Advances in computational methods for PROTAC drug discovery

Proteolysis-targeting chimeras (PROTACs) represent a transformative strategy in drug discovery, enabling the selective degradation of target proteins rather than merely inhibiting their activity. However, their structural complexity and deviation from conventional drug-like properties present major challenges for traditional design and optimization methods. In this review, we provide a comprehensive overview of recent computational advances that facilitate PROTAC development, encompassing chemoinformatics, structural bioinformatics, molecular modeling and machine learning resources. We highlight computational tools for warhead and linker design, ternary complex modeling and the prediction of degradation efficiency and ADMET profiles. Finally, we discuss current limitations and future perspectives, emphasizing strategies to enhance design effectiveness and accelerate clinical translation.

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Publication Details

Journal
Drug Discovery Today
Published
2026-02-18
DOI
https://doi.org/10.1016/j.drudis.2026.104627
Primary Topic
Protein Degradation and Inhibitors
Type
article
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article

Advances in computational methods for PROTAC drug discovery

Carlos A. Velázquez‐Martínez, Massyel S. Martínez-Cortés, José L. Medina-Franco
Drug Discovery Today
Protein Degradation and Inhibitors
article

Advances in computational methods for PROTAC drug discovery

Carlos A. Velázquez‐Martínez, Massyel S. Martínez-Cortés, José L. Medina-Franco
article en

Abstract

Proteolysis-targeting chimeras (PROTACs) represent a transformative strategy in drug discovery, enabling the selective degradation of target proteins rather than merely inhibiting their activity. However, their structural complexity and deviation from conventional drug-like properties present major challenges for traditional design and optimization methods. In this review, we provide a comprehensive overview of recent computational advances that facilitate PROTAC development, encompassing chemoinformatics, structural bioinformatics, molecular modeling and machine learning resources. We highlight computational tools for warhead and linker design, ternary complex modeling and the prediction of degradation efficiency and ADMET profiles. Finally, we discuss current limitations and future perspectives, emphasizing strategies to enhance design effectiveness and accelerate clinical translation.

Drug Discovery TodayVol. 31(2)
University of Alberta (CA), Universidad Nacional Autónoma de México (MX)
Openalex Percentile: Top 53%
Protein Degradation and Inhibitors
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Advances in computational methods for PROTAC drug discovery — Carlos A. Velázquez‐Martínez, Massyel S. Martínez-Cortés, et al. · Drug Discovery Today (2026) | TGRS Research Map | TGRS