Quantum chip simulation method, apparatus, device, and medium for drug molecules

Abstract

Embodiments of the present application disclose a quantum chip simulation method, device, equipment and medium for a drug molecule, which comprises determining an active region and an inactive region of a conformation of the drug molecule, the conformation of the drug molecule referring to different three-dimensional spatial arrangements of the drug molecule formed through single bond rotation or skeleton distortion, the active region referring to a structure in the conformation of the drug molecule that directly participates in a chemical reaction or affects a property of the drug; replacing multi-electron atoms in the active region with hydrogen atoms and simplifying structures in the inactive region to obtain an optimized molecular structure; and simulating the molecular structure through a high-efficiency pseudo quantum circuit to determine an energy of the drug molecule, the high-efficiency pseudo quantum circuit being a quantum circuit designed for optimizing performance on a specific quantum chip and reducing noise influence by utilizing native gate operations and connectivity of the quantum chip. According to the embodiments of the present application, simulation of the drug molecule can be realized while chemical precision is maintained.

Description

Technical Field

[0001] This invention relates to the field of chemical drug synthesis technology, and in particular to a quantum chip simulation method, apparatus, device, and medium for drug molecules. Background Technology

[0002] Chemical drug synthesis (hereinafter referred to as drug synthesis) is a very important and widely used source of drugs for modern drug research and development. Creating novel drugs by constructing highly efficient molecules that do not exist in nature through synthetic chemistry enables precision medicine; stereochemical control of the drug synthesis process can solve drug resistance problems, enable rapid response to infectious diseases, and combat the threat of superbugs; standardizing drug synthesis processes can overcome geographical limitations, reduce drug costs, and increase production capacity.

[0003] 一 Synthesizing drug molecules typically requires designing synthetic methods and conducting theoretical simulations. However, theoretical simulations present a significant challenge in achieving exact solutions due to the exponential growth of dimensionality with system size. Quantum computing is considered a promising method to overcome this exponential wall, with the Variational Quantum Eigensolver (VQE) algorithm proving to be the most promising quantum algorithm for simulating the ground-state energy of chemical molecules in the current era of noisy intermediate-scale quantum (NISQ). However, even a true VQE cannot overcome the limitations of qubit count and parameter limitations.

[0004] Therefore, how to achieve drug molecule simulation while maintaining chemical precision is a technical problem that urgently needs to be solved. Summary of the Invention

[0005] This application provides a quantum chip simulation method, apparatus, device, and medium for drug molecules, which can simulate drug molecules while maintaining chemical accuracy.

[0006] The first aspect of this application provides a quantum chip simulation method for drug molecules, including:

[0007] The active and inactive regions of a drug molecule conformation are determined. The drug molecule conformation refers to the different three-dimensional spatial arrangements of a drug molecule formed by single bond rotation or skeleton twisting. The active region refers to the structure in the drug molecule conformation that directly participates in chemical reactions or affects the properties of the drug.

[0008] The multi-electron atoms in the active region are replaced with hydrogen atoms, and the structure in the inactive region is simplified to obtain the optimized molecular structure.

[0009] The molecular structure is simulated by an efficient simulated quantum circuit to determine the energy of the drug molecule. The efficient simulated quantum circuit is a quantum circuit designed to optimize performance on a specific quantum chip, which reduces the impact of noise by utilizing the native gate operation and connectivity of the quantum chip.

[0010] Optionally, simplifying the structure in the inactive region to obtain the optimized molecular structure includes:

[0011] The structure in the inactive region is simplified according to the inactive region simplification method to obtain the optimized molecular structure. The inactive region simplification method includes at least one of the following: substituent simplification, cyclic structure simplification, and removal of unimportant parts.

[0012] Optionally, before determining the active and inactive regions of the drug molecule conformation, the method further includes:

[0013] One or more initial drug molecule conformations are generated based on the structural information of the drug molecule;

[0014] The initial drug molecule conformation is expanded to obtain multiple candidate drug molecule conformations;

[0015] Optimize the molecular conformations of several of the candidate drugs.

[0016] Optionally, the expansion of the initial drug molecule conformation to obtain multiple candidate drug molecule conformations includes:

[0017] Based on the conformation search algorithm, a conformation search is performed starting from the initial drug molecule conformation to obtain multiple candidate drug molecule conformations. The conformation search algorithm includes at least one of the following: Monte Carlo method, molecular dynamics simulation method, and genetic algorithm.

[0018] Optionally, before expanding the initial drug molecule conformation to obtain multiple candidate drug molecule conformations, the method further includes:

[0019] An energy minimization algorithm is applied to each initial drug molecule conformation to determine the local energy minimum of the initial drug molecule conformation, thereby obtaining a stable initial drug molecule conformation. The energy minimization algorithm includes at least one of the following: steepest descent method, conjugate gradient method, Newton's method, and quasi-Newton's method.

