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IITM Journal of Information Technology

ISSN (P) 2395-5457 | Single Blind Peer Reviewed Journal

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INSTITUTE OF INNOVATION IN TECHNOLOGY & MANAGEMENT
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AI-Enhanced Drug Discovery Using Graph Neural Networks

Nehuti
Department of Computer Science and Engineering
Bharati Vidyapeeth College of Engineering (BVCOE), New Delhi, India 
Author

Keywords: Artificial Intelligence, Deep Learning, Drug Discovery, Graph Neural Networks, Molecular Representation.

Abstract: The integration of artificial intelligence (AI) in drug discovery has profoundly transformed the pharmaceutical landscape by significantly accelerating the identification of potential drug candidates. Among the various AI techniques, Graph Neural Networks (GNNs) have proven to be particularly effective in modeling molecular structures, optimizing drug-target interactions, and enhancing prediction accuracy. This paper aims to explore the application of GNNs in the field of drug discovery, emphasizing their advantages in comparison to traditional molecular representations. Furthermore, the paper delves into real-world applications, case studies, and a comparative analysis of existing methodologies to offer a comprehensive overview of the current advancements in AI-driven drug discovery

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