Identification of Potential Inhibitors of Severe Acute Respiratory Syndrome Coronavirus 2 Envelope Protein Ion Channel Activity Using Machine Learning Techniques

Overview

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) is a viral disease that has caused a major global pandemic. There are many developing treatments for SARS-CoV2 including vaccines from Pfizer or Moderna but the field lacks specific treatments that target viral pathogenesis. Quick screening of drug candidates is critical to reducing the fatality rate and societal impacts of SARS-CoV2. We used 3 models including Random Forest, Support Vector Machine, and Multilayer Perceptron Neural Network to examine previously identified inhibitors. The most promising new inhibitors our classification models identified include: Methylene Blue Cation and Piretanide. Further study with Molecular Docking confirmed the effective inhibition of SARS-CoV2 Envelope protein by these 2 molecules. A set of chemical descriptors were proposed as key indicators for future screening using new datasets. IOWA

Competition history

• JSHS 2022 Category not listed

Resources

• National JSHS abstract book ↗

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