[0020] Optionally, before optimizing the conformations of the plurality of candidate drug molecules, the method further includes:

[0021] Determine the minimum energy of multiple candidate drug molecule conformations;

[0022] Calculate the energy difference of each candidate drug molecule conformation relative to the minimum value;

[0023] The Boltzmann factor for each candidate drug molecule conformation is calculated based on the difference.

[0024] Calculate the partition function based on the Boltzmann factor;

[0025] The Boltzmann distribution of each candidate drug molecule conformation is calculated based on the Boltzmann factor and the partition function.

[0026] The candidate drug molecule conformations are screened based on the Boltzmann distribution.

[0027] Optionally, the simulation of the molecular structure by efficiently simulating a quantum circuit includes:

[0028] An efficient pseudo-quantum circuit is constructed by using a single-qubit rotating logic gate and a dual-gate supported by a quantum chip. The efficient pseudo-quantum circuit is used to evolve a qubit from an initial state to a target state.

[0029] The rotation parameters of the single-qubit rotating logic gate are optimized by constructing a loss function using the Hamiltonian corresponding to the target state and the molecular structure, so that the target state is the ground state of the drug molecule.

[0030] A second aspect of this application provides a quantum chip simulation of drug molecules, including:

[0031] An active region determination unit is used to determine the active and inactive regions of a drug molecule conformation, wherein the drug molecule conformation refers to the different three-dimensional spatial arrangements formed by the rotation of single bonds or the twisting of the skeleton of the drug molecule, and the active region refers to the structure in the drug molecule conformation that directly participates in chemical reactions or affects the properties of the drug.

[0032] The structure optimization unit is used to replace multi-electron atoms in the active region with hydrogen atoms and to simplify the structure in the inactive region to obtain an optimized molecular structure.

[0033] A molecular simulation unit is used to simulate the molecular structure by means of an efficient simulated quantum circuit to determine the energy of the drug molecule. The efficient simulated quantum circuit is a quantum circuit designed to optimize performance on a specific quantum chip and reduces the impact of noise by utilizing the native gate operation and connectivity of the quantum chip.

[0034] A third aspect of this application provides an electronic device, including: a processor and a memory;

[0035] The processor is connected to a memory, wherein the memory is used to store computer programs and the processor is used to invoke the computer programs to execute the methods as described in the first aspect of the embodiments of this application.

[0036] A fourth aspect of this application provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, perform the method as described in the first aspect of this application.

[0037] The quantum chip simulation method, apparatus, equipment, and medium for drug molecules provided in this application determine the active and inactive regions of the drug molecule conformation. The drug molecule conformation refers to different three-dimensional spatial arrangements formed by single bond rotation or skeletal twisting of the drug molecule. The active region refers to the structure in the drug molecule conformation that directly participates in chemical reactions or affects the properties of the drug. The optimized molecular structure is obtained by replacing multi-electron atoms in the active region with hydrogen atoms and simplifying the structure in the inactive region. The molecular structure is then simulated using a highly efficient quantum circuit to determine the energy of the drug molecule. This highly efficient quantum circuit is designed to optimize performance on a specific quantum chip and reduces noise by utilizing the native gate operations and connectivity of the quantum chip.

[0038] As can be seen in the embodiments of this application, after optimizing the active and inactive regions of the drug molecule conformation respectively, the simulation is carried out by efficiently simulating quantum circuits, thereby overcoming the limitations of the number of qubits and parameters and overcoming the exponential wall, and realizing the simulation of drug molecules while maintaining chemical accuracy. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 An example system block diagram of a quantum chip simulation method for drug molecules provided in one embodiment of this application is shown;

[0041] Figure 2 A flowchart illustrating a quantum chip simulation method for drug molecules provided in one embodiment of this application is shown.

[0042] Figure 3 A flowchart illustrating a quantum chip simulation method for drug molecules provided in another embodiment of this application is shown.

[0043] Figure 4 A flowchart illustrating a quantum chip simulation method for drug molecules provided in yet another embodiment of this application is shown.

[0044] Figure 5 A flowchart illustrating a quantum chip simulation method for drug molecules provided in yet another embodiment of this application is shown.

[0045] Figure 6 A schematic flowchart of a drug molecule conformation screening method provided in one embodiment of this application is shown;

[0046] Figure 7 A flowchart illustrating a molecular structure simulation method provided in one embodiment of this application is shown;

[0047] Figure 8 This paper shows a schematic diagram of the structure of a quantum chip simulation device for drug molecules provided in one embodiment of this application;

[0048] Figure 9 A schematic diagram of the structure of a computer device provided in one embodiment of this application is shown. Detailed Implementation

[0049] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0050] Classical computers use transistors to encode information in binary data, such as bits, where each bit can represent a value of 1 or 0. These 1s and 0s act as switches to drive the functions of a classical computer. If there are n bits of data, there are 2^n possible classical states, and one state is represented at a time.

