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

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

Closes 04 June, 2024

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Journal: Anti-Infective Agents
Guest editor(s): Saad Salman
Co-Guest Editor(s):

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

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Review Article

An overview of drugs for multiple targets and variants of SARS-COV-2: datasets obtained through AI, ML and experimental analysis

Author(s): Sci-sol Consortium*

The ongoing global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has highlighted the urgent need for effective therapeutics. Traditional drug development approaches have primarily focused on targeting individual proteins or pathways involved in viral replication or host immune response. However, given the complex nature of SARS-CoV-2 infection and its ability to exploit multiple cellular pathways, a multi-targeted approach has gained considerable attention. This comprehensive review aims to summarize the current state of research on drugs targeting multiple pathways of SARS-CoV-2. Several drugs, including nucleoside analogs, RNA-dependent RNA polymerase inhibitors, and protease inhibitors, are examined for their efficacy in targeting multiple viral enzymes simultaneously. We report multiple SARS-COV-2 targets and variants utilizing Computational studies, Machine Learning (ML), Artificial Intelligence (AI), and in-vitro analysis. The dysregulation of host immune responses in severe cases of COVID-19 necessitates the development of immunomodulatory therapies. We discussed the potential of repurposing existing drugs, such as antivirals, antimalarials, and antiretrovirals, as well as novel drug combinations, to achieve synergistic effects against SARS-CoV-2. The drugs that demonstrated their action on multiple sites (Spike, RdRp, N-protein, PLpro, NendoU, Mpro) of SARS-COV-2 were Cobicistat, Ivermectin, Ledipasvir, Montelukast, Sildenafil, Ritonavir and Telmisartan. Whereas monoclonal antibodies such as Imdevimab, Casirivimab, Bamlanivimab, Sotrovimab, and Etesevimab were active against the variants of SARS-COV-2. The development of drugs targeting multiple pathways of SARS-CoV-2 offers a promising strategy to combat the virus effectively. The integration of antiviral agents, immunomodulatory drugs, and repurposed therapeutics presents a comprehensive approach that can address the complexities of viral infection, viral replication, and the host immune response. Further preclinical and clinical studies are needed to validate the efficacy, safety, and long-term effects of these multi-targeted drugs in the fight against COVID-19.