AIMC Topic: Intrinsically Disordered Proteins

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Divergence in a eukaryotic transcription factor's co-TF dependence involves multiple intrinsically disordered regions.

Nature communications Jun 18, 2025
Combinatorial control by transcription factors (TFs) is central to eukaryotic gene regulation, yet its mechanism, evolution, and regulatory impact are not well understood. Here we use natural variation in the yeast phosphate starvation (PHO) response...
Candida glabrata Saccharomyces cerevisiae Proteins DNA-Binding Proteins Intrinsically Disordered Proteins Saccharomyces cerevisiae Gene Expression Regulation, Fungal Phosphates Protein Binding Transcription Factors
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Deciphering disordered regions controlling mRNA decay in high-throughput.

Nature Apr 23, 2025
Intrinsically disordered regions within proteins drive specific molecular functions despite lacking a defined structure. Although disordered regions are integral to controlling mRNA stability and translation, the mechanisms underlying these regulator...
Humans Machine Learning RNA, Messenