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Updated: Jun 3, 2025

Assessing Cellular Target Engagement by SHP2 PTPN11 Phosphatase Inhibitors
Published on: July 17, 2020
Study on SHP2 Conformational Transition and Structural Characterization of Its High-Potency Allosteric Inhibitors by
Baerlike Wujieti1, Mingtian Hao1, Erxia Liu1
1School of Chemical Sciences, University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing 100049, China.
Abstract:
The src-homology 2 domain-containing phosphatase 2 (SHP2) is a human cytoplasmic protein tyrosine phosphatase that plays a crucial role in cellular signal transduction. Aberrant activation and mutations of SHP2 are associated with tumor growth and immune suppression, thus making it a potential target for cancer therapy. Initially, researchers sought to develop inhibitors targeting SHP2's catalytic site (protein tyrosine phosphatase domain, PTP). Due to limitations such as conservativeness and poor membrane permeability, SHP2 was once considered a challenging drug target. Nevertheless, with the in-depth investigations into the conformational switch mechanism from SHP2's inactive to active state and the emergence of various SHP2 allosteric inhibitors, new hope has been brought to this target. In this study, we investigated the interaction models of various allosteric inhibitors with SHP2 using molecular dynamics simulations. Meanwhile, we explored the free energy landscape of SHP2 activation using enhanced sampling technique (meta-dynamics simulations), which provides insights into its conformational changes and activation mechanism. Furthermore, to biophysically interpret high-dimensional simulation trajectories, we employed interpretable machine learning methods, specifically extreme gradient boosting (XGBoost) with Shapley additive explanations (SHAP), to comprehensively analyze the simulation data. This approach allowed us to identify and highlight key structural features driving SHP2 conformational dynamics and regulating the activity of the allosteric inhibitor. These studies not only enhance our understanding of SHP2's conformational switch mechanism but also offer crucial insights for designing potent allosteric SHP2 inhibitors and addressing drug resistance issues.
Insights
This study reveals key structural features of SHP2 (src-homology 2 domain-containing phosphatase 2) allosteric inhibitors. Machine learning analysis of simulations provides insights into SHP2
Area of Science:
- Biochemistry
- Molecular Biology
- Pharmacology
Background:
- SHP2 (src-homology 2 domain-containing phosphatase 2) is a key regulator of cellular signaling.
- Aberrant SHP2 activity drives tumor growth and immune suppression, making it a cancer therapeutic target.
- Allosteric inhibitors offer a promising strategy for targeting SHP2, overcoming limitations of catalytic site inhibitors.
Purpose of the Study:
- To investigate the interaction models of SHP2 allosteric inhibitors using molecular dynamics simulations.
- To explore the free energy landscape of SHP2 activation and understand its conformational changes.
- To apply interpretable machine learning for analyzing simulation data and identifying key structural drivers.
Main Methods:
- Molecular dynamics (MD) simulations to model inhibitor-SHP2 interactions.
- Meta-dynamics simulations to map the free energy landscape of SHP2 activation.
- Extreme Gradient Boosting (XGBoost) with Shapley Additive Explanations (SHAP) for analyzing simulation trajectories.
Main Results:
- Identified key structural features governing SHP2 conformational dynamics.
- Elucidated the mechanism of SHP2 activation and allosteric inhibition.
- Highlighted critical interactions for designing potent SHP2 allosteric inhibitors.
Conclusions:
- Advanced understanding of SHP2 allosteric inhibitor mechanisms.
- Provided crucial insights for developing novel SHP2-targeted cancer therapies.
- Offered strategies to address drug resistance in SHP2-targeted treatments.
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