In-Silico Approaches for the Screening and Discovery of Broad-Spectrum Marine Natural Product Antiviral Agents Against Coronaviruses

Abstract

Zachary Boswell,1 Jacopo Umberto Verga,1,2 James Mackle,1 Karen Guerrero-Vazquez,2 Olivier P Thomas,3 James Cray,4 Bethany J Wolf,5 Yeun-Mun Choo,6 Peter Croot,7 Mark T Hamann,8 Gary Hardiman1,5,9 1School of Biological Sciences and Institute for Global Security, Queen’s University, Belfast, Northern Ireland, UK; 2Genomic Data Science, University of Galway, Galway, Ireland; 3School of Biological and Chemical Sciences, Ryan Institute, University of Galway, Galway, H91TK33 Ireland; 4Department of Biomedical Education and Anatomy, College of Medicine and Division of Biosciences, College of Dentistry, Ohio State University, Columbus, OH, USA; 5Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA; 6Department of Chemistry, University of Malaya, Kuala Lumpur, Malaysia; 7Irish Centre for Research in Applied Geoscience, Earth and Ocean Sciences and Ryan Institute, School of Natural Sciences, University of Galway, Galway, Ireland; 8Departments of Drug Discovery and Biomedical Sciences and Public Health, Colleges of Pharmacy and Medicine, Medical University of South Carolina, Charleston, SC, USA; 9Department of Medicine, Medical University of South Carolina, Charleston, SC, USACorrespondence: Gary Hardiman, School of Biological Sciences and Institute for Global Food Security, Faculty of Medicine, Health, and Life Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL, Northern Ireland, UK, Email [email protected]: The urgent need for SARS-CoV-2 controls has led to a reassessment of approaches to identify and develop natural product inhibitors of zoonotic, highly virulent, and rapidly emerging viruses. There are yet no clinically approved broad-spectrum antivirals available for beta-coronaviruses. Discovery pipelines for pan-virus medications against a broad range of betacoronaviruses are therefore a priority. A variety of marine natural product (MNP) small molecules have shown inhibitory activity against viral species. Access to large data caches of small molecule structural information is vital to finding new pharmaceuticals. Increasingly, molecular docking simulations are being used to narrow the space of possibilities and generate drug leads. Combining in-silico methods, augmented by metaheuristic optimization and machine learning (ML) allows the generation of hits from within a virtual MNP library to narrow screens for novel targets against coronaviruses. In this review article, we explore current insights and techniques that can be leveraged to generate broad-spectrum antivirals against betacoronaviruses using in-silico optimization and ML. ML approaches are capable of simultaneously evaluating different features for predicting inhibitory activity. Many also provide a semi-quantitative measure of feature relevance and can guide in selecting a subset of features relevant for inhibition of SARS-CoV-2.Keywords: SARS-CoV-2, natural products, protease, methyl transferases, RNA dependent polymerases, viral transcription, genome replication, betacoronavirus

Keywords

• sars-cov-2
• natural products
• protease
• methyl transferases
• rna dependent polymerases
• viral transcription
• genome replication
• betacoronavirus.