A method and system for rapid screening of alternative secondary metabolites for antibiotic resistance

Abstract

This invention discloses a method and system for rapidly screening alternative secondary metabolites of antibiotic resistance. The method includes: reading preset known antibacterial activity structure data and molecular structure data of the secondary metabolites to be screened; calculating whether each molecular structure of the secondary metabolite to be screened possesses known antibacterial activity structural features; and outputting the structure of the alternative secondary metabolite of antibiotic resistance and the corresponding type of antibiotic drug that can be substituted. This invention achieves rapid and efficient screening of alternative secondary metabolites of antibiotic resistance. It not only eliminates the need for molecular docking calculations using specific antibiotic target protein receptors, saving significant computational resources and time, but also is applicable to various types of antibiotic drugs, covering most known antibacterial activity mechanisms. The output results can be directly used as a reference and basis for the design of natural antibiotic drugs and can be used for high-throughput screening of natural antibiotic drugs.

Description

Technical Field

[0001] This invention relates to a method and system for rapidly screening alternative secondary metabolites of antibiotic resistance, belonging to the field of information processing technology. Background Technology

[0002] For decades, antibiotics have saved countless lives from once-deadly infections. However, due to overuse or misuse in the medical and animal health fields, these indispensable antibiotics are rapidly losing their effectiveness, a phenomenon known as antibiotic resistance. In fact, antibiotic resistance is a natural evolutionary process of microorganisms; microbial resistance to antibiotics is inherent in nature because antibiotics are actually secondary metabolites of microorganisms. With antibiotic resistance seriously endangering human health in recent years, scientists worldwide have begun to dedicate themselves to developing various strategies to combat resistance. These strategies mainly include vigorously exploring and screening new antibiotics and antibacterial drugs, researching new targets of action, and developing antibiotic adjuvants (Bulletin of the Chinese Academy of Sciences, 2015, Vol. 30, No. 4, pp. 509-516). Currently, three drug development methods are used: whole-cell (non-target) antibacterial screening, in vitro high-throughput screening based on individual biochemical targets (identified through genomic methods), and structure-based drug development (SBDD). Structure-based drug development (SBDD) includes Virtual High-Throughput Screening (VHTS) and Fragment-Based Drug Design (FBDD), which is a novel computer-aided method for discovering new drugs. This method becomes feasible due to the elucidation of the three-dimensional structure of drug targets (Foreign Medicine and Antibiotics, January 2014, Vol. 35, No. 1, pp. 5-11).

[0003] Secondary metabolites are structurally complex, reactive small-molecule chemical substances synthesized by microorganisms through secondary metabolic biosynthesis after reaching a certain stage of microbial growth, under specific conditions such as time, state, and environment. The diversity of microorganisms and their metabolites provides a rich and irreplaceable resource for drug screening. To date, the vast majority of antibacterial drugs used clinically, such as penicillin, erythromycin, and tetracycline, are derived from microbial metabolites. Screening for antibiotic resistance alternatives based on known antibacterial activity structures will be a rapid and low-risk approach to mitigating the threat posed by drug-resistant bacteria and providing clinically viable drug options for treating drug-resistant infections.

[0004] However, if existing structure-based virtual screening methods are used to screen for alternative secondary metabolites of antibiotic resistance, it is necessary to calculate the binding ability of the chemical structure of the secondary metabolite to the antimicrobial target protein. This usually requires molecular docking. Although molecular docking technology is quite mature, its computational complexity and accuracy requirements require a lot of computational resources and time, resulting in low screening efficiency. In addition, molecular docking can only predict the binding state between drug molecule ligands and a specific target protein receptor, and cannot broadly screen different types of antibiotics, resulting in a narrow screening range and making it impossible to achieve large-scale and rapid screening of alternative secondary metabolites of antibiotic resistance. Summary of the Invention

[0005] In view of the above-mentioned problems and needs of the existing technology, the purpose of this invention is to provide a method and system for rapidly screening alternative secondary metabolites of antibiotic resistance, providing a fast and efficient auxiliary means to alleviate the threat of antibiotic resistance and develop natural antibiotic drugs.

[0006] To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0007] A method for rapidly screening alternative secondary metabolites of antibiotic resistance includes the following steps:

[0008] S1) Read the preset known antibacterial activity structure data and the molecular structure data of the secondary metabolites to be screened;

[0009] S2) Calculate whether each secondary metabolite to be screened has known antibacterial activity structural features in its molecular structure;

[0010] S3) Output the structure of alternative secondary metabolites for antibiotic resistance and the corresponding types of antibiotic drugs that can be substituted.

[0011] In one implementation scheme, in step S1), the known antibacterial activity structure data read includes the known antibacterial activity structure and the corresponding antibiotic drug type, and the molecular structure data of the secondary metabolite to be screened read includes the molecular structure of the secondary metabolite and the corresponding biosynthetic pathway type.

[0012] In one embodiment, in step S2), the known antibacterial active structural feature includes a known antibacterial active structure of at least one antibiotic drug type selected from "aminoglycosides", "oxazolidinones", "quinolones", "chloramphenicol", "β-lactams", "macrolides", "tetracyclines", and "glycopeptides".

[0013] In a further implementation scheme, step S2) calculates whether each secondary metabolite molecule to be screened possesses known antibacterial activity structural features in the following order:

[0014] S21) Calculate whether the molecular structure of the secondary metabolite to be screened contains a known antibacterial active structure of the preset antibiotic drug types of "aminoglycosides", "oxazolidinones", "quinolones", "chloramphenicols" and "β-lactams".

[0015] S22) Calculate whether the molecular structure of the secondary metabolite to be screened contains a known antibacterial active structure of the preset "macrolide" and "macrolide" antibiotic drug types;

[0016] S23) Calculate whether the molecular structure of the secondary metabolite to be screened contains a known antibacterial active structure of a preset "tetracycline" antibiotic drug type;

[0017] S24) Calculate whether the molecular structure of the secondary metabolite to be screened contains a known antibacterial active structure of a preset "glycopeptide" antibiotic drug type.

[0018] In a further implementation scheme, if the calculation result of step S21) contains a known antibacterial active structure of antibiotic drug types such as "aminoglycosides", "oxazolidinones", "quinolones" and "chloramphenicol", then the molecular structure of the secondary metabolite is marked as the hit structure, and the alternative antibiotic drug types are marked as "aminoglycosides", "oxazolidinones", "quinolones" and "chloramphenicol" respectively.

[0019] In a further implementation scheme, if the calculation result of step S21) contains a known antibacterial active structure of the "β-lactam" antibiotic drug type, then the ring information of the secondary metabolite molecule structure is further calculated, and the ring information of all atoms is obtained. Then, the atom number information of the structure is calculated, and the atom number of the nitrogen atom in the structure is obtained. Then, based on the ring information of all atoms, it is checked whether the nitrogen atom belongs to multiple rings. If so, the secondary metabolite molecule structure is marked as the hit structure, and the alternative antibiotic drug type is marked as "β-lactam".

[0020] The calculation steps for step S22) in the further implementation scheme are as follows:

[0021] S221) Calculate the ring information of the molecular structure of the secondary metabolite and obtain the ring information of all atoms. If the number of atoms in a certain ring is greater than or equal to 14, it is considered to have a macrocyclic structure.

[0022] S222) If the calculation result shows that the molecular structure of the secondary metabolite contains a macrocyclic structure, then the skeleton structure of the molecular structure is further calculated, and it is calculated whether the skeleton structure contains a known antibacterial structure of "macrolide". If so, the molecular structure of the secondary metabolite is marked as the hit structure, and the type of antibiotic that can be replaced is marked as "macrolide".

[0023] S223) Further calculate whether the above skeleton structure contains a known antibacterial structure of "macrolide". If so, mark the molecular structure of the secondary metabolite as the hit structure and mark the type of antibiotic that can be replaced as "macrolide".

[0024] In a further implementation scheme, the calculation steps for step S23) are as follows:

[0025] Calculate the structural shape of the secondary metabolite molecule and determine whether the structural shape contains a "tetracycline" antibacterial active structure. If so, label the secondary metabolite molecule as the hit structure and label the alternative antibiotic drug type as "tetracycline".

[0026] The calculation steps for step S24) in the further implementation scheme are as follows:

[0027] If the biosynthetic pathway type in the secondary metabolite molecular structure data is "non-ribosomal peptide", then it is further calculated whether the secondary metabolite molecular structure contains an antibacterial structure of "glycopeptide". If so, the secondary metabolite molecular structure is marked as the hit structure, and the type of alternative antibiotic is marked as "glycopeptide".

[0028] A system for rapidly screening alternative secondary metabolites of antibiotic resistance includes:

[0029] The input module is used to input and read preset known antibacterial activity structure data and molecular structure data of secondary metabolites to be screened;

[0030] A screening calculation module is used to calculate whether each secondary metabolite molecule to be screened has a known antibacterial activity structural feature.

[0031] The output module is used to output the structure of antibiotic resistance alternative secondary metabolites and the corresponding antibiotic drug types that can be substituted.

[0032] In addition, the present invention also provides a storage medium storing one or more programs including execution instructions, which can be read and executed by electronic devices (including but not limited to computers, servers, or network devices) to perform the method described above for rapidly screening alternative secondary metabolites of antibiotic resistance.

[0033] The present invention also provides an electronic device comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method described above for rapid screening of alternative secondary metabolites for antibiotic resistance.

[0034] The present invention also provides a computer program product comprising a computer program stored on a storage medium, the computer program comprising program instructions that, when executed by a computer, enable the computer to perform the method described above for rapidly screening alternative secondary metabolites of antibiotic resistance.

[0035] Compared with the prior art, the beneficial technical effects of the present invention are as follows:

[0036] This invention utilizes chemical molecular structure data processing technology to identify whether the chemical structure of the secondary metabolites to be screened contains pre-defined known antibacterial activity structural features. This ensures that the selected secondary metabolites not only have the ability to bind to known antibiotic drug targets but also possess novel side chains or substituents to avoid antibiotic resistance. This achieves rapid and efficient screening of antibiotic resistance alternative secondary metabolites. It not only eliminates the need for molecular docking calculations using specific antibiotic target protein receptors, saving significant computational resources and time, but is also applicable to various antibiotic drug types, covering most known antibacterial activity mechanisms. The output results can be directly used as a reference and basis for the design of natural antibiotic drugs. Therefore, this invention can be used for high-throughput screening of natural antibiotic drugs, and has significant significance and application value for alleviating antibiotic resistance research. Attached Figure Description

[0037] Figure 1 The present invention provides a flowchart of a method for rapidly screening alternative secondary metabolites for antibiotic resistance.

[0038] Figure 2 This invention provides a system structure diagram for rapidly screening alternative secondary metabolites for antibiotic resistance. Detailed Implementation

[0039] The technical solution of the present invention will be further described in detail and completely below with reference to the embodiments and accompanying drawings.

[0040] Example

[0041] Assuming that the known antibacterial activity structure data preset in this embodiment are as shown in Table 1:

[0042] Table 1. Pre-defined known antibacterial activity structure data

[0043]

[0044] Assume the molecular structure data of the secondary metabolites to be screened in this embodiment are as shown in Table 2:

[0045] Table 2. Molecular structure data of the secondary metabolites to be screened.

[0046]

[0047]

[0048]

[0049] Please see Figure 1 As shown, the steps for antibiotic resistance substitution screening of the above-mentioned secondary metabolites using the method described in this invention are as follows:

[0050] S1) Use the "MolFromSmiles" function of the RDKit tool to read the known antimicrobial activity structure data shown in Table 1 and the molecular structure data of the secondary metabolites to be screened shown in Table 2. As shown in Table 1, the known antimicrobial activity structure data read includes known antimicrobial activity structures (including SMILES data and structural diagrams) and the corresponding antibiotic drug types. As shown in Table 2, the molecular structure data of the secondary metabolites to be screened read includes the molecular structure of the secondary metabolites (including SMILES data and structural diagrams) and the corresponding biosynthetic pathway types.

