Small molecule drug virtual screening method based on deep migration learning and application thereof

A technology of virtual screening and transfer learning, which is applied in the field of virtual screening of small molecule drugs based on deep transfer learning, which can solve problems such as difficulty in obtaining useful ligand samples and insufficient information on active ligand samples.
CN110459274AActive Publication Date: 2019-11-15NANJING UNIV OF POSTS & TELECOMM
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
NANJING UNIV OF POSTS & TELECOMM
Publication Date
2019-11-15

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Abstract

The invention discloses a small molecule drug virtual screening method based on deep migration learning and application thereof. A source domain is used as an input to be trained, converged and derived to obtain a weight matrix; a target domain is input into an improvement tool to serve as the initialization weight of the target domain; fine adjustment, training and convergence are conducted on the initialization weight and data in the target domain sequentially; a biological activity value of interaction of a lead compound and a drug target in the target domain is predicted, a target domain molecular fingerprint and a predicted value are obtained, and an evaluation index root mean square error and a correlation coefficient of a predicted result are output; the target domain is subjected to fine adjustment by repeating above steps, and the weight matrix of the source domain helps the target domain build a model. According to the small molecule drug virtual screening method and the application thereof, the effective virtual screening model can still be obtained under the condition that the information of a known active ligand sample is insufficient, and does not need to rely on a large number of data samples.
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Description

technical field

[0001] The present invention relates to a small molecule drug screening method and its application, in particular to a small molecule drug virtual screening method based on deep transfer learning and its application. Background technique

[0002] Small molecule drug screening often requires high-throughput experimental techniques to measure the biological activity value of the interaction between the target and the compound in a huge number of compound databases to screen lead compounds. However, the experimental method is time-consuming and labor-intensive. What's worse, the number of compounds that are often available is very limited, and not all drug targets are suitable for high-throughput screening experiments. Therefore, computational-based virtual screening, which simulates the interaction between the target of interest and drug candidates, has been widely used in small molecule drug design.

[0003] Computational-based virtual screening can be divide...

Claims

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