A Novel Deep Neural Network Technique for Drug-Target Interaction.

ABSTRACT: Drug discovery (DD) is a time-consuming and expensive process. Thus, the industry employs strategies such as drug repositioning and drug repurposing, which allows the application of already approved drugs to treat a different disease, as occurred in the first months of 2020, during the COVID-19 pandemic. The prediction of drug-target interactions is an essential part of the DD process because it can accelerate it and reduce the required costs. DTI prediction performed in silico have used approaches based on molecular docking simulations, including similarity-based and network- and graph-based ones. This paper presents MPS2IT-DTI, a DTI prediction model obtained from research conducted in the following steps: the definition of a new method for encoding molecule and protein sequences onto im

SUBMITTER: de Souza JG 

PROVIDER: S-EPMC8954728 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature