CN116665765A - Method and device for analyzing structural rigidity weak points of protein based on atomic nodes and network constraint model - Google Patents
Method and device for analyzing structural rigidity weak points of protein based on atomic nodes and network constraint model Download PDFInfo
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Abstract
The application relates to a method and a device for analyzing structural rigidity weaknesses of proteins based on an atomic node and a network constraint model. The method comprises the following steps: obtaining a first crystal structure of a target protein molecule; performing free energy minimization simulation on the first crystal structure to obtain an energy minimization crystal structure; constructing an atomic node and network constraint model of an energy minimization crystal structure; performing pyrolytic folding molecular dynamics simulation on the atomic nodes and the network constraint model until the atomic nodes and the network constraint model are in a motion balance state; analyzing the atomic node in the motion balance state and the network constraint model, and obtaining an analysis result; and finding out a weak rigidity region in the target protein molecule according to the analysis result. According to the scheme provided by the application, the rigidity weakness of the protein structure can be calculated, and more proper reconstruction sites or regions can be found, so that the protein can be subjected to targeted mutation, and the stability of protein molecules can be improved.
Description
Technical Field
The application relates to the technical field of computer and computational structure biology, in particular to a method and a device for analyzing structural rigidity weaknesses of proteins based on an atomic node and a network constraint model.
Background
The protein is a macromolecule which has high efficiency and high specificity and performs physiological functions, and can be widely applied to the fields of biological medicine and chemical production. However, proteins generally work under mild conditions and are extremely inactivated under extreme conditions, severely limiting their use.
There are small amounts of proteins in nature that can still be active under extreme conditions: the DNA polymerase used in the polymerase chain reaction is derived from a strain of thermophilic bacillus growing in hot springs, and compared with the most original escherichia coli DNA polymerase, the thermal stability of the polymerase is greatly improved. The sequences of the thermophilic bacillus DNA polymerase are similar to those of the escherichia coli DNA polymerase, but the sequences of the thermophilic bacillus DNA polymerase and the escherichia coli DNA polymerase are different from each other in thermal stability.
In 1961, krilis An Anfisen completed a series of protein denaturation and renaturation tests of bovine pancreatic ribonuclease and the like, and found that the folded protein or the denatured protein can still recover the original structure under the physiological condition. For example, the protein is denatured by high temperature or chemical factors, so that the structure of the protein is loose or disintegrated, and when the environment is changed back to the original state, the loose or disintegrated protein can be instantaneously folded to return to the original three-dimensional structure, and the protein is only in the three-dimensional structure no matter how many times the experiment is carried out. Amfisen then states that the primary amino acid sequence of a protein contains all the information of its secondary or higher order structure, i.e. the primary structure of the protein determines the higher order structure.
Therefore, how to rapidly start from the primary structure or the secondary structure of the protein and accurately analyze the rigidity weak point of the protein at fixed points is a problem to be solved.
Disclosure of Invention
In order to solve or partially solve the problems in the related art, the application provides a method and a device for analyzing the rigidity weak points of a protein structure based on an atomic node and a network constraint model, which can rapidly analyze the rigidity weak points of the protein structure and provide references for rational design for improving the stability of the protein.
The first aspect of the application provides a method for resolving structural rigidity weaknesses of proteins based on an atomic node and a network constraint model, which comprises the following steps:
obtaining a first crystal structure of a target protein molecule;
performing free energy minimization simulation on the first crystal structure to obtain an energy minimization crystal structure of the target protein molecule;
constructing an atomic node and network constraint model of the energy minimization crystal structure;
performing thermal unfolding molecular dynamics simulation on the atomic node of the energy minimization crystal structure and the network constraint model until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state;
analyzing the atomic node of the energy minimization crystal structure in the motion balance state and the network constraint model, and obtaining an analysis result;
And finding out a weak rigidity region in the target protein molecule according to the analysis result.
As an alternative embodiment, the obtaining the first crystal structure of the target protein molecule includes:
obtaining a second crystal structure carrying the target protein molecule;
repairing the crystal structure of the second crystal structure to obtain a repaired second crystal structure;
separating the first crystal structure of the target protein molecule from the repaired second crystal structure.
As an alternative embodiment, the performing free energy minimization simulation on the first crystal structure to obtain the energy minimization crystal structure of the target protein molecule includes:
adding a water molecular model and a force field to the first crystal structure to construct a topological structure of the target protein molecule;
adding a simulation box for the topology;
performing pretreatment of energy minimization simulation on the topological structure added with the simulation box under a vacuum condition by adopting a preset method;
formally performing energy minimization simulation on the topological structure added with the simulation box under a vacuum condition to obtain a simulation result;
and converting the topological structure corresponding to the simulation result into an energy minimization crystal structure of the target protein molecule, and outputting the energy minimization crystal structure.
As an alternative embodiment, the constructing the atomic node and network constraint model of the energy minimization crystal structure includes:
taking all atoms in the energy minimization crystal structure as atomic nodes, and taking covalent bonds and non-covalent bonds among all the atoms as connecting lines;
and setting the movement form of the corresponding connecting line according to the types of the covalent bond and the non-covalent bond.
As an alternative embodiment, the setting the movement form of the corresponding connection line according to the types of the covalent bond and the non-covalent bond includes:
if the covalent bond is a peptide bond or a covalent double bond, limiting rotation of the connecting line corresponding to the peptide bond or the covalent double bond;
if the covalent bond is a covalent single bond, setting that the connecting line corresponding to the covalent single bond can rotate around a bond axis and cannot be broken;
if the non-covalent bond is one of a hydrogen bond, a salt bond and a hydrophobic effect, the wire corresponding to the hydrogen bond or the salt bond is set to be cleavable.
As an alternative embodiment, van der waals interactions between the atoms are not used as wires.
As an optional embodiment, the performing a thermal unfolding molecular dynamics simulation on the atomic node of the energy minimization crystal structure and the network constraint model until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state includes:
And simulating the process of the connection line fracture of the atomic node of the energy minimization crystal structure and the network constraint model in the heating process until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state.
As an optional embodiment, the analyzing the atomic node of the energy minimization crystal structure in the motion equilibrium state and the network constraint model to obtain the analysis result includes:
the atomic nodes which are not broken and still keep the original network in analysis are gathered into one type and are divided into different structural clusters;
and marking the different structural clusters with different marks to obtain a plurality of different structural clusters with different marks.
As an alternative embodiment, the finding the weak rigidity region in the target protein molecule according to the analysis result includes:
according to the plurality of different structural clusters with different marks, finding a structural cluster with weaker interaction, and finding secondary structural information of amino acid residues in the structural cluster with weaker interaction.
The second aspect of the present application provides an apparatus for resolving structural rigidity weaknesses of proteins based on atomic nodes and a network constraint model, comprising:
An acquisition module for acquiring a first crystal structure of the target protein molecule;
the first simulation module is used for performing free energy minimization simulation on the first crystal structure to obtain an energy minimization crystal structure of the target protein molecule;
the construction module is used for constructing an atomic node and network constraint model of the energy minimization crystal structure;
the second simulation module is used for carrying out pyrolytic folding molecular dynamics simulation on the atomic node of the energy minimization crystal structure and the network constraint model until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state;
the analysis module is used for analyzing the atomic node of the energy minimization crystal structure in the motion balance state and the network constraint model, and obtaining an analysis result;
and the determining module is used for finding out a weak rigidity area in the target protein molecule according to the analysis result.
A third aspect of the present application provides an electronic apparatus, comprising:
a processor; and
a memory having executable code stored thereon which, when executed by the processor, causes the processor to perform the method as described above.
A fourth aspect of the application provides a computer readable storage medium having stored thereon executable code which, when executed by a processor of an electronic device, causes the processor to perform a method as described above.
The technical scheme provided by the application can comprise the following beneficial effects:
the embodiment of the application obtains the first crystal structure of the target protein molecule; performing free energy minimization simulation on the first crystal structure to obtain an energy minimization crystal structure; constructing an atomic node and network constraint model of an energy minimization crystal structure, and changing a complex protein structure into a simple structure of a node, a connecting line and a network; performing thermal unfolding molecular dynamics simulation on the atomic node of the energy minimization crystal structure and the network constraint model until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state; analyzing the atomic node of the energy minimization crystal structure in the motion balance state and the network constraint model, and obtaining an analysis result; and finally, finding out a weak rigidity area in the target protein molecule according to the analysis result. Therefore, the weak rigidity area of the target protein molecular structure can be calculated, and more proper reconstruction sites or areas can be found, so that the protein molecules can be subjected to targeted mutation, and the stability of the protein molecules is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.
Drawings
The foregoing and other objects, features and advantages of the application will be apparent from the following more particular descriptions of exemplary embodiments of the application as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout the exemplary embodiments of the application.
FIG. 1 is a schematic flow diagram of a method for resolving structural rigidity weaknesses of proteins based on atomic nodes and a network constraint model according to an embodiment of the present application;
FIG. 2 is another flow diagram of a method for resolving structural rigidity vulnerabilities of proteins based on atomic nodes and a network constraint model according to an embodiment of the present application;
FIG. 3 is a schematic flow diagram of a method for resolving structural rigidity weaknesses of proteins based on atomic nodes and a network constraint model according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a region of weakness of the FGF10 protein molecule presented in an embodiment of the present application;
FIG. 5 is a schematic structural diagram of an apparatus for resolving structural rigidity weaknesses of proteins based on an atomic node and a network constraint model according to an embodiment of the present application;
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While embodiments of the present application are illustrated in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the application to those skilled in the art.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.
It should be understood that although the terms "first," "second," and the like may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the application. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
The embodiment of the application provides a method for analyzing protein structural rigidity weaknesses based on an atomic node and network constraint model, which can rapidly analyze protein structural rigidity weaknesses based on a computer and computational structure biological technology and provides references for improving protein stability rational design.
The following describes the technical scheme of the embodiment of the present application in detail with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method for resolving structural rigidity weaknesses of proteins based on atomic nodes and a network constraint model according to an embodiment of the present application.
Referring to fig. 1, a method for resolving structural rigidity weak points of proteins based on an atomic node and a network constraint model according to an embodiment of the present application includes steps S1 to S6:
step S1: a first crystal structure of the target protein molecule is obtained.
The first crystal structure of the target protein molecule can be obtained by the following method: obtaining a second crystal structure of the target protein molecule; repairing the crystal structure of the second crystal structure to obtain a repaired second crystal structure; and separating the first crystal structure of the target protein molecule from the repaired second crystal structure.
The second crystal structure in the embodiment of the application refers to a crystal structure of a target protein molecule analyzed by a biophysical method. The second crystal structure obtains the crystal structure of the target protein molecule from a protein structure database (Protein Data Bank, PDB for short). Wherein the protein structure database may be constructed in advance. It should be noted that modeling can be performed by using a modeling method of the related art, which is not limited in the present application.
Step S2: and performing free energy minimization simulation on the first crystal structure to obtain the energy minimization crystal structure of the target protein molecule.
The embodiments of the present application can obtain an energy minimized crystal structure by: adding a water molecular model and a force field for the first crystal structure to construct a topological structure of the target protein molecule; adding a simulation box for the topology; performing pretreatment of energy minimization simulation on the topological structure under a vacuum condition by adopting a preset method; formally performing energy minimization simulation on the topological structure under a vacuum condition to obtain a simulation result; and converting the topological structure corresponding to the simulation result into an energy minimization crystal structure of the target protein molecule, and outputting the energy minimization crystal structure.
Step S3: and constructing an atomic node and network constraint model of the energy minimization crystal structure.
The embodiment of the application can construct an atomic node and network constraint model of an energy minimization crystal structure by the following modes: taking all atoms in the energy minimization crystal structure as atomic nodes, and taking covalent bonds and non-covalent bonds among all atoms as connecting lines; and setting the movement form of the corresponding connecting line according to the types of the covalent bond and the non-covalent bond.
Wherein, the movement form of the corresponding connecting line is set according to the types of covalent bonds and non-covalent bonds, and the method can comprise the following steps: if the covalent bond is a peptide bond or a covalent double bond, limiting rotation of a connecting line corresponding to the peptide bond or the covalent double bond; if the covalent bond is a covalent single bond, setting that a connecting line corresponding to the covalent single bond can rotate around a bond axis and cannot be broken; if the non-covalent bond is one of a hydrogen bond, a salt bond and a hydrophobic effect, then the bond or the bond corresponding to the salt bond is set to be cleavable.
Step S4: and performing thermal unfolding molecular dynamics simulation on the atomic node of the energy minimization crystal structure and the network constraint model until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state.
Step S4 of the embodiment of the present application may be simulated in the following manner: and simulating the process of connecting line fracture of the atomic node of the energy minimization crystal structure and the network constraint model in the heating process until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state.
Step S5: and analyzing the atomic node of the energy minimization crystal structure in the motion balance state and the network constraint model, and obtaining an analysis result.
The embodiment of the application can be analyzed by the following modes: the method comprises the steps of gathering atomic nodes which are not broken in the analysis and still keep the original network into one type, and dividing the atomic nodes into clusters with different structures; different structural clusters are marked with different marks, and a plurality of different structural clusters with different marks are obtained.
That is, a node with interactions is understood to be a group of atomic nodes whose links are not broken during thermal unfolding and which still remain in the original network. Therefore, a group of atomic nodes which are not broken in the connecting line in the thermal unfolding process and still keep the original network can be gathered into one type and divided into different structural clusters.
Step S6: and finding out a weak rigidity region in the target protein molecule according to the analysis result.
According to the embodiment of the application, the structure cluster with weak interaction can be found according to a plurality of different structure clusters with different marks, and the secondary structure information of the amino acid residues in the structure cluster with weak interaction can be found.
The embodiment of the application obtains the first crystal structure of the target protein molecule; performing free energy minimization simulation on the first crystal structure to obtain an energy minimization crystal structure; constructing an atomic node and network constraint model of an energy minimization crystal structure, and changing a complex protein structure into a simple structure of a node, a connecting line and a network; performing thermal unfolding molecular dynamics simulation on the atomic node of the energy minimization crystal structure and the network constraint model until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state; analyzing the atomic node of the energy minimization crystal structure in the motion balance state and the network constraint model, and obtaining an analysis result; and finally, finding out a weak rigidity area in the target protein molecule according to the analysis result. Therefore, the weak rigidity area of the target protein molecular structure can be calculated, and more proper reconstruction sites or areas can be found, so that the protein molecules can be subjected to targeted mutation, and the stability of the protein molecules is improved.
FIG. 2 is another flow diagram of a method for resolving structural rigidity vulnerabilities of proteins based on atomic nodes and a network constraint model according to an embodiment of the present application; FIG. 3 is a schematic flow diagram of a method for resolving structural rigidity weaknesses of proteins based on atomic nodes and a network constraint model according to an embodiment of the present application.
Referring to fig. 2 and 3, a method for resolving structural rigidity weak points of proteins based on an atomic node and a network constraint model according to an embodiment of the present application includes the following steps:
s10: obtaining a second crystal structure with the target protein molecule.
The second crystal structure of the embodiment of the application refers to a crystal structure of a target protein molecule analyzed by a biophysical method. The second crystal structure obtains the crystal structure of the target protein molecule from a protein structure database (Protein Data Bank, PDB for short). Wherein the protein structure database may be constructed in advance. It should be noted that modeling can be performed by using a modeling method of the related art, which is not limited in the present application.
S11: and repairing the crystal structure of the second crystal structure to obtain the repaired second crystal structure.
For example, the electron density symmetry of the glutamine residue, the amide group in the asparagine residue side chain and the imidazole group in the histidine residue side chain in the second crystal structure is extremely high, and these amino acid residue side chains need to be inverted 180 °, and then specific positions are determined by calculating interactions with surrounding atoms. Other amino acid residues optimize energy through subtle rotations of the side chain groups or the peptide plane. And finally obtaining the repaired second crystal structure.
S12: and separating the first crystal structure of the target protein molecule from the repaired second crystal structure.
Wherein, the first crystal structure of the target protein molecule can be separated from the repaired second crystal structure by a separation method in the related art, which is not limited by the present application.
S20: and adding a water molecular model and a force field to the first crystal structure to construct the topological structure of the target protein molecule.
The embodiment of the application can utilize molecular dynamics simulation, input a first crystal structure, add a water molecule model such as TIP3P and a force field such as Amber99sb-ildn for the first crystal structure, and construct a topological structure of a target protein molecule.
S21: a simulated box is added to the topology.
The simulated box of the embodiment of the application can be a solvent box, the shape and the size of the simulated box can be defined, for example, a cubic simulated box with the boundary distance of 2nm can be added for the topological structure of the target protein molecule.
S22: and (3) carrying out pretreatment of energy minimization simulation on the topological structure added with the simulation box under the vacuum condition by adopting a preset method.
The preset method of the embodiment of the application can be a steepest descent method, and the step number of energy minimization can be set according to actual conditions.
S23: and formally performing energy minimization simulation on the topological structure added with the simulation box under the vacuum condition to obtain a simulation result.
And (4) obtaining the optimal step number of energy minimization according to the pretreatment in the step (S22), and formally performing energy minimization simulation on the topological structure under the vacuum condition by using the optimal step number of energy minimization.
S24: and converting the topological structure corresponding to the simulation result into an energy minimization crystal structure of the target protein molecule, and outputting the energy minimization crystal structure.
Since the result of the simulation is the topology of the target protein molecule, it is necessary to convert the topology of the target protein molecule into a crystal structure and minimize the crystal structure as energy of the target protein molecule.
S30: all atoms in the energy minimization crystal structure are taken as atomic nodes, and covalent bonds and non-covalent bonds between all atoms are taken as connecting lines.
In this step, all atoms in the energy minimized crystal structure can be taken as nodes, and covalent bonds and non-covalent bonds between all atoms can be taken as links. In addition, van der Waals interactions between atoms may not be used as a link.
By constructing an atomic node and network constraint model of an energy minimization crystal structure, a complex protein structure is changed into a simple structure of a node, a connecting line and a network, the subsequent calculated amount is greatly reduced, and the efficiency of analyzing the rigidity weak points of the protein molecular structure is improved.
S31: and setting the movement form of the corresponding connecting line according to the types of the covalent bond and the non-covalent bond.
For example: if the covalent bond is a peptide bond or a covalent double bond, rotation of the wire corresponding to the peptide bond or covalent double bond is restricted. If the covalent bond is a covalent single bond, the connection line corresponding to the covalent single bond is set to be rotatable around the bond axis and not cleavable. If the non-covalent bond is one of a hydrogen bond, a salt bond and a hydrophobic effect, then the bond or the bond corresponding to the salt bond is set to be cleavable.
S40: and simulating the process of connecting line fracture of the atomic node of the energy minimization crystal structure and the network constraint model in the heating process until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state.
The embodiment of the application simulates the thermal unfolding process and acquires a set number of conformations, such as 5000 atomic nodes in a motion balance state and a network constraint model, for statistical analysis.
The thermal unfolding process is described below by way of example with respect to several non-covalent bonds:
the energy of the broken connection line of hydrogen bond and salt bond is simulated as follows:
is Gaussian white noise->A standard deviation of 0 for the mean depends on the gaussian distribution of hydrogen bonds.
The energy of the link fracture of the hydrophobic effect simulates the following formula:
d ij D is the distance between nodes vdW For Van der Waals interactions, D cut Is a gaussian function half width.
S50: and (3) gathering the atomic nodes which are not broken in the analysis and still keep the original network into one type, and dividing the atomic nodes into different structural clusters.
A set number, for example 5000, of link fracture conditions in the unfolding process of the conformations of the atomic nodes in the motion equilibrium state and the network constraint model are analyzed statistically. And (3) gathering a group of atomic nodes which are not broken in the connection line and still keep the original network in the thermal unfolding process into one type, and dividing the group of atomic nodes into different structural clusters.
After thermal unfolding simulation, the connecting lines are not broken, and the interaction among atomic nodes of the original network is still kept large, so that the stability of protein molecules is supported, and the nodes with the interaction are clustered together to form different structural clusters.
S51: different structural clusters are marked with different marks, and a plurality of different structural clusters with different marks are obtained.
The form of the mark is not limited in the embodiment of the present application, and may be, for example, color or number, so long as the structure cluster can be distinguished. Different structure clusters can be distinguished through marking, and target structure clusters meeting the requirements can be found more clearly and intuitively.
S60: according to a plurality of different structural clusters with different marks, a structural cluster with weaker interaction is found, and secondary structural information of amino acid residues in the structural cluster with weaker interaction is found.
For example, the presence of relatively independent structural clusters in a protein molecule, which indicate weak interactions between these structural clusters, and the cleavage of the links after thermal unfolding simulation, may be considered to increase the interactions between these independent structural clusters to increase the thermal stability of the protein molecule.
The following embodiment of the application takes a human FGF10 protein molecule as an example, and describes a method for analyzing structural rigidity weaknesses of protein based on an atomic node and network constraint model, which comprises the following steps:
1. the method comprises the steps of firstly obtaining a second crystal structure 1NUN of a receptor FGFR2b complex with FGF10 protein molecules, which is obtained through crystallization and analysis by an X-ray diffraction method, from a PDB database, then repairing the second crystal structure 1NUN, and finally separating a first crystal structure of the FGF10 protein molecules from the second crystal structure 1NUN. Repairing the second crystal structure 1NUN includes: the electron density symmetry of the glutamine residue, the amide group in the asparagine residue side chain and the imidazole group in the histidine residue side chain in the second crystal structure 1NUN is extremely high, the amino acid residue side chains need to be turned 180 degrees, and specific positions are judged by calculating the interactions with surrounding atoms; other amino acid residues optimize energy by subtle rotations of the side chain groups or the peptide plane; and finally obtaining the repaired second crystal structure 1NUN.
2. And performing free energy minimization simulation on the first crystal structure to obtain an energy minimization crystal structure. For example, the first crystal structure of the FGF10 protein molecule can be input by utilizing molecular dynamics simulation, and the topological structure of the FGF10 protein molecule can be constructed by adding a TIP3P water molecular model and an Amber99sb-ildn force field. A cubic simulated box was then added at a distance of 2nm from the boundary. And then carrying out energy minimization pretreatment on the topological structure of the FGF10 protein molecule under a vacuum condition by adopting a steepest descent method, and carrying out formal energy minimization simulation on the topological structure of the FGF10 protein molecule under the vacuum condition to obtain a simulation result. And finally, converting the topological structure of the FGF10 protein molecule corresponding to the simulation result into an energy minimization crystal structure of the target protein molecule, and outputting the energy minimization crystal structure.
3. And constructing an atomic node and network constraint model of an energy minimization crystal structure of the FGF10 protein molecule. For example, all atoms in the energy minimization crystal structure of FGF10 protein molecules are considered as atomic nodes, and covalent and non-covalent bonds between all atoms are taken as the connecting lines, and van der waals interactions between atoms are not taken as the connecting lines. And setting the movement form of the corresponding connecting line according to the types of the covalent bond and the non-covalent bond. Wherein, the energy minimization crystal structure of FGF10 protein molecule has 6 connecting lines with covalent double bonds, and the rotation of the connecting lines is strictly limited. The covalent single bond in the energy minimization crystal structure of the FGF10 protein molecule counts as 5 links, which can rotate around the shaft and cannot be broken. The energy of FGF10 protein molecules minimizes hydrogen bonds and salt bonds in the crystal structure, and 5 lines are counted and can be broken. The hydrophobic effect in the energy minimization crystal structure of FGF10 protein molecules is 2 lines, which can be broken.
