Evidence map›Paper›PMID 39386564›Full record

ArticlebioRxiv : the preprint server for biology2024

Rationalize the Functional Roles of Protein-Protein Interactions in Targeted Protein Degradation by Kinetic Monte-Carlo Simulations.

Zhaoqian Su, Shanye Yin, Yinghao Wu

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In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Zhaoqian SuData Science Institute, Vanderbilt University, 1001 19th Ave S, Nashville, TN, 37212.
Shanye YinDepartment of Pathology, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY, 10461.
Yinghao WuDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY, 10461.ORCID 0000-0003-1181-5670

Funding

A multiscale model for binding kinetics of membrane receptors on cell surfacesR01GM120238 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI WU, YINGHAO · 2016 to 2020
$1.6M
Computational models for the signaling of tumor necrosis factor receptor on cell surfacesR01GM122804 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI WU, YINGHAO · 2017 to 2020
$1.3M
NIGMS NIH HHS R01 GM120238NIGMS NIH HHS R01 GM122804
6 · The paper itself

Abstract

Targeted protein degradation is a promising therapeutic strategy to tackle disease-causing proteins that lack binding pockets for traditional small-molecule inhibitors. Its first step is to trigger the proximity between a ubiquitin ligase complex and a target protein through a heterobifunctional molecule, such as proteolysis targeting chimeras (PROTACs), leading to the formation of a ternary complex. The properties of protein-protein interactions play an important regulatory role during this process, which can be reflected by binding cooperativity. Unfortunately, although computer-aided drug design has become a cornerstone of modern drug development, the endeavor to model targeted protein degradation is still in its infancy. The development of computational tools to understand the impacts of protein-protein interactions on targeted protein degradation, therefore, is highly demanded. To reach this goal, we constructed a non-redundant structural benchmark of the most updated ternary complexes and applied a kinetic Monte-Carlo method to simulate the association between ligases and PROTAC-targeted proteins in the benchmark. Our results show that proteins in most complexes with positive cooperativity tend to associate into native-like configurations more often. In contrast, proteins very likely failed to associate into native-like configurations in complexes with negative cooperativity. Moreover, we compared the protein-protein association through different interfaces generated from molecular docking. The native-like binding interface shows a higher association probability than all the other alternative interfaces only in the complex with positive cooperativity. These observations support the idea that the formation of ternary complexes is closely regulated by the binary interactions between proteins. Finally, we applied our method to cyclin-dependent kinases 4 and 6 (CDK4/6). We found that their interactions with the ligase are not as similar as their structures. Altogether, our study paves the way for understanding the role of protein-protein interactions in PROTACE-induced ternary complex formation. It can potentially help in searching for degraders that selectively target specific proteins.

Identifiers

PMID39386564
PMCPMC11463391

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