Efficient machine learning model for predicting drug-target interactions with case study for Covid-19.

ABSTRACT:

Background

Discover possible Drug Target Interactions (DTIs) is a decisive step in the detection of the effects of drugs as well as drug repositioning. There is a strong incentive to develop effective computational methods that can effectively predict potential DTIs, as traditional DTI laboratory experiments are expensive, time-consuming, and labor-intensive. Some technologies have been developed for this purpose, however large numbers of interactions have not yet been detected, the accuracy of their prediction still low, and protein sequences and structured data are rarely used together in the prediction process.

Methods

This paper presents DTIs prediction model that takes advantage of the special capacity of the structured form of proteins and drugs. Our model obtains feat

SUBMITTER: El-Behery H 

PROVIDER: S-EPMC8256690 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature