OptNCMiner: a deep learning approach for the discovery of natural compounds modulating disease-specific multi-targets.

ABSTRACT:

Background

Due to their diverse bioactivity, natural product (NP)s have been developed as commercial products in the pharmaceutical, food and cosmetic sectors as natural compound (NC)s and in the form of extracts. Following administration, NCs typically interact with multiple target proteins to elicit their effects. Various machine learning models have been developed to predict multi-target modulating NCs with desired physiological effects. However, due to deficiencies with existing chemical-protein interaction datasets, which are mostly single-labeled and limited, the existing models struggle to predict new chemical-protein interactions. New techniques are needed to overcome these limitations.

Results

We propose a novel NC discovery model called OptNCMiner that offers vario

SUBMITTER: Shin SH 

PROVIDER: S-EPMC9175487 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature