Abstract 2428: Structural proteomics and AI powers PROTAC rational design

Abstract Proximity-inducing drugs are an emerging class of protein interaction modulators, as many cellular processes rely on the coordinated activity of proteins to support cell growth, homeostasis, regulation and communication. This is most famously exemplified by proteolysis-targeting chimera (PROTAC). PROTACs are heterobifunctional compounds consisting of two ligands joined by a linker to bring together an E3 ligase and a protein of interest and induce ubiquitination and subsequent degradation. Dozens of PROTAC drugs are being investigated in clinical trials, most notably targeting androgen receptor (AR) and BTK. The efficacy of a PROTAC molecule is driven by ternary complex formation and stability, rather than relying solely on the binary affinity of a single molecule to a single protein. Therefore, the major challenge in rational development of PROTACs is deep understanding of the dynamics and functions of complex assembly. However, protein complexes and interactions have traditionally been hard to model and are not well represented in existing protein structure resources, both experimental and computational.In this work, we present the AIMS™ platform, which integrates structural mass spectrometry (MS) data and AI modeling tools. We apply our AIMS™ platform to multiple PROTAC systems, allowing us to improve the confidence of predicted structures compared to AI alone and support rational PROTAC design. Citation Format: Nitzan Simchi, Michal Ran Shchory, Joseph Rinberg, Alon Shtrikman, Yaron Ben Shoshan-Galeczki, Gali Arad, Katharina Lange, Sagie Brodsky, Anjana Shenoy, Dimitri Kovalerchik, Yonatan Kedem, Iris Alchanati, Galina Otonin, Noam Cohen, Kirill Pevzner, Eran Seger. Structural proteomics and AI powers PROTAC rational design [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2428.

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Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-2428
Primary Topic
Protein Degradation and Inhibitors
Type
article
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article

Abstract 2428: Structural proteomics and AI powers PROTAC rational design

Eran Seger, Iris Alchanati, Yaron Ben Shoshan-Galeczki, Alon Shtrikman et al.
Cancer Research
Protein Degradation and Inhibitors
article

Abstract 2428: Structural proteomics and AI powers PROTAC rational design

Eran Seger, Iris Alchanati, Yaron Ben Shoshan-Galeczki, Alon Shtrikman, Kirill Pevzner, Nitzan Simchi, Sagie Brodsky, Kathrin Lange, Dimitri Kovalerchik, Galina Otonin, Joseph Rinberg, Anjana Shenoy, Gali Arad, Yonatan Kedem, Noam Cohen, Michal Ran Shchory
article en

Abstract

Abstract Proximity-inducing drugs are an emerging class of protein interaction modulators, as many cellular processes rely on the coordinated activity of proteins to support cell growth, homeostasis, regulation and communication. This is most famously exemplified by proteolysis-targeting chimera (PROTAC). PROTACs are heterobifunctional compounds consisting of two ligands joined by a linker to bring together an E3 ligase and a protein of interest and induce ubiquitination and subsequent degradation. Dozens of PROTAC drugs are being investigated in clinical trials, most notably targeting androgen receptor (AR) and BTK. The efficacy of a PROTAC molecule is driven by ternary complex formation and stability, rather than relying solely on the binary affinity of a single molecule to a single protein. Therefore, the major challenge in rational development of PROTACs is deep understanding of the dynamics and functions of complex assembly. However, protein complexes and interactions have traditionally been hard to model and are not well represented in existing protein structure resources, both experimental and computational.In this work, we present the AIMS™ platform, which integrates structural mass spectrometry (MS) data and AI modeling tools. We apply our AIMS™ platform to multiple PROTAC systems, allowing us to improve the confidence of predicted structures compared to AI alone and support rational PROTAC design. Citation Format: Nitzan Simchi, Michal Ran Shchory, Joseph Rinberg, Alon Shtrikman, Yaron Ben Shoshan-Galeczki, Gali Arad, Katharina Lange, Sagie Brodsky, Anjana Shenoy, Dimitri Kovalerchik, Yonatan Kedem, Iris Alchanati, Galina Otonin, Noam Cohen, Kirill Pevzner, Eran Seger. Structural proteomics and AI powers PROTAC rational design [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2428.

Cancer ResearchVol. 86(7_Supplement)
Alzheimer's Association of Israel (IL)
Openalex Percentile: Top 9%
Protein Degradation and Inhibitors
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