Geometric Deep learning Prioritization and Validation of Cannabis Phytochemicals as Anti-HCV Non-nucleoside Direct-acting Inhibitors.

ABSTRACT:

Introduction

The rate of acute hepatitis C increased by 7% between 2020 and 2021, after the number of cases doubled between 2014 and 2020. With the current adoption of pan-genotypic HCV therapy, there is a need for improved availability and accessibility of this therapy. However, double and triple DAA-resistant variants have been identified in genotypes 1 and 5 with resistance-associated amino acid substitutions (RAASs) in NS3/4A, NS5A, and NS5B. The role of this research was to screen for novel potential NS5B inhibitors from the cannabis compound database (CBD) using Deep Learning.

Methods

Virtual screening of the CBD compounds was performed using a trained Graph Neural Network (GNN) deep learning model. Re-docking and conventional docking were used to validate the results

SUBMITTER: Charles S 

PROVIDER: S-EPMC11638990 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature