein the method is characterized by, The protein-side analysis atom set is used to represent protein atoms that may participate in interfacial donor-receptor interactions; the interfacial analysis atom set is used to represent atoms on material surfaces or biological interfaces that can participate in short-range contact or directional interactions.

3. The method of claim 1, wherein the method is characterized by, The condition for determining the distance contact event is: the distance between the protein-side analysis atom and the interface-side analysis atom is less than or equal to a preset distance threshold.

4. The method of claim 3, wherein the method is characterized by, The criteria for determining the directional interaction event include: the donor-hydrogen-acceptor angle formed by the donor atom, the hydrogen atom connected to the donor atom, and the acceptor atom is greater than or equal to a preset angle threshold.

5. The method for identifying and evaluating protein interface adhesion sites based on molecular dynamics trajectories according to claim 1, characterized in that, The method further includes: scoring protein residues on multiple initial orientation trajectories of the same target protein and the same target interface, and determining site stability based on the repetition of candidate residues or candidate sites in multiple initial orientations.

6. The method for identifying and evaluating protein interface adhesion sites based on molecular dynamics trajectories according to claim 1, characterized in that, The method further includes: generating protein-level adhesion descriptors for multiple target proteins, and sorting, classifying or clustering the relative adhesion tendencies of multiple proteins on the same interface based on the descriptors.

7. The method for identifying and evaluating protein interface adhesion sites based on molecular dynamics trajectories according to claim 1, characterized in that, The method further includes: performing correlation analysis between protein-level adhesion descriptors and time-resolved proteomics data or protein crown data to evaluate the retention trend, enrichment trend, or class-level correspondence of proteins at the interface.

8. A protein interface adhesion site recognition system based on molecular dynamics trajectories, characterized in that, include: Data acquisition module: used to acquire molecular dynamics trajectory data of the target protein and the target interface; Atom set determination module: used to determine the protein-side polar atom set and the interface-side analytical atom set; Distance contact event recognition module: used to calculate the distance between protein-side analysis atoms and interface-side analysis atoms frame by frame, and to recognize distance contact events according to distance thresholds; Directional interaction event identification module: used to identify donor, hydrogen atom, and acceptor based on distance contact events, calculate donor-hydrogen-acceptor angle, and filter directional interaction events according to angle thresholds; Residue scoring module: Used to score protein residues based on distance contact events and directional interaction events; Site output module: Used to sort high-scoring residues and merge them into candidate adhesion sites according to sequence or spatial proximity, and then output them. Multi-trajectory consistency evaluation module and / or multi-protein comparison module: used to output adhesion descriptors and compare multiple orientations, multiple proteins or multiple environmental conditions, to achieve relative evaluation across proteins, interfaces and environmental conditions.

9. A computer device for identifying protein interface adhesion sites based on molecular dynamics trajectories, characterized in that, include: A processor, a memory, and a computer program, wherein the computer program, when executed by the processor, implements the method of any one of claims 1-7.

10. A computer-readable storage medium or computer program product, characterized in that, The computer instructions stored therein, when executed by a processor, implement the method described in any one of claims 1-7.

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