Method For Predict Affinity Between Drug And Target Substance

A computer program stored in a computer-readable storage medium, wherein the computer program executes following methods for predicting an affinity between a drug and a target substance when the computer program is executed by one or more processors, the method comprising:

• extracting a feature value of each of the drug and the target substance by using a first neural network;
• performing a cross attention between the feature value by using a second neural network;
• and
• predicting the affinity between the drug and the target substance based on a result of performing the cross attention by using a third neural network,
• wherein the performing of the cross attention between the feature values by using the second neural network includes:
• generating a first key, a first query, and a first value for the drug based on the feature value of the drug, and generating a second key, a second query, and a second value for the target substance based on the feature value of the target substance;
• generating a cross attention vector based on the second query and the first key, and calculating the feature value of the target substance for the drug by applying the cross attention vector to the first value;
• and
• generating a cross attention vector based on the first query and the second key, and calculating the feature value of the drug for the target substance by applying the cross attention vector to the second value.

A computing device predicting an affinity between a drug and a target substance, comprising:

• a processor including at least one core;
• and
• a storage unit storing information related to a drug and a target substance,
• wherein the processor is configured to:
• extract a feature value of each of the drug and the target substance by using a first neural network,
• perform a cross attention between the features by using a second neural network, and
• predict the affinity between the drug and the target substance based on a result of performing the cross attention by using a third neural network,
• wherein the performing of the cross attention between the feature values by using the second neural network includes:
• generating a first key, a first query, and a first value for the drug based on the feature value of the drug, and generating a second key, a second query, and a second value for the target substance based on the feature value of the target substance;
• generating a cross attention vector based on the second query and the first key, and calculating the feature value of the target substance for the drug by applying the cross attention vector to the first value;
• and
• generating a cross attention vector based on the first query and the second key, and calculating the feature value of the drug for the target substance by applying the cross attention vector to the second value.