Amino Acid Search System Using Segmented Optimization
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Solution Overview
Problem
Current search methods for finding the optimum arrangement of amino acids in coarse-grained models of medium molecules, such as peptides with a large number of residues, face increased search time due to the enormous number of bits used in combinatorial optimization problems.
Innovation Solution
A search system that employs a terminal device and an Ising device to efficiently find the optimum arrangement combination by transforming cost arithmetic expressions to reduce computation complexity, distinguishing between L-form and D-form amino acids in subsequent stages, and adjusting constraint terms to avoid local solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a search method is used to find the optimum arrangement of amino acids in coarse-grained models with a large number of residues, then the accuracy of finding the optimum arrangement is improved, but the search time increases due to the enormous number of bits used in combinatorial optimization problems
Solution Approach 1:
The patent divides the combinatorial optimization problem into two stages: first solving without distinguishing L-form and D-form amino acids to obtain a rough optimum arrangement, then using this result as initial arrangement for a second search that does distinguish between forms. This segmentation reduces the search space in each stage, improving efficiency while maintaining accuracy.
Solution Approach 2:
The patent performs a preliminary search without distinguishing L-form and D-form amino acids to obtain an initial arrangement that minimizes the cost function. This preliminary action creates a good starting point for the subsequent refined search, reducing the time needed to reach the final optimum solution.
2Measurement precision
If the number of amino acid residues in the coarse-grained model is increased, then the accuracy of the drug discovery model is improved, but the computation complexity increases due to the enormous number of bits required
Solution Approach 1:
The patent segments the computation process into two phases: a first phase that ignores L/D-form distinctions to quickly establish spatial arrangement, and a second phase that incorporates form distinctions for refined optimization. This reduces the computational complexity at each stage while achieving the same level of modeling accuracy.
Solution Approach 2:
The patent performs preliminary optimization without L/D-form distinctions to establish a baseline arrangement, then uses this as the foundation for the more computationally intensive second phase that incorporates form-specific interactions. This preliminary action significantly reduces the overall computation complexity.
3Measurement precision
If a conventional search method is used that makes distinction between L-form and D-form amino acids from the beginning, then the accuracy of the arrangement is improved, but the search time becomes excessively long
Solution Approach 1:
The patent segments the search process into two distinct stages: the first stage searches without distinguishing L-form and D-form amino acids to quickly find a near-optimum arrangement, while the second stage performs refined searching with full distinction between forms. This segmentation avoids the excessive search time of conventional methods while maintaining accuracy.
Solution Approach 2:
The patent performs a preliminary search that establishes spatial arrangement without L/D-form distinctions, creating an informed initial state for the subsequent refined search. This preliminary action dramatically reduces the search time compared to conventional methods that start with full distinction from the beginning.
Data Source
AI summary
A non-transitory computer-readable storage medium storing a search program that causes at least one computer to execute a process, the process includes searching for, as an answer of a combinatorial optimization problem, a first arrangement of a plurality of amino acids included in a medium molecule based on a value of a first cost arithmetic expression that does not make distinction between a L-form and a D-form of the plurality of amino acids; searching for, as the answer of the combinatorial optimization problem, a second arrangement of the plurality of amino acids based on a value of a second cost arithmetic expression that makes distinction between the L-form and the D-form of the plurality of amino acids by setting the first arrangement as an initial arrangement of searching; and outputting the second arrangement.