Drug-target protein affinity prediction method and system

A prediction method and target protein technology, applied in proteomics, biostatistics, bioinformatics, etc., can solve problems such as task inequality, improve accuracy, solve cold start problems, and improve task adaptability Effect
CN113823352AActive Publication Date: 2021-12-21NANKAI UNIV
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
NANKAI UNIV
Publication Date
2021-12-21

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Abstract

The invention provides a drug-target protein affinity prediction method and system, and belongs to the technical field of biological information processing based on artificial intelligence. The method comprises the following steps: respectively coding a drug chemical molecule and a target protein molecule in a drug-target protein pair to be detected to obtain a drug input representation and a target protein input representation ; and processing the drug input representation and the target protein input representation by using a drug-target protein affinity prediction model to obtain a drug-target protein affinity prediction value. A meta-learning algorithm is utilized to effectively mine the correlation between different subtasks; and the task unevenness between different subtasks is relieved by using the regularization item, the task adaptability of the drug-target protein affinity prediction model is improved, the drug-target protein affinity prediction model with generalization performance is obtained, the accuracy of unknown drug-target protein pair affinity prediction is improved, and the cold start problem in the aspect of drug-target protein affinity prediction is effectively solved.
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Description

technical field

[0001] The invention relates to the technical field of biological information processing based on artificial intelligence, in particular to a drug-target protein affinity prediction method and system based on a task-adaptive meta-learning neural network. Background technique

[0002] Drug-target protein affinity, also known as drug-target protein interaction, reflects the binding strength between a drug molecule and a specific target protein, and its prediction results play an important role in new drug discovery, drug repositioning and drug side effect prediction.

[0003] Traditional laboratory-based methods for drug-target protein affinity prediction are costly and inefficient, and are not suitable for dealing with a large number of medicinal chemical molecules and target protein molecules. In recent years, machine learning-based methods have accelerated the progress of drug-target protein affinity prediction, and have received more and more attention in b...

Claims

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