An Overview of Drugs for Multiple Targets and Variants of SARS-CoV-2 Through Artificial Intelligence, Machine Learning, Deep Learning, and Experimental Analysis

Introduction

The emergence and rapid evolution of SARS-CoV-2 variants have posed significant challenges in the ongoing fight against the COVID-19 pandemic. The development of effective treatments for multiple viral targets and variants demands innovative approaches, including artificial intelligence (AI), machine learning (ML), and deep learning (DL) techniques. This special issue aims to provide an overview of recent advances in drug discovery for SARS-CoV-2, leveraging AI and ML technologies, as well as experimental analysis. The ongoing COVID-19 pandemic has highlighted the urgent need for innovative approaches in drug discovery to combat the ever-evolving SARS-CoV-2 virus. This special issue aims to provide a comprehensive overview of the latest advancements in drug discovery, focusing on AI-driven strategies, machine learning models, deep learning techniques, structural biology insights, experimental validation, and integrative approaches to address the challenges posed by SARS-CoV-2 and its variants. Additionally, it will explore herbal and combination therapies, therapeutic modalities for mutations in SARS-CoV-2 targeting sites, and the future directions in multi-target drug discovery.

Keywords

SARS-COV-2, Machine learning, Deep learning, Artificial intelligence, computational analysis