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Intrinsically Disordered Proteins

Intrinsically Disordered Proteins

Intrinsically disordered proteins are a group of proteins that do not fold into specific three-dimensional structures. Their structural flexibility allows them to complement ordered proteins to perform functions that are inaccessible to rigid structures. They are more common in eukaryotes than prokaryotes and may either be exclusively intrinsically disordered or hybrid proteins, consisting of a mix of ordered and disordered regions. The absence of a rigid structure in these proteins can be...

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Related Experiment Video

Updated: Jun 7, 2026

Paramagnetic Relaxation Enhancement for Detecting and Characterizing Self-Associations of Intrinsically Disordered Proteins

Paramagnetic Relaxation Enhancement for Detecting and Characterizing Self-Associations of Intrinsically Disordered Proteins

Published on: September 23, 2021

Targeting the intrinsically disordered AR-NTD through a machine learning-based enhanced sampling workflow.

Kai Zhu^1,2,3, Huating Wang^1,2,3, Jintu Zhang^1,2,3

¹College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, China.

Nature Communications

|June 5, 2026

Summary

This summary is machine-generated.

Researchers developed a computational method to design drugs targeting the intrinsically disordered N-terminal domain of the androgen receptor (AR-NTD) in prostate cancer. This approach identified K53, a novel antagonist with potent anti-cancer activity against resistant cells.

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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Related Experiment Videos

Last Updated: Jun 7, 2026

Paramagnetic Relaxation Enhancement for Detecting and Characterizing Self-Associations of Intrinsically Disordered Proteins

Paramagnetic Relaxation Enhancement for Detecting and Characterizing Self-Associations of Intrinsically Disordered Proteins

Published on: September 23, 2021

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Area of Science:

Biochemistry
Computational Biology
Oncology

Background:

The androgen receptor N-terminal domain (AR-NTD) is a key target for prostate cancer therapy.
Its intrinsically disordered nature presents challenges for drug development, leading to resistance.
Developing new strategies to target the AR-NTD is crucial for overcoming treatment resistance.

Purpose of the Study:

To develop a computational workflow for identifying druggable conformations of the AR-NTD.
To elucidate the binding mechanism of AR-NTD modulators.
To discover novel AR-NTD antagonists for resistant prostate cancer.

Main Methods:

Utilized enhanced sampling techniques and machine learning for computational analysis.
Characterized metastable states of the AR-NTD Tau-5 region.
Performed structure-based virtual screening to identify potential drug candidates.

Main Results:

Identified nine metastable states of the AR-NTD Tau-5 region.
Revealed ligand recognition driven by π-π stacking and water-mediated hydrogen bonds.
Discovered K53, a novel AR-NTD antagonist with potent anti-proliferative activity in resistant prostate cancer cells.

Conclusions:

The study presents a successful computational paradigm for targeting intrinsically disordered proteins.
K53 demonstrates direct binding to AR-NTD, suppresses transcriptional activity, and shows cancer cell selectivity.
K53 represents a promising therapeutic candidate for treating resistant prostate cancer.