Protein Tyrosine Phosphatase, Non-Receptor Type 11

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Study on SHP2 Conformational Transition and Structural Characterization of Its High-Potency Allosteric Inhibitors by Molecular Dynamics Simulations Combined with Machine Learning.

Molecules (Basel, Switzerland) Dec 24, 2024

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 im...

Humans Machine Learning Protein Binding Molecular Dynamics Simulation Enzyme Inhibitors Protein Conformation Allosteric Regulation Protein Tyrosine Phosphatase, Non-Receptor Type 11

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Study on the allosteric activation mechanism of SHP2 elastic network models and neural relational inference molecular dynamics simulation.

Physical chemistry chemical physics : PCCP Sep 13, 2023

As a ubiquitous protein tyrosine phosphatase, SHP2 is involved in PD-1/PD-L1 mediated tumor immune escape and undergoes substantial conformational changes. Therefore, it is considered an ideal target for tumor intervention. However, the allosteric me...

Artificial Intelligence Molecular Dynamics Simulation Programmed Cell Death 1 Receptor Allosteric Regulation Protein Tyrosine Phosphatase, Non-Receptor Type 11

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Development and validation of machine learning models for the prediction of SH-2 containing protein tyrosine phosphatase 2 inhibitors.

Molecular diversity Aug 8, 2023

Discovery and development of a new drug to the market is a highly challenging and resource consuming process. Although, modern drug discovery technologies have enabled the rapid identification of lead compounds, translation of the lead compounds into...

Humans Machine Learning Reproducibility of Results Drug Discovery Models, Molecular Enzyme Inhibitors Small Molecule Libraries Protein Tyrosine Phosphatase, Non-Receptor Type 11

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AIMC Topic: Protein Tyrosine Phosphatase, Non-Receptor Type 11

Study on SHP2 Conformational Transition and Structural Characterization of Its High-Potency Allosteric Inhibitors by Molecular Dynamics Simulations Combined with Machine Learning.

Study on the allosteric activation mechanism of SHP2 elastic network models and neural relational inference molecular dynamics simulation.

Development and validation of machine learning models for the prediction of SH-2 containing protein tyrosine phosphatase 2 inhibitors.

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AIMC Topic: Protein Tyrosine Phosphatase, Non-Receptor Type 11

Study on SHP2 Conformational Transition and Structural Characterization of Its High-Potency Allosteric Inhibitors by Molecular Dynamics Simulations Combined with Machine Learning.

Study on the allosteric activation mechanism of SHP2 elastic network models and neural relational inference molecular dynamics simulation.

Development and validation of machine learning models for the prediction of SH-2 containing protein tyrosine phosphatase 2 inhibitors.

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