[0051] S2) Calculate whether each secondary metabolite molecule to be screened possesses known antibacterial activity structural features. The calculation for each secondary metabolite molecule to be screened shall be performed in the following order:

[0052] S21) Use the "HasSubstructMatch" function of the RDKit tool to calculate whether the molecular structure of the secondary metabolite to be screened contains a known antibacterial active structure of the preset antibiotic drug types "aminoglycosides", "oxazolidinones", "quinolones", "chloramphenicols", and "β-lactams". If the calculation result contains a known antibacterial active structure of the antibiotic drug types "aminoglycosides", "oxazolidinones", "quinolones", and "chloramphenicols", then mark the molecular structure of the secondary metabolite as the hit structure and mark the alternative antibiotic drug types as "aminoglycosides", "oxazolidinones", "quinolones", and "chloramphenicols", respectively.

[0053] If the calculation result contains a known antibacterial active structure of a "β-lactam" antibiotic drug type, then the "GetRingInfo" function of the RDKit tool is used to calculate the ring information of the secondary metabolite molecule structure, and the "AtomRings" function of the RDKit tool is used to obtain the ring information of all atoms. Then, the "GetSubstructMatches" function of the RDKit tool is used to calculate the atom number information of the contained structure, and the "GetAtomWithIdx" function of the RDKit tool is used to obtain the atom number of the nitrogen atom in the contained structure. Then, based on the ring information of all atoms, it is checked whether the nitrogen atom belongs to multiple rings. If so, the secondary metabolite molecule structure is marked as a hit structure, and the alternative antibiotic drug type is marked as "β-lactam".

[0054] S22) Calculate whether the molecular structure of the secondary metabolite to be screened contains a known antibacterial active structure of a pre-defined "macrolide" or "macrolide" antibiotic drug type; the specific calculation is as follows:

[0055] S221) Use the "GetRingInfo" function of the RDKit tool to calculate the ring information of the secondary metabolite molecule structure, and use the "AtomRings" function of the RDKit tool to obtain the ring information of all atoms. If the number of atoms in a ring is greater than or equal to 14, it is considered to have a macrocyclic structure.

[0056] S222) If the calculation result shows that the secondary metabolite molecule contains a macrocyclic structure, then the "GetScaffoldForMol" function of the RDKit tool is used to calculate the skeleton structure of the molecule and to calculate whether the skeleton structure contains a known antibacterial structure of "macrolide". If so, the secondary metabolite molecule is marked as the hit structure and the type of alternative antibiotic is marked as "macrolide".

[0057] S223) Further calculate whether the above skeleton structure contains a known antibacterial structure of "macrolide". If so, mark the molecular structure of the secondary metabolite as the hit structure and mark the type of antibiotic that can be replaced as "macrolide".

[0058] S23) Use the “MakeScaffoldGeneric” function of the RDKit tool to calculate the structural shape of the secondary metabolite molecule and calculate whether the structural shape contains a “tetracycline” antibacterial activity structure. If so, mark the secondary metabolite molecule as the hit structure and mark the alternative antibiotic drug type as “tetracycline”.

[0059] S24) If the biosynthetic pathway type in the secondary metabolite molecular structure data is "non-ribosomal peptide", then the "HasSubstructMatch" function of the RDKit tool is used to calculate whether the secondary metabolite molecular structure contains a "glycopeptide" antibacterial active structure. If so, the secondary metabolite molecular structure is marked as a hit structure and the type of alternative antibiotic is marked as "glycopeptide".

[0060] S3) Output the structure of alternative secondary metabolites for antibiotic resistance and the corresponding types of antibiotic drugs that can be substituted.

[0061] For example, in this embodiment,

[0062] Calculations revealed that: the molecular structure of the secondary metabolite to be screened, number 1, contains a known antibacterial structure of "aminoglycosides"; the molecular structure of the secondary metabolite to be screened, number 2, contains a known antibacterial structure of "oxazolidinones"; the molecular structure of the secondary metabolite to be screened, number 3, contains a known antibacterial structure of "quinolones"; and the molecular structure of the secondary metabolite to be screened, number 4, contains a known antibacterial structure of "chloramphenicol". Therefore, the molecular structures of the secondary metabolites to be screened, numbers 1, 2, 3, and 4, are marked as the hit structures, and the types of antibiotics that can be replaced are respectively labeled as "aminoglycosides", "oxazolidinones", "quinolones", and "chloramphenicol".

[0063] Because calculations revealed that the molecular structure of the secondary metabolite to be screened, number 5, contains a known antibacterial active structure of the "β-lactam" antibiotic drug type, and its ring information was obtained through calculation as [(4,16,17,21,22),(18,20,21,17)], the atom numbering information of the contained structure is (19,18,17,21,20), and the atom number of the nitrogen atom in the contained structure is 17. According to the ring information, this nitrogen atom belongs to multiple rings, indicating that the molecular structure of this secondary metabolite contains both a lactam structure and a fused ring structure. Therefore, the molecular structure of the secondary metabolite to be screened, number 5, is marked as the hit structure, and the type of antibiotic drug that can be replaced is marked as "β-lactam".

[0064] The ring information of the molecular structure of the secondary metabolite to be screened, number 6, was calculated as follows:

[0065] [(2,45,44,40,38,37,36,35,34,33,31,18,5,4),(13,14,15,16,17,12),(21,22,25,27,29,20)], where the first ring has 14 atoms, therefore it is considered to have a macrocyclic structure; and the calculated framework structure is:

[0066]

[0067] O=C(CCc1ccccc1)NC1CCC(=O)OCCC=CC=CCCC1OC1CCCCO1; This skeleton structure contains a known antibacterial structure of "macrolide". Therefore, the molecular structure of the secondary metabolite to be screened in sequence 6 is marked as the hit structure, and the type of alternative antibiotic is marked as "macrolide".

[0068] The ring information of the molecular structure of the secondary metabolite to be screened (serial number 7) was also calculated as follows:

[0069] [(4,25,24,22,16,15,13,11,10,9,8,7,6,5),(8,9,29,30,37,7),(31,32,34,36,37,30)]

[0070] The first ring also has 14 atoms, therefore it is also considered to have a macrocyclic structure; and the calculated framework structure is as follows:

[0071]

[0072] O=C1CCC2=CC(SCCCNC(=O)CN1)c1ccccc1N2; This skeletal structure contains a known antibacterial structure of "macrolides", therefore the molecular structure of the secondary metabolite to be screened in sequence 7 is marked as the hit structure, and the type of alternative antibiotic is marked as "macrolides".

[0073] Furthermore, the calculated molecular structure of the secondary metabolite to be screened, number 8, is as follows:

[0074]

[0075] CCC1(C)CCC2C(C)C3C(C)C4C(C)CCCC4C(C)C3C(C)C2C1CC1CC(C)C(CC2CC(C)C(C)C(C)C2)C(C(C)C)C1; This structure contains a "tetracycline" antibacterial activity structure, therefore the molecular structure of the secondary metabolite to be screened in sequence 8 is marked as the hit structure, and the type of alternative antibiotic is marked as "tetracycline";

[0076] Furthermore, since the biosynthetic pathway type of the secondary metabolite molecular structure 9 to be screened is "non-ribosomal peptide", and it is calculated that the structure contains a known antibacterial structure of "glycopeptide", the secondary metabolite molecular structure to be screened is marked as the hit structure, and the type of antibiotic that can be replaced is marked as "glycopeptide".

[0077] Although the biosynthetic pathway type of the secondary metabolite molecular structure to be screened in sequence 10 in this embodiment is also "non-ribosomal peptide", it is calculated that this structure does not contain the known antibacterial activity structure of "glycopeptide". Therefore, this secondary metabolite molecular structure is ignored, that is, this structure is not marked as the hit structure.

[0078] The output results of the screening of the secondary metabolite molecular structures shown in Table 2 of this embodiment after being screened by the method described in this invention are as follows:

[0079]

[0080]

[0081] It should be noted that the above embodiments are specifically designed to illustrate the present invention. Due to the wide chemical sphere of microbial secondary metabolites, the actual screening success rate is much lower than that of this embodiment. Furthermore, although each secondary metabolite in this embodiment replaces only one type of antibiotic, it is possible that the secondary metabolites actually screened may simultaneously possess known antibacterial activity structures that can replace two or more types of antibiotics. Therefore, it is possible to screen for secondary metabolites that can simultaneously replace multiple types of antibiotics.

[0082] As described above, this invention utilizes chemical molecular structure data processing technology to identify whether the chemical structure of the secondary metabolites to be screened contains pre-defined known antibacterial activity structural features. This ensures that the selected secondary metabolites not only have the ability to bind to known antibiotic drug targets but also possess novel side chains or substituent groups to avoid antibiotic resistance. This achieves rapid and efficient screening of antibiotic resistance alternative secondary metabolites. It not only eliminates the need for molecular docking calculations using specific antibiotic target protein receptors, saving significant computational resources and time, but is also applicable to various antibiotic drug types, covering most known antibacterial activity mechanisms. The output results can be directly used as a reference and basis for the design of natural antibiotic drugs. Therefore, this invention can be used for high-throughput screening of natural antibiotic drugs, and has significant implications and application value for alleviating antibiotic resistance research.

[0083] In addition, such as Figure 2 As shown, the present invention provides a system for rapidly screening alternative secondary metabolites of antibiotic resistance, comprising:

[0084] The input module is used to input and read preset known antibacterial activity structure data and molecular structure data of secondary metabolites to be screened;

[0085] A screening calculation module is used to calculate whether each secondary metabolite molecule to be screened has a known antibacterial activity structural feature.

[0086] The output module is used to output the structure of antibiotic resistance alternative secondary metabolites and the corresponding antibiotic drug types that can be substituted.

[0087] The aforementioned program modules generally include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types.

[0088] The present invention also provides a storage medium storing one or more programs including execution instructions, which can be read and executed by electronic devices (including but not limited to computers, servers, or network devices) to perform the method described above for rapidly screening alternative secondary metabolites of antibiotic resistance.

[0089] The present invention also provides an electronic device comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method described above for rapid screening of alternative secondary metabolites for antibiotic resistance.

[0090] The memory may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function. The data storage area may store data created during system use for rapid screening of alternative secondary metabolites of antibiotic resistance. Furthermore, the memory may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the system for rapid screening of alternative secondary metabolites of antibiotic resistance via a network. The network includes, but is not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0091] The electronic device can exist in various forms, including but not limited to:

[0092] (1) Mobile communication devices: These devices are characterized by having mobile communication functions and are primarily designed to provide voice and data communication. These terminals include: smartphones (such as iPhones), multimedia phones, feature phones, and low-end phones, etc.

[0093] (2) Ultra-mobile personal computer devices: These devices fall under the category of personal computers, have computing and processing functions, and generally also have mobile Internet access capabilities. These terminals include: PDA, MID and UMPC devices, such as iPad;

[0094] (3) Portable entertainment devices: These devices can display and play multimedia content. Such devices include: audio and video players (e.g., iPod), handheld game consoles, e-books, as well as smart toys and portable car navigation devices;

[0095] (4) Server: A device that provides computing services. The components of a server include a processor, hard disk, memory, system bus, etc. Servers are similar to general computer architectures, but because they need to provide highly reliable services, they have higher requirements in terms of processing power, stability, reliability, security, scalability, and manageability.

[0096] (5) Other electronic devices with data interaction functions.

[0097] The present invention also provides a computer program product comprising a computer program stored on a storage medium, the computer program including program instructions that, when executed by a computer, enable the computer to perform the method described above for rapidly screening alternative secondary metabolites of antibiotic resistance. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform the methods described in various embodiments or certain portions of the embodiments.

[0098] Finally, it should be pointed out that the above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. In the absence of conflict, the embodiments and features in the embodiments of this application can be combined with each other. Furthermore, for the foregoing method embodiments, for the sake of simplicity, they are all described as a combination of a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

Claims

1. A method for rapidly screening alternative secondary metabolites of antibiotic resistance, characterized in that, The method includes the following steps: S1) Read the preset known antibacterial activity structure data and the molecular structure data of the secondary metabolites to be screened; S2) Calculate whether each secondary metabolite molecule structure to be screened has a known antibacterial activity structure feature. The known antibacterial activity structure feature includes at least one known antibacterial activity structure of an antibiotic drug type selected from "aminoglycosides", "oxazolidinones", "quinolones", "chloramphenicol", "β-lactams", "macrolides", "tetracyclines", and "glycopeptides". If the calculation result contains a known antibacterial activity structure of the "β-lactam" antibiotic drug type, then further calculate the ring information of the secondary metabolite molecule structure and obtain the ring information of all atoms. Then calculate the atom number information of the structure and obtain the atom number of the nitrogen atom in the structure. Then check whether the nitrogen atom belongs to multiple rings according to the ring information of all atoms. If so, then mark the secondary metabolite molecule structure as the hit structure and mark the alternative antibiotic drug type as "β-lactam". S3) Output the structure of alternative secondary metabolites for antibiotic resistance and the corresponding types of antibiotic drugs that can be substituted.

