A deep learning-based method for drug-target interaction prediction based on long short-term memory neural network.

ABSTRACT:

Background

The key to modern drug discovery is to find, identify and prepare drug molecular targets. However, due to the influence of throughput, precision and cost, traditional experimental methods are difficult to be widely used to infer these potential Drug-Target Interactions (DTIs). Therefore, it is urgent to develop effective computational methods to validate the interaction between drugs and target.

Methods

We developed a deep learning-based model for DTIs prediction. The proteins evolutionary features are extracted via Position Specific Scoring Matrix (PSSM) and Legendre Moment (LM) and associated with drugs molecular substructure fingerprints to form feature vectors of drug-target pairs. Then we utilized the Sparse Principal Component Analysis (SPCA) to compress the

SUBMITTER: Wang YB 

PROVIDER: S-EPMC7079345 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature