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REVIEW article
Front. Pharmacol.
Sec. Experimental Pharmacology and Drug Discovery
Volume 16 - 2025 | doi: 10.3389/fphar.2025.1553853
This article is part of the Research Topic Advancing Drug Discovery with AI: Drug-Target Interactions, Mechanisms of Action, and Screening View all 4 articles
Trends in the Research and Development of Peptide Drug Conjugates: Artificial Intelligence Aided Design
Provisionally accepted- 1 Wuhan Third Hospital, Wuhan, Hubei Province, China
- 2 Huazhong University of Science and Technology, Wuhan, China
Peptide-drug conjugates (PDCs) represent an emerging class of targeted therapeutic agents that consist of small molecular drugs coupled to multifunctional peptides through cleavable or non-cleavable linkers. The principal advantage of PDCs lies in their capacity to deliver drugs to diseased tissues at increased local concentrations, thereby reducing toxicity and mitigating adverse effects by limiting damage to non-diseased tissues. Despite the increasing number of PDCs being developed for various diseases, their advancements remain relatively slow due to several development constraints, which include limited available peptides and linkers, narrow therapeutic applications, and incomplete evaluation and information platforms for PDCs. Marked by the recent Nobel Prize awarded to artificial intelligence (AI) and de novo protein design for "protein design and structure prediction", AI is playing an increasingly important role in drug discovery and development. In this review, we summarize the recent developments and limitations of PDCs, highlights the potential of AI in revolutionizing the design and evaluation of PDC.
Keywords: peptide-drug conjugates, artificial intelligence, Drug Discovery, drug design, Drug Evaluation
Received: 31 Dec 2024; Accepted: 11 Feb 2025.
Copyright: © 2025 Zhang, He, Shi, Huang and Peng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Dong-E Zhang, Wuhan Third Hospital, Wuhan, Hubei Province, China
Tong He, Huazhong University of Science and Technology, Wuhan, China
Tianyi Shi, Huazhong University of Science and Technology, Wuhan, China
Kun Huang, Huazhong University of Science and Technology, Wuhan, China
Anlin Peng, Wuhan Third Hospital, Wuhan, Hubei Province, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.