[0051] Quantum computers use quantum processors that operate on data represented by qubits, also known as quantum bits. A single qubit can represent the classical binary states "0" or "1", or a superposition of "0" and "1". Because it can represent a superposition of "0" and "1", a qubit can represent both "0" and "1" states simultaneously. For example, if there are n bits of data, then 2^n qubits can represent n bits of data. nA quantum state can be represented simultaneously. Furthermore, qubits in a superposition can be correlated with each other, a phenomenon known as entanglement, where the state of one qubit (whether 1, 0, or both) depends on the state of another qubit, and more information can be encoded within two entangled qubits. Based on the principles of superposition and entanglement, qubits enable quantum computers to perform functions that might be relatively complex and time-consuming for classical computers.

[0052] Please refer to Figure 1 This illustrates an example system block diagram of a quantum chip simulation method for drug molecules provided in one embodiment of this application. System 100 may be a hybrid computing system comprising a combination of one or more quantum computers, quantum systems, and / or classical computers. Figure 1 In the example shown, system 100 may include a quantum system 110 and a classical computer 120. In one implementation, the quantum system 110 and the classical computer 120 may be configured to communicate via one or more wired and / or wireless connections (e.g., wireless networks). The quantum system 110 may include a quantum chipset consisting of one or more quantum chips, comprising various hardware components for processing data encoded in qubits. The quantum chipset may be a quantum computing core surrounded by infrastructure to protect the quantum chips from electromagnetic noise sources, mechanical vibration sources, heat sources, and other noise sources that can degrade the performance of the quantum chips. The classical computer 120 may be electronically integrated with the quantum system 110 via any suitable wired and / or wireless electronic connection.

[0053] exist Figure 1 In the example shown, quantum system 110 can be any suitable set of components capable of performing quantum operations on a physical system. Quantum operations, such as quantum gate operations, manipulate the quantum states of qubits to evolve and / or become entangled. Figure 1 In the illustrated example embodiment, the quantum system 110 may include a measurement and control unit 111, an interface 112, and a quantum chip 113. In some embodiments, all or part of each of the measurement and control unit 111, interface 112, and quantum chip 113 may be located in a cryogenic environment to facilitate the performance of quantum operations. The quantum chip 113 may be any hardware capable of processing information using quantum states. This hardware may include multiple qubits and means for coupling or entanglement of the qubits to process information using quantum states. Qubits may include, but are not limited to, charge qubits, flux qubits, phase qubits, spin qubits, and ion qubits. The quantum chip may include a set of quantum logic gates configured to perform quantum logic operations on the qubits stored in a quantum register. The quantum gates may include one or more single-qubit gates, two-qubit gates, and / or other multi-qubit gates.

[0054] The measurement and control unit 111 can be any combination of digital computing devices capable of performing quantum computing (e.g., executing quantum circuits) in conjunction with interface 112. This digital computing device may include a digital processor and memory for storing and executing quantum instructions using interface 112. The digital computing device may also include a communication protocol device for receiving instructions and sending the results of the performed quantum computing to a classical computer. Additionally, the digital computing device may include a communication interface having interface 112. In one embodiment, the measurement and control unit 111 may be configured to receive classical instructions (e.g., from classical computer 120) and convert these classical instructions into measurement and control instructions for interface 112. The measurement and control instructions provided by the measurement and control unit 111 to interface 112 may be, for example, digital signals indicating which quantum gates in a quantum gate array need to be applied to the qubits to perform a specific function. Interface 112 may be configured to convert these digital signals into analog signals (e.g., analog pulses of microwave pulses), which can be used to apply quantum gates to the qubits to manipulate the interactions between the qubits.

[0055] Interface 112 may be a classical-quantum interface, comprising a combination of devices capable of receiving instructions from the integrated measurement and control unit 111 and converting those instructions into a means for implementing quantum operations. In one embodiment, interface 112 may convert instructions from the integrated measurement and control unit 111 into drive signals capable of driving or manipulating qubits, and / or applying quantum gates to qubits. Additionally, interface 112 may be configured to convert signals received from the quantum chip 113 into digital signals capable of being processed and transmitted by the integrated measurement and control unit 111. Devices included in interface 112 may include, but are not limited to, digital-to-analog converters, analog-to-digital converters, waveform generators, attenuators, amplifiers, optical fibers, lasers, and filters. Interface 112 may further include circuitry configured to measure multiple qubits after the application of quantum gates, wherein the measurements may produce results represented in classical bits. Each measurement performed by interface 112 may be read out to a device connected to the quantum system 110, such as a classical computer 120. The multiple measurement results provided by interface 112 may represent probabilistic results.

[0056] The classical computer 120 can include hardware components such as a processor and storage devices (e.g., including memory devices and classical registers) for processing data encoded in classical bits. In one embodiment, the classical computer 120 can be configured to provide the quantum system 110 with various control signals, instructions, and data encoded in classical bits. Further, quantum states measured by the quantum system 110 can be read out by the classical computer 120, and the classical computer 120 can store the measured quantum states as classical bits in classical registers. In one embodiment, the classical computer 120 can be any suitable combination of computer-executable hardware and / or computer-executable software capable of executing the preparation module 121 to perform quantum computation using data stored in the data storage module 122 as part of the construction and computation. The data storage module 122 can be a repository for data to be analyzed using quantum computing algorithms and the results of that analysis. The preparation module 121 can be a program or module capable of preparing classical data from the data storage module 122 as part of a quantum circuit implementation. Preparation module 121 can be instantiated as part of a larger algorithm, such as an application programming interface (API) function call, or by resolving hybrid classical-quantum computing into aspects of quantum and classical computing. For example, preparation module 121 can generate instructions for creating quantum circuits using quantum gates. In an embodiment, such instructions can be stored by the measurement and control unit 111 and can be instantiated by components of interface 112 to execute, enabling quantum operations of quantum gates to be performed on quantum chip 113.

[0057] The classic computer 120 may be a laptop computer, desktop computer, vehicle-integrated computer, smart mobile device, tablet device, and / or any other suitable classic computing device. Additionally or alternatively, the classic computer 120 may also operate as part of a cloud computing service model, such as Software as a Service (SaaS), Platform as a Service (PaaS), or Infrastructure as a Service (IaaS). The classic computer 120 may also reside in a cloud computing deployment model, such as a private cloud, community cloud, public cloud, or hybrid cloud.

[0058] Drug synthesis is a crucial source of drugs, and it demands the following: fewer synthetic steps, higher yields per step, and cheaper starting materials or catalysts. Therefore, constructing a synthetic route for a given drug molecule is critical. Constructing a synthetic route for a target drug molecule requires addressing core issues: the molecule's skeleton, introducing the necessary functional groups, and resolving stereochemical aspects of the target drug molecule. Simply designing a synthetic route and conducting experimental synthesis is a waste of resources. 一When synthesizing drug molecules, it is generally necessary to design synthetic methods and conduct theoretical simulations. Among these, theoretical simulations are challenging because the dimensionality increases exponentially with the size of the system, making it difficult to obtain accurate solutions.

[0059] In the chemical synthesis pathway, there are various classical methods and theories for ground-state energy. The Hartree-Fock method averages the interactions between electrons and can handle systems with tens of thousands of atoms, but due to the lack of electronic correlations, its predictions of many structures or properties are inaccurate or even erroneous. High-precision electronic correlation methods based on quantum mechanics, such as CCSD(T), consider the dynamic correlation of electrons and can handle strongly correlated systems, but the resulting exponentially huge computational cost limits its application to smaller molecules. The complete configuration interaction of the wavefunction is the expansion of all Slater determinants that can be generated under a given basis set; however, the number of Slater determinants depends exponentially on the number of electrons and orbitals, so FCI is only effective for small to medium-sized molecules. The largest CI calculation ever reportedly was performed on a state-of-the-art supercomputer with 22 electrons in 22 orbital activity spaces, corresponding to a staggering 497,634,306,624 (5 × 10^11) Slater determinants. The core bottleneck of this challenge is not necessarily just a lack of computational hardware, but rather our inability to effectively express the exponential growth of the wavefunction.

[0060] Quantum computing is considered a promising method to overcome the exponential wall of wave function theory. Among them, the variational quantum characteristic solution (VQE) algorithm has proven to be the most promising quantum algorithm for simulating the ground state energy of chemical molecules in the current era of noisy intermediate-scale quantum (NISQ). However, even true VQE cannot overcome the limitations of the number of qubits and parameters.

[0061] Therefore, how to simulate drug molecules while maintaining chemical accuracy is a pressing technical problem. To address this problem, this application provides a quantum chip simulation method, apparatus, device, and medium for drug molecules, which can simulate drug molecules while maintaining chemical accuracy.

[0062] Please refer to Figure 2 This document illustrates a flowchart of a quantum chip simulation method for drug molecules according to an embodiment of this application. This method can be applied to computer devices, which refer to electronic devices capable of data computation and processing. For example, the executing entity for each step could be... Figure 1 The method can include the following steps: (The example shown is a quantum computer or a classical computer.)

[0063] Step 201: Determine the active and inactive regions of the drug molecule conformation. The drug molecule conformation refers to the different three-dimensional spatial arrangements formed by the rotation of single bonds or the twisting of the skeleton of the drug molecule. The active region refers to the structure in the drug molecule conformation that directly participates in chemical reactions or affects the properties of the drug.

[0064] For example, the three-dimensional structure of the drug molecule and target complex can be analyzed to directly observe the binding sites and key interactions (such as hydrogen bonds, hydrophobic interactions, and electrostatic interactions), thereby determining the active and inactive regions of the drug molecule conformation; alternatively, the binding conformation of the active region can be predicted by calculating and simulating the binding mode of the drug molecule and the target protein, which is not limited here.

[0065] Among them, see Figure 3 Before step 201, i.e., before determining the active and inactive regions of the drug molecule conformation, the method further includes:

[0066] Step 204: Generate one or more initial drug molecule conformations based on the structural information of the drug molecule.

[0067] For example, open-source tools such as RDKit, Open Babel, and CORINA can be used to generate one or more initial drug molecule conformations based on the structural information of the drug molecule input by the user, such as the types of atoms and their connection methods. These tools employ different principles; for instance, RDKit generates low-energy conformations by rotating single bonds and supports diverse sampling, OpenBabel rapidly generates initial conformations based on force field parameters, and CORINA is a high-precision 2D-to-3D conversion tool suitable for complex molecules.

[0068] Step 205: Expand the initial drug molecule conformation to obtain multiple candidate drug molecule conformations.

[0069] Specifically, see Figure 4 In step 205, the initial drug molecule conformation is expanded to obtain multiple candidate drug molecule conformations, including:

[0070] Step 207: Perform conformation search starting from the initial drug molecule conformation according to the conformation search algorithm to obtain multiple candidate drug molecule conformations. The conformation search algorithm includes at least one of the following: Monte Carlo method, molecular dynamics simulation method, and genetic algorithm.

[0071] For example, to avoid getting trapped in local minima, the Monte Carlo method accepts high-energy conformations with a certain probability and gradually reduces the "temperature" parameter to achieve the search for multiple candidate drug molecule conformations; molecular dynamics simulation uses numerical integration of Newton's equations of motion to simulate the trajectory of drug molecules at a specific temperature, covering the dynamic conformation space; genetic algorithms generate new conformations through "population" evolution (selection, crossover, mutation), using conformation energy or pharmacophore matching degree as the evaluation criterion.

[0072] Among them, see Figure 5 Before step 205, i.e., before expanding the initial drug molecule conformation to obtain multiple candidate drug molecule conformations, the method further includes:

[0073] Step 208: Apply an energy minimization algorithm to each initial drug molecule conformation to determine the local energy minimum of the initial drug molecule conformation and obtain a stable initial drug molecule conformation. The energy minimization algorithm includes at least one of the following: steepest descent method, conjugate gradient method, Newton's method, and quasi-Newton's method.

[0074] Step 206: Optimize the conformation of multiple candidate drug molecules.

[0075] For example, the classic Gaussian method can be used to optimize the top N conformations with high Boltzmann ratios generated in the previous step to approximately optimal.

[0076] Among them, see Figure 6 Prior to step 206, and prior to optimizing the conformations of the plurality of candidate drug molecules, the method further includes:

[0077] Step 209: Determine the minimum energy of the plurality of candidate drug molecule conformations;

[0078] Step 210: Calculate the energy difference of each candidate drug molecule conformation relative to the minimum value;

[0079] Step 211: Calculate the Boltzmann factor for each of the candidate drug molecule conformations based on the difference;

[0080] Step 212: Calculate the partition function based on the Boltzmann factor;

[0081] Step 213: Calculate the Boltzmann distribution of each candidate drug molecule conformation based on the Boltzmann factor and the partition function;

[0082] Step 214: Screen multiple candidate drug molecule conformations based on the Boltzmann distribution.

[0083] For example, the energy of each conformation can be calculated using molecular mechanical force fields (such as MMFF94, GAFF) or quantum mechanical methods (such as DFT), and then the minimum energy value can be found; the energy difference can then be calculated. The formula for calculating the Boltzmann factor is as follows:

[0084]

[0085] Among them, B i Let ΔE be the Boltzmann factor of the conformation of the i-th candidate drug molecule. i Let k be the difference between the energy of the i-th candidate drug molecule conformation and the minimum value. B Where is the Boltzmann constant, and T is the temperature, which can be set to room temperature or the optimal activity temperature of the drug molecule.

[0086] The formula for calculating the partition function is:

[0087]

[0088] Where Z is the partition function and n is the number of candidate drug molecules.

[0089] The formula for calculating the Boltzmann distribution is:

[0090]

[0091] Among them, P i Let be the Boltzmann distribution of the conformation of the i-th candidate drug molecule.

[0092] For example, screening multiple candidate drug molecule conformations based on the Boltzmann distribution can be performed using either a threshold method or a cumulative probability method. The threshold method retains conformations with a probability higher than a certain threshold (e.g., >0.01, meaning a proportion exceeding 1%). The cumulative probability method sorts conformations from highest to lowest probability and retains those with a cumulative probability reaching a target value (e.g., 95%).

[0093] Step 202: Replace the multi-electron atoms in the active region with hydrogen atoms, and simplify the structure in the inactive region to obtain the optimized molecular structure.

[0094] Among these, atoms such as oxygen and nitrogen, which possess lone pairs of electrons, also belong to the chemically active region. A general principle for simplifying active regions is that for chemical reactions within the active region that do not significantly affect key sites, multi-electron atoms can be carefully replaced with simple hydrogen atoms, thus reducing resource consumption. This simplification scheme neither affects the crucial parts of the chemical reaction nor hinders resource reduction.

[0095] In step 202, namely, simplifying the structure in the inactive region to obtain the optimized molecular structure, the following steps are included:

[0096] The structure in the inactive region is simplified according to the inactive region simplification method to obtain the optimized molecular structure. The inactive region simplification method includes at least one of the following: substituent simplification, cyclic structure simplification, and removal of unimportant parts.

[0097] Substituent simplification involves replacing complex substituents with simpler groups that have similar electronic properties and steric effects. For example, replacing a large alkyl chain with a methyl group, or a chlorine atom with a fluorine atom, provided these substitutions do not significantly affect the key properties of the molecule. The advantages of substituent simplification are that it can greatly reduce molecular complexity and computational load. Furthermore, for complex substituents that are difficult to describe accurately, replacing them with simpler groups can improve the reliability of calculations. The disadvantage is that improper substitution can lead to significant deviations between calculated results and actual conditions. A thorough understanding of the molecule's properties is required to select appropriate substituents.

[0098] Ring structure simplification involves replacing complex ring structures with simpler or open-chain structures. For example, a six-membered ring can be simplified to a five-membered ring, or a fused ring system can be broken down into individual monocyclic structures. The advantages of ring structure simplification include reducing the geometric complexity of the molecule and decreasing the computational time and resources required. For some highly symmetrical ring structures, simplification can better utilize symmetry to reduce computational load. The disadvantage is that it may alter the electronic structure and spatial configuration of the molecule, thus affecting its properties. The impact of the simplified structure on the research objectives needs to be carefully evaluated.

[0099] Removing unimportant parts involves eliminating components in the molecule that have minimal impact on the research objective, such as long-chain alkyl groups or solvent molecules. The advantages are a significant reduction in the number of atoms and lower computational complexity. It allows focus on critical parts of the molecule, improving computational efficiency. The disadvantages are the need for accurate identification of unimportant parts; otherwise, important information may be lost. Removing parts may alter the overall properties of the molecule, requiring appropriate verification.

[0100] Step 203: Simulate the molecular structure using an efficient simulated quantum circuit to determine the energy of the drug molecule. The efficient simulated quantum circuit is a quantum circuit designed to optimize performance on a specific quantum chip, which reduces the impact of noise by utilizing the native gate operations and connectivity of the quantum chip.

[0101] Efficiently simulated quantum circuits are a commonly used method in quantum computing for simulating molecular energy states. This method typically involves the representation of quantum states, quantum gate operations, and the construction of Hamiltonians.

[0102] In drug synthesis, energy computation is a core tool for optimizing reaction pathways, predicting reaction feasibility, and understanding reaction mechanisms. By quantifying thermodynamic and kinetic parameters, energy computation significantly shortens the drug synthesis development cycle and reduces trial-and-error costs.

[0103] Specifically, see Figure 7 In step 203, namely, simulating the molecular structure by efficiently designing a quantum circuit, the following is included:

[0104] Step 2031: Construct an efficient simulated quantum circuit using a single-qubit rotating logic gate and a dual-gate supported by a quantum chip. The efficient simulated quantum circuit is used to evolve the qubit from the initial state to the target state.

[0105] Step 2032: Optimize the rotation parameters of the single-qubit rotating logic gate by constructing a loss function using the Hamiltonian corresponding to the target state and the molecular structure, so that the target state is the ground state of the drug molecule.

[0106] In this system, a single-qubit rotation logic gate can be one or more of the following: RX(θ) gate, RY(θ) gate, RZ(θ) gate, etc., where θ is the rotation parameter. The number of gates depends on the quantum chip used; for example, some quantum chips support CZ gates, while others support CNOT gates. To improve the expressive power of quantum circuits, a repeating multi-layer structure can also be used.

[0107] For example, a variational quantum algorithm can be used to construct the loss function to optimize the quantum state. The variational quantum algorithm is a quantum-classical hybrid variational method that, through optimization, progressively adjusts the parameter θ of the variational wavefunction to obtain the system's ground-state energy E. g :

[0108] E g =<ψ trial (θ)|H|ψ trial (θ)>,

[0109] E g The matrix corresponding to the system's Hamiltonian H is given by the variational wave function ψ. trial The expected value on (θ). Variational wave function ψ trial (θ) Constructing a circuit by design:

[0110] |ψ trial (θ)>=U(θ)|00…00>.

[0111] For example, for any system, its Hamiltonian can be written out. By performing a second quantization on the Hamiltonian, it can be expanded using multiple Pauli subterms (tensor products of Pauli operators) as a basis. For instance, the expanded Hamiltonian can take the form:

[0112] H = ∑ k w k P k ,

[0113] Where H is the Hamiltonian, It is a combination of the tensor products of four Pauli matrices, i.e., the Pauli observables in the embodiments of this application, where n is the number of qubits included in the original quantum circuit, and w k The weights for each basis.

[0114] The quantum chip simulation method for drug molecules provided in this application determines the active and inactive regions of the drug molecule conformation. The drug molecule conformation refers to different three-dimensional spatial arrangements formed by single bond rotation or skeleton twisting of the drug molecule. The active region refers to the structure in the drug molecule conformation that directly participates in chemical reactions or affects the properties of the drug. The method replaces multi-electron atoms in the active region with hydrogen atoms and simplifies the structure in the inactive region to obtain an optimized molecular structure. The method then simulates the molecular structure using an efficient simulated quantum circuit to determine the energy of the drug molecule. The efficient simulated quantum circuit is a quantum circuit designed to optimize performance on a specific quantum chip and reduces the impact of noise by utilizing the native gate operation and connectivity of the quantum chip.

[0115] As can be seen in the embodiments of this application, after optimizing the active and inactive regions of the drug molecule conformation respectively, the simulation is carried out by efficiently simulating quantum circuits, thereby overcoming the limitations of the number of qubits and parameters and overcoming the exponential wall, and realizing the simulation of drug molecules while maintaining chemical accuracy.

[0116] Figure 8 A schematic diagram of a quantum chip simulation device for drug molecules according to an embodiment of this application is shown. The device includes:

[0117] The active region determination unit 801 is used to determine the active and inactive regions of the drug molecule conformation. The drug molecule conformation refers to the different three-dimensional spatial arrangements formed by the drug molecule through single bond rotation or skeleton twisting. The active region refers to the structure in the drug molecule conformation that directly participates in chemical reactions or affects the properties of the drug.

[0118] The structure optimization unit 802 is used to replace the multi-electron atoms in the active region with hydrogen atoms and to simplify the structure in the inactive region to obtain an optimized molecular structure.

[0119] The molecular simulation unit 803 is used to simulate the molecular structure by means of an efficient simulated quantum circuit to determine the energy of the drug molecule. The efficient simulated quantum circuit is a quantum circuit designed to optimize performance on a specific quantum chip and reduces the impact of noise by utilizing the native gate operation and connectivity of the quantum chip.

[0120] Figure 9 A schematic diagram of the structure of a computer device provided in one embodiment of this application is shown, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the functions of the computer system of the quantum chip simulation method for drug molecules in any of the above embodiments.

[0121] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a computer, causes the computer to perform the functions of the computer system of the quantum chip simulation method for drug molecules in any of the above embodiments.

[0122] This application also provides a computer program product containing instructions that, when executed by a computer, cause the computer to perform the functions of the computer system of the quantum chip simulation method for drug molecules in any of the above embodiments.

[0123] It is understood that the specific examples in this application are only intended to help those skilled in the art better understand the implementation methods of this application, and are not intended to limit the scope of the invention.

[0124] It is understood that in the various embodiments of this application, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not limit the implementation process of the embodiments of this application in any way.

[0125] It is understood that the various implementation methods described in this application can be implemented individually or in combination, and the implementation methods in this application are not limited in this respect.

[0126] Unless otherwise stated, all technical and scientific terms used in the embodiments of this application have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The term "and / or" as used in this application includes any and all combinations of one or more of the associated listed items. The singular forms "a," "the," and "the" as used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0127] It is understood that the processor in the embodiments of this application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by the integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0128] It is understood that the memory in the embodiments of this application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. Specifically, non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may be random access memory (RAM). It should be noted that the memory in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0129] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0130] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the aforementioned method implementations, and will not be repeated here.

[0131] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0132] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0133] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0134] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0135] The above are merely specific embodiments of this application, but the scope of protection of this invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this invention should be determined by the scope of the claims.

Claims

1. A quantum chip simulation method for drug molecules, characterized in that, include: The active and inactive regions of a drug molecule conformation are determined. The drug molecule conformation refers to the different three-dimensional spatial arrangements of a drug molecule formed by single bond rotation or skeleton twisting. The active region refers to the structure in the drug molecule conformation that directly participates in chemical reactions or affects the properties of the drug. The multi-electron atoms in the active region are replaced with hydrogen atoms, and the structure in the inactive region is simplified to obtain the optimized molecular structure. The molecular structure is simulated by an efficient simulated quantum circuit to determine the energy of the drug molecule. The efficient simulated quantum circuit is a quantum circuit designed to optimize performance on a specific quantum chip, which reduces the impact of noise by utilizing the native gate operation and connectivity of the quantum chip.

2. The method according to claim 1, characterized in that, The simplification of the structure in the inactive region to obtain the optimized molecular structure includes: The structure in the inactive region is simplified according to the inactive region simplification method to obtain the optimized molecular structure. The inactive region simplification method includes at least one of the following: substituent simplification, cyclic structure simplification, and removal of unimportant parts.

3. The method according to claim 1, characterized in that, Before determining the active and inactive regions of the drug molecule conformation, the method further includes: One or more initial drug molecule conformations are generated based on the structural information of the drug molecule; The initial drug molecule conformation is expanded to obtain multiple candidate drug molecule conformations; Optimize the molecular conformations of several of the candidate drugs.

4. The method according to claim 3, characterized in that, The expansion of the initial drug molecule conformation yields multiple candidate drug molecule conformations, including: Based on the conformation search algorithm, a conformation search is performed starting from the initial drug molecule conformation to obtain multiple candidate drug molecule conformations. The conformation search algorithm includes at least one of the following: Monte Carlo method, molecular dynamics simulation method, and genetic algorithm.

5. The method according to claim 3, characterized in that, Before expanding the initial drug molecule conformation to obtain multiple candidate drug molecule conformations, the method further includes: An energy minimization algorithm is applied to each initial drug molecule conformation to determine the local energy minimum of the initial drug molecule conformation, thereby obtaining a stable initial drug molecule conformation. The energy minimization algorithm includes at least one of the following: steepest descent method, conjugate gradient method, Newton's method, and quasi-Newton's method.

6. The method according to any one of claims 3-5, characterized in that, Prior to optimizing the conformations of the plurality of candidate drug molecules, the method further includes: Determine the minimum energy of multiple candidate drug molecule conformations; Calculate the energy difference of each candidate drug molecule conformation relative to the minimum value; The Boltzmann factor for each candidate drug molecule conformation is calculated based on the difference. Calculate the partition function based on the Boltzmann factor; The Boltzmann distribution of each candidate drug molecule conformation is calculated based on the Boltzmann factor and the partition function. The candidate drug molecule conformations are screened based on the Boltzmann distribution.

7. The method according to claim 1, characterized in that, The simulation of the molecular structure using a highly efficient simulated quantum circuit includes: An efficient simulated quantum circuit is constructed using a single-qubit rotating logic gate and a dual-gate system supported by a quantum chip. This efficient simulated quantum circuit is used to evolve a qubit from an initial state to a target state. The rotation parameters of the single-qubit rotating logic gate are optimized by constructing a loss function using the Hamiltonian corresponding to the target state and the molecular structure, so that the target state is the ground state of the drug molecule.

8. A quantum chip simulation device for drug molecules, characterized in that, include: The active region determination unit is used to determine the active and inactive regions of a drug molecule conformation, wherein the drug molecule conformation refers to the different three-dimensional spatial arrangements formed by the rotation of single bonds or the twisting of the skeleton of the drug molecule, and the active region refers to the structure in the drug molecule conformation that directly participates in chemical reactions or affects the properties of the drug. The structure optimization unit is used to replace multi-electron atoms in the active region with hydrogen atoms and to simplify the structure in the inactive region to obtain an optimized molecular structure. A molecular simulation unit is used to simulate the molecular structure by means of an efficient simulated quantum circuit to determine the energy of the drug molecule. The efficient simulated quantum circuit is a quantum circuit designed to optimize performance on a specific quantum chip and reduces the impact of noise by utilizing the native gate operation and connectivity of the quantum chip.

9. An electronic device, characterized in that, include: Processor and memory; The processor is connected to a memory, wherein the memory is used to store a computer program, and the processor is used to invoke the computer program to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, perform the method as described in any one of claims 1-7.

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