A high-throughput prediction method and system for drug-regulatory element associations

By constructing regulatory element-transcription factor and regulatory element-target gene networks, and using the NetOpen model to predict the openness of regulatory elements under drug action, the low efficiency problem of drug-regulatory element association prediction in existing technologies is solved, and drug target prediction for high-throughput screening and personalized medicine is realized.

CN115732026BActive Publication Date: 2026-05-26ACAD OF MATHEMATICS & SYSTEMS SCIENCE - CHINESE ACAD OF SCI +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ACAD OF MATHEMATICS & SYSTEMS SCIENCE - CHINESE ACAD OF SCI
Filing Date
2021-08-26
Publication Date
2026-05-26

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Abstract

This invention relates to a high-throughput prediction method and system for drug-regulatory element associations. The method includes: constructing a regulatory element-transcription factor network; constructing a regulatory element-target gene network; using the expression levels of transcription factors bound to the regulatory element and the target gene of the regulatory element as inputs, constructing a predictive model of the chromatin openness of the regulatory element; using gene expression levels under different drug action conditions as inputs, using the predictive model to predict and compare the openness of the regulatory element under different drug action conditions, thereby predicting drug-regulatory element associations. This invention can predict the relationship between regulatory elements and drugs at the genome-wide level with high throughput, enabling high-throughput screening of drug-regulatory element associations with relatively low investment, reducing drug development risks. These associations have potential value in research on drug mechanisms, drug combinations, and drug repositioning.
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