Ligand-Macromolecule Complex Modeling via Substructure Mapping
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Solution Overview
Problem
Current methods for determining the three-dimensional structural information of molecules are limited, as experimental determination of all molecular structures is unrealistic, and computational techniques struggle to accurately model complex formations between ligands and macromolecules.
Innovation Solution
A computer-based method is developed to model complex formations between query ligands and target macromolecules by identifying substructures, mapping spatial relationships, and generating 3-D structural models, which can include partial or complete atomic coordinates, allowing for the evaluation of compatibility and binding affinity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If experimental determination methods are used to obtain 3-D structural information of molecules, then measurement precision is improved, but productivity deteriorates due to the unrealistic scope of determining all molecular structures
Solution Approach 1:
The patent uses computational techniques to generate 3-D structural models as copies of experimentally determined structures. Instead of determining every molecular structure experimentally, the system creates computational representations based on 2-D structures and known 3-D templates, enabling high-throughput structural analysis without corresponding experimental workload
Solution Approach 2:
The patent performs preliminary computational modeling of 3-D structures before experimental validation. By pre-generating 3-D models from 2-D structures and comparing them against databases of known structures, the system identifies candidate molecules for experimental study, thereby reducing the overall experimental burden while maintaining structural accuracy
2Productivity
If computational techniques are used to generate 3-D structural models, then productivity is improved, but measurement precision deteriorates due to limitations in accurately modeling complex ligand-macromolecule formations
Solution Approach 1:
The patent segments the ligand molecule into substructures and compares each segment against substructures in the database. This segmentation allows the system to handle complex ligand-macromolecule formations by breaking them into manageable comparative units, improving both the accuracy of spatial relationship mapping and the overall productivity of the modeling process
Solution Approach 2:
The patent introduces a database of pre-stored 3-D structural models as an intermediary between computational generation and final structural determination. This intermediary database provides reference structures that guide the computational modeling process, enhancing accuracy by anchoring predictions to experimentally validated templates while maintaining high throughput
3Ease of operation
If substructure comparison methods are used to model ligand-macromolecule complexes, then ease of operation is improved, but manufacturing precision deteriorates due to potential loss of atomic coordinate accuracy
Solution Approach 1:
The patent maps spatial relationships by comparing 2-D substructure representations across different dimensional representations. By identifying corresponding atoms through 2-D substructure matching and then transferring 3-D coordinates from database entries, the system achieves accurate atomic coordinate determination while maintaining operational simplicity through automated dimensionality transformation
Data Source
AI summary
Computer-based methods for modeling complex formation between a query ligand and a target macromolecule are described herein. The methods can include, for example, providing a structural model of a query ligand and a structural model of a target macromolecule; identifying a substructure of the query ligand; identifying comparison ligands in a set of 3-D structural models that each share an identical substructure with the query ligand, wherein each 3-D structural model comprises a comparison ligand and a comparison macromolecule, and wherein the comparison macromolecule has structural features homologous to the target macromolecule; mapping spatial relationships between the substructure atoms of the query ligand and the comparison ligand such that corresponding atoms are identified; assigning atomic coordinates to the corresponding atoms of the query ligand; and generating one or more output models, each model comprising a 3-D structural model of the query ligand substructure and the target macromolecule. Related articles and apparatuses are also described.