4. And performing pyrolytic folding molecular dynamics simulation on an atomic node of an energy minimization crystal structure of the FGF10 protein molecule and a network constraint model until the energy minimization crystal structure of the FGF10 protein molecule is in a motion balance state. For example: simulating a thermal unfolding process, wherein the sampling number is 5000, and acquiring 5000 conformations of atomic nodes in a motion balance state and a network constraint model for statistical analysis. And simulating the process of connecting line fracture between the atomic node of the energy minimization crystal structure of the FGF10 protein molecule and the network constraint model in the heating process until the atomic node of the energy minimization crystal structure of the FGF10 protein molecule and the network constraint model are in a motion balance state.
5. And analyzing the atomic node of the energy minimization crystal structure of the FGF10 protein molecule in the motion equilibrium state and the network constraint model, and obtaining an analysis result. For example: and (3) statistically analyzing the broken states of the connection lines of 5000 atomic nodes in the motion balance state and the conformations of the network constraint model in the unfolding process. The method comprises the steps of gathering atomic nodes which are not broken in a connecting line in a thermal unfolding process and still keep an original network into one type, and dividing the atomic nodes into clusters with different structures; and marking different structural clusters with different colors to obtain a plurality of different structural clusters marked with different colors.
6. According to a plurality of different structural clusters with different labels, a structural cluster with weaker interaction in FGF10 protein molecules is found, and secondary structural information of amino acid residues in the structural cluster with weaker interaction is found.
7. By the above method, FGF10 crystal structure was divided into 6 relatively independent parts: core region (core), region a, region B, region C, region D, and the N-terminus. These 6 portions form 6 relatively independent clusters of structures. The interactions inside each structural cluster are tight, and the interactions among 6 structural clusters are extremely weak. Further searching for secondary structure information of amino acid residues in the structure cluster with weak interaction: the N-terminus, β2- β3loop, β3- β4loop, heparin binding region, and C-terminus of FGF10 are not closely related to other regions. These clusters and secondary structures are areas of weakness in FGF10 rigidity (fig. 4). Aiming at the weak rigidity area of the protein molecular structure, more proper reconstruction sites or areas can be searched, so that the protein molecules can be subjected to targeted mutation, and the stability of the protein molecules is improved.
Corresponding to the embodiment of the application function implementation method, the application also provides a device for analyzing the structural rigidity weak point of the protein based on the atomic node and the network constraint model, electronic equipment and corresponding embodiments.
Fig. 5 is a schematic structural diagram of an apparatus for resolving structural rigidity weaknesses of proteins based on an atomic node and a network constraint model according to an embodiment of the present application.
Referring to fig. 5, an apparatus for resolving structural rigidity weaknesses of proteins based on atomic nodes and a network constraint model, comprising: the system comprises an acquisition module 50, a first simulation module 51, a construction module 52, a second simulation module 53, an analysis module 54 and a determination module 55.
An acquisition module 50 for acquiring a first crystal structure of the protein molecule.
The first simulation module 51 is configured to perform free energy minimization simulation on the first crystal structure to obtain an energy minimization crystal structure of the target protein molecule.
A construction module 52 for constructing an atomic node and network constraint model of the energy minimization crystal structure.
The second simulation module 53 is configured to perform a pyrolytic folding molecular dynamics simulation on the atomic node of the energy-minimized crystal structure and the network constraint model until the atomic node of the energy-minimized crystal structure and the network constraint model are in a motion balance state.
The analysis module 54 is configured to analyze the atomic node of the energy minimization crystal structure in the motion equilibrium state and the network constraint model, and obtain an analysis result;
The determining module 55 is configured to find out a weak rigidity region in the target protein molecule according to the analysis result.
The acquiring module 50 includes an acquiring sub-module, a repairing module and a separating module.
The acquisition submodule is used for acquiring a second crystal structure with target protein molecules; the repair module is used for repairing the crystal structure of the second crystal structure to obtain a repaired second crystal structure; the separation module is used for separating the first crystal structure of the target protein molecule from the repaired second crystal structure.
The first simulation module 51 includes a first adding module, a second adding module, a preprocessing module, a formal simulation module, and a conversion output module.
The first adding module is used for adding a water molecular model and a force field to the first crystal structure to construct a topological structure of the target protein molecule; the second adding module is used for adding a simulation box for the topological structure; the pretreatment module is used for carrying out pretreatment of energy minimization simulation on the topological structure added with the simulation box by adopting a preset method under the vacuum condition; the formal simulation module is used for formally performing energy minimization simulation on the topological structure added with the simulation box under the vacuum condition to obtain a simulation result; the conversion output module is used for converting the topological structure corresponding to the simulation result into an energy minimization crystal structure of the target protein molecule and outputting the energy minimization crystal structure.
