De novo drug design through artificial intelligence: an introduction

• Published in: Frontiers in hematology Vol. 3
• Main Authors: Crucitti, Davide, Pérez Míguez, Carlos, Díaz Arias, José Ángel, Fernandez Prada, Diego Beltrán, Mosquera Orgueira, Adrián
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 25-01-2024
• Subjects: artificial intelligence; cheminformatics; de novo; drug design; machine learning
• ISSN: 2813-3935; 2813-3935
• DOI: 10.3389/frhem.2024.1305741

Developing new drugs is a complex and formidable challenge, intensified by rapidly evolving global health needs.
De novo
drug design is a promising strategy to accelerate and refine this process. The recent introduction of Generative Artificial Intelligence (AI) algorithms has brought new attention to the field and catalyzed a paradigm shift, allowing rapid and semi-automatic design and optimization of drug-like molecules. This review explores the impact of
de novo
drug design, highlighting both traditional methodologies and the recently introduced generative algorithms, as well as the promising development of Active Learning (AL). It places special emphasis on their application in oncological drug development, where the need for novel therapeutic agents is urgent. The potential integration of these AI technologies with established computational and experimental methods heralds a new era in the rapid development of innovative drugs. Despite the promising developments and notable successes, these technologies are not without limitations, which require careful consideration and further advancement. This review, intended for professionals across related disciplines, provides a comprehensive introduction to AI-driven
de novo
drug design of small organic molecules. It aims to offer a clear understanding of the current state and future prospects of these innovative techniques in drug discovery.