2. The method according to claim 1, characterized in that: In step S1), the known antibacterial activity structure data read includes the known antibacterial activity structure and the corresponding antibiotic drug type, and the molecular structure data of the secondary metabolite to be screened read includes the molecular structure of the secondary metabolite and the corresponding biosynthetic pathway type.

3. The method according to claim 1, characterized in that, Step S2) Calculate whether each secondary metabolite molecule to be screened possesses known antibacterial activity structural features in the following order: S21) Calculate whether the molecular structure of the secondary metabolite to be screened contains a known antibacterial active structure of a preset antibiotic drug type such as "aminoglycoside", "oxazolidinone", "quinolone", "chloramphenicol" and "β-lactam". S22) Calculate whether the molecular structure of the secondary metabolite to be screened contains a known antibacterial active structure of the preset "macrolide" and "macrolide" antibiotic drug types; S23) Calculate whether the molecular structure of the secondary metabolite to be screened contains a known antibacterial active structure of a preset "tetracycline" antibiotic drug type; S24) Calculate whether the molecular structure of the secondary metabolite to be screened contains a known antibacterial active structure of a preset "glycopeptide" antibiotic drug type.

4. The method according to claim 3, characterized in that: If the calculation result of step S21) contains a known antibacterial active structure of antibiotic drug types such as "aminoglycosides", "oxazolidinones", "quinolones", and "chloramphenicol", then the molecular structure of the secondary metabolite is marked as the hit structure, and the alternative antibiotic drug types are marked as "aminoglycosides", "oxazolidinones", "quinolones", and "chloramphenicol", respectively.

5. The method according to claim 3, characterized in that, The specific calculation steps for step S22) are as follows: S221) Calculate the ring information of the molecular structure of the secondary metabolite and obtain the ring information of all atoms. If the number of atoms in a certain ring is greater than or equal to 14, it is considered to have a macrocyclic structure. S222) If the calculation result shows that the molecular structure of the secondary metabolite contains a macrocyclic structure, then the skeleton structure of the molecular structure is further calculated, and it is calculated whether the skeleton structure contains a known antibacterial structure of "macrolide". If so, the molecular structure of the secondary metabolite is marked as the hit structure, and the type of antibiotic that can be replaced is marked as "macrolide". S223) Further calculate whether the above skeleton structure contains a known antibacterial structure of "macrolide". If so, mark the molecular structure of the secondary metabolite as the hit structure and mark the type of antibiotic that can be replaced as "macrolide".

6. The method according to claim 3, characterized in that, The specific calculation steps for step S23) are as follows: Calculate the structural shape of the secondary metabolite molecule and determine whether the structural shape contains a "tetracycline" antibacterial active structure. If so, label the secondary metabolite molecule as the hit structure and label the alternative antibiotic drug type as "tetracycline".

7. The method according to claim 3, characterized in that, The specific calculation steps for step S24) are as follows: If the biosynthetic pathway type in the secondary metabolite molecular structure data is "non-ribosomal peptide", then it is further calculated whether the secondary metabolite molecular structure contains an antibacterial structure of "glycopeptide". If so, the secondary metabolite molecular structure is marked as the hit structure, and the type of alternative antibiotic is marked as "glycopeptide".

8. A system for rapidly screening antibiotic resistance alternative secondary metabolites for performing the method of claim 1, characterized in that, The system includes: The input module is used to input and read preset known antibacterial activity structure data and molecular structure data of secondary metabolites to be screened; A screening calculation module is used to calculate whether each secondary metabolite molecule to be screened has a known antibacterial activity structural feature. The output module is used to output the structure of antibiotic resistance alternative secondary metabolites and the corresponding antibiotic drug types that can be substituted.

9. A storage medium having a computer program stored thereon, characterized in that: When executed by a processor, the program can implement the method described in any one of claims 1 to 7.

10. An electronic device comprising: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor; characterized in that: the at least one processor is capable of performing the method according to any one of claims 1 to 7.

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