Novel in silico screening system for plant defense activators using deep learning-based prediction of reactive oxygen species accumulation.

ABSTRACT:

Background

Plant defense activators offer advantages over pesticides by avoiding the emergence of drug-resistant pathogens. However, only a limited number of compounds have been reported. Reactive oxygen species (ROS) act as not only antimicrobial agents but also signaling molecules that trigger immune responses. They also affect various cellular processes, highlighting the potential ROS modulators as plant defense activators. Establishing a high-throughput screening system for ROS modulators holds great promise for identifying lead chemical compounds with novel modes of action (MoAs).

Results

We established a novel in silico screening system for plant defense activators using deep learning-based predictions of ROS accumulation combined with the chemical properties of the co

SUBMITTER: Kogoshi M 

PROVIDER: S-EPMC10704738 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature