Hierarchical Structural Alert Model for Endocrine Disruptor Screening
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Solution Overview
Problem
Current methods for high-throughput screening of potential nuclear receptor-mediated endocrine disruptors are inefficient, lacking effective mechanisms for high-throughput screening and providing limited insights into receptor competitive activity and agonistic-antagonistic activity.
Innovation Solution
A hierarchical structure alert method is developed, extracting primary, secondary, and tertiary structural alerts from compounds to form a high-throughput screening model. This model uses PubChem fingerprint molecular fingerprints, SARpy software, and in vitro experimental data to predict the disrupting activity of compounds on nuclear receptors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If in vitro experimental methods (competitive binding, reporter gene, yeast two-hybrid, fluorescence polarization) and in vivo tests are used to screen for EDCs, then the screening can identify potential endocrine disruptors with mechanisms, but the process takes time and effort and is quite high in cost
Solution Approach 1:
The patent creates virtual copies of the complex in vitro and in vivo screening processes through computational models. Molecular docking simulations replicate ligand-receptor binding interactions, and QSAR models replicate the predictive capability of experimental assays, enabling high-throughput virtual screening that eliminates the need for time-consuming physical experiments while maintaining screening reliability
Solution Approach 2:
The patent replaces physical laboratory experiments (mechanical/chemical processes) with computational simulations. Molecular docking algorithms substitute for competitive binding and fluorescence polarization assays, while QSAR calculations replace reporter gene and yeast two-hybrid experiments, transforming the screening process from wet-lab to dry-lab methodology
2Reliability
If in vitro and in vivo test methods are used to screen for EDCs, then the screening can provide mechanistic insights, but the cost is quite high
Solution Approach 1:
The patent generates virtual replicas of experimental data through computational modeling. Molecular docking scores and QSAR predictions create surrogate measures that replicate the information content of expensive experimental assays, enabling comprehensive screening of thousands of compounds at minimal cost while maintaining comparable reliability
Solution Approach 2:
The patent employs inexpensive computational tools and algorithms that can be rapidly applied to large datasets. The molecular docking software and QSAR models serve as low-cost, reusable screening filters that can evaluate millions of compounds without the need for repeated expensive experimental measurements
3Measurement precision
If thousands of chemicals in the environment are screened for one by one using traditional methods, then each compound can be evaluated individually, but the process is inefficient and cannot keep pace with the volume of chemicals to be screened
Solution Approach 1:
The patent divides the screening process into sequential filtering stages: first applying molecular docking to identify compounds with potential binding affinity, then applying QSAR models to predict biological activity, and finally applying structural alert patterns to identify mechanistic signatures. This multi-stage segmentation enables systematic evaluation of large chemical datasets with both speed and precision
Solution Approach 2:
The patent performs preliminary computational screening using molecular docking and QSAR models before any experimental work is undertaken. By pre-filtering the chemical database to identify the most promising candidates based on virtual binding affinity and predicted activity, the system prepares a reduced set of compounds for subsequent targeted evaluation, dramatically increasing overall throughput
4Loss of information
If molecular dynamics simulation is used to study ligand-receptor binding, then the interaction mechanism can be analyzed, but it takes a long time and cannot provide effective high-throughput screening means for more than 100 million chemicals
Solution Approach 1:
The patent segments the mechanism analysis into discrete, computationally efficient components: molecular docking for binding mode prediction, QSAR models for activity quantification, and structural alert pattern recognition for mechanistic classification. This segmentation enables detailed mechanistic insights to be obtained through rapid, parallelizable calculations rather than time-consuming continuous simulation
Solution Approach 2:
The patent extracts key mechanistic information from complex molecular interactions by identifying critical binding residues, interaction energies, and structural alert patterns. By isolating and analyzing only the most informative features rather than performing comprehensive dynamics simulation, the system obtains mechanism insights at a fraction of the computational cost
Data Source
AI summary
The present invention provides a model for high-throughput screening of endocrine disruptors and a method for screening the same. In the present invention, primary structural alerts, secondary structural alerts and tertiary structural alerts of compounds are extracted according to a nuclear receptor, and then the primary structural alerts, the secondary structural alerts and the tertiary structural alerts form a nuclear receptor high-throughput screening model; hierarchical structural alert matching is carried out on target compounds through the nuclear receptor high-throughput screening model, and ligand-receptor binding mode analysis and semi-quantitative prediction of binding activity and disrupting activity are performed. According to the present invention, the defect in prior art that potential nuclear receptor-mediated endocrine disruptors cannot be effectively screened in high throughput is overcome, high-throughput screening of potential nuclear receptor-mediated endocrine disruptors can be performed, and receptor competitive activity and A-Anta activity of the nuclear receptor-mediated endocrine disruptors can be determined.