The build module 52 includes a modeling module and a setup module.
The modeling module is used for taking all atoms in the energy minimization crystal structure as atomic nodes and covalent bonds and non-covalent bonds among all atoms as connecting lines; the setting module is used for setting the movement form of the corresponding connecting line according to the types of the covalent bond and the non-covalent bond. For example: if the covalent bond is a peptide bond or a covalent double bond, rotation of the wire corresponding to the peptide bond or covalent double bond is restricted. If the covalent bond is a covalent single bond, the connection line corresponding to the covalent single bond is set to be rotatable around the bond axis and not cleavable. If the non-covalent bond is one of a hydrogen bond, a salt bond and a hydrophobic effect, then the bond or the bond corresponding to the salt bond is set to be cleavable.
The parsing module 54 includes a clustering module and a labeling module.
The clustering module is used for gathering the atomic nodes which are not broken in the analysis and still keep the original network into one type and dividing the atomic nodes into clusters with different structures; the marking module is used for marking different structural clusters with different marks to obtain a plurality of different structural clusters with different marks. The form of the mark is not limited in the embodiment of the present application, and may be, for example, color or number, so long as the structure cluster can be distinguished. Different structure clusters can be distinguished through marking, and target structure clusters meeting the requirements can be found more clearly and intuitively.
The determining module 55 is configured to find a structure cluster with weak interaction according to a plurality of different structure clusters with different labels, and find secondary structure information of amino acid residues in the structure cluster with weak interaction. For example, the presence of relatively independent structural clusters in a protein molecule, which indicate weak interactions between these structural clusters, and the cleavage of the links after thermal unfolding simulation, may be considered to increase the interactions between these independent structural clusters to increase the thermal stability of the protein molecule.
The embodiment of the application obtains the first crystal structure of the target protein molecule; performing free energy minimization simulation on the first crystal structure to obtain an energy minimization crystal structure; constructing an atomic node and network constraint model of an energy minimization crystal structure, and changing a complex protein structure into a simple structure of a node, a connecting line and a network; performing thermal unfolding molecular dynamics simulation on the atomic node of the energy minimization crystal structure and the network constraint model until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state; analyzing the atomic node of the energy minimization crystal structure in the motion balance state and the network constraint model, and obtaining an analysis result; and finally, finding out a weak rigidity area in the target protein molecule according to the analysis result. Therefore, the weak rigidity area of the target protein molecular structure can be calculated, and more proper reconstruction sites or areas can be found, so that the protein molecules can be subjected to targeted mutation, and the stability of the protein molecules is improved.
The specific manner in which the respective modules perform the operations in the apparatus of the above embodiments has been described in detail in the embodiments related to the method, and will not be described in detail herein.
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Referring to fig. 6, an electronic device 600 includes a memory 610 and a processor 620.
The processor 620 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Memory 610 may include various types of storage units, such as system memory, read Only Memory (ROM), and persistent storage. Where the ROM may store static data or instructions that are required by the processor 620 or other modules of the computer. The persistent storage may be a readable and writable storage. The persistent storage may be a non-volatile memory device that does not lose stored instructions and data even after the computer is powered down. In some embodiments, the persistent storage device employs a mass storage device (e.g., magnetic or optical disk, flash memory) as the persistent storage device. In other embodiments, the persistent storage may be a removable storage device (e.g., diskette, optical drive). The system memory may be a read-write memory device or a volatile read-write memory device, such as dynamic random access memory. The system memory may store instructions and data that are required by some or all of the processors at runtime. Furthermore, memory 610 may include any combination of computer-readable storage media including various types of semiconductor memory chips (e.g., DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), magnetic disks, and/or optical disks may also be employed. In some implementations, memory 610 may include readable and/or writable removable storage devices such as Compact Discs (CDs), digital versatile discs (e.g., DVD-ROMs, dual layer DVD-ROMs), blu-ray discs read only, super-density discs, flash memory cards (e.g., SD cards, min SD cards, micro-SD cards, etc.), magnetic floppy disks, and the like. The computer readable storage medium does not contain a carrier wave or an instantaneous electronic signal transmitted by wireless or wired transmission.
The processor 620 may include an obtaining module 50, a first simulation module 51, a building module 52, a second simulation module 53, an analyzing module 54, and a determining module 55, and specific functions and connection relationships may be described with reference to fig. 5, which is not repeated herein.
The electronic device 600 may also include a display for presenting results of execution by the processor 520.
The memory 610 has stored thereon executable code that, when processed by the processor 520, can cause the processor 620 to perform some or all of the methods described above.
Furthermore, the method according to the application may also be implemented as a computer program or computer program product comprising computer program code instructions for performing part or all of the steps of the above-described method of the application.
Alternatively, the application may also be embodied as a computer-readable storage medium (or non-transitory machine-readable storage medium or machine-readable storage medium) having stored thereon executable code (or a computer program or computer instruction code) which, when executed by a processor of an electronic device (or a server, etc.), causes the processor to perform part or all of the steps of the above-described method according to the application.
The foregoing description of embodiments of the application has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the improvement of technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A method for resolving structural rigidity weaknesses of proteins based on atomic nodes and a network constraint model, comprising the steps of:
obtaining a first crystal structure of a target protein molecule;
performing free energy minimization simulation on the first crystal structure to obtain an energy minimization crystal structure of the target protein molecule;
constructing an atomic node and network constraint model of the energy minimization crystal structure;
performing thermal unfolding molecular dynamics simulation on the atomic node of the energy minimization crystal structure and the network constraint model until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state;
Analyzing the atomic node of the energy minimization crystal structure in the motion balance state and the network constraint model, and obtaining an analysis result;
and finding out a weak rigidity region in the target protein molecule according to the analysis result.
2. The method of claim 1, wherein the obtaining a first crystal structure of the target protein molecule comprises:
obtaining a second crystal structure carrying the target protein molecule;
repairing the crystal structure of the second crystal structure to obtain a repaired second crystal structure;
separating the first crystal structure of the target protein molecule from the repaired second crystal structure.
3. The method of claim 1, wherein said performing free energy minimization simulation on said first crystal structure to obtain an energy minimization crystal structure of said target protein molecule comprises:
adding a water molecular model and a force field to the first crystal structure to construct a topological structure of the target protein molecule;
adding a simulation box for the topology;
performing pretreatment of energy minimization simulation on the topological structure added with the simulation box under a vacuum condition by adopting a preset method;
Formally performing energy minimization simulation on the topological structure added with the simulation box under a vacuum condition to obtain a simulation result; and converting the topological structure corresponding to the simulation result into an energy minimization crystal structure of the target protein molecule, and outputting the energy minimization crystal structure.
4. The method of claim 1, wherein said constructing an atomic node and network constraint model of the energy minimization crystal structure comprises:
taking all atoms in the energy minimization crystal structure as atomic nodes, and taking covalent bonds and non-covalent bonds among all the atoms as connecting lines;
and setting the movement form of the corresponding connecting line according to the types of the covalent bond and the non-covalent bond.
5. The method of claim 4, wherein said setting the movement pattern of the corresponding link according to the types of the covalent bond and the non-covalent bond comprises:
if the covalent bond is a peptide bond or a covalent double bond, limiting rotation of the connecting line corresponding to the peptide bond or the covalent double bond;
if the covalent bond is a covalent single bond, setting that the connecting line corresponding to the covalent single bond can rotate around a bond axis and cannot be broken;
If the non-covalent bond is one of a hydrogen bond, a salt bond and a hydrophobic effect, the wire corresponding to the hydrogen bond or the salt bond is set to be cleavable.
6. The method of claim 4, wherein resolving the atomic nodes of the energy minimized crystal structure in a state of motion equilibrium with a network constraint model and obtaining a resolved result comprises:
the atomic nodes which are not broken and still keep the original network in analysis are gathered into one type and are divided into different structural clusters;
and marking the different structural clusters with different marks to obtain a plurality of different structural clusters with different marks.
7. The method of claim 6, wherein the locating the region of weakness in the target protein molecule based on the analysis result comprises:
according to the plurality of different structural clusters with different marks, finding a structural cluster with weaker interaction, and finding secondary structural information of amino acid residues in the structural cluster with weaker interaction.
8. An apparatus for resolving structural rigidity weaknesses of proteins based on atomic nodes and a network constraint model, comprising:
An acquisition module for acquiring a first crystal structure of the target protein molecule;
the first simulation module is used for performing free energy minimization simulation on the first crystal structure to obtain an energy minimization crystal structure of the target protein molecule;
the construction module is used for constructing an atomic node and network constraint model of the energy minimization crystal structure;
the second simulation module is used for carrying out pyrolytic folding molecular dynamics simulation on the atomic node of the energy minimization crystal structure and the network constraint model until the atomic node of the energy minimization crystal structure and the network constraint model are in a motion balance state;
the analysis module is used for analyzing the atomic node of the energy minimization crystal structure in the motion balance state and the network constraint model, and obtaining an analysis result;
and the determining module is used for finding out a weak rigidity area in the target protein molecule according to the analysis result.
9. An electronic device, comprising:
a processor; and
a memory having executable code stored thereon, which when executed by the processor, causes the processor to perform the method of any of claims 1-7.
10. A computer readable storage medium having stored thereon executable code which when executed by a processor of an electronic device causes the processor to perform the method of any of claims 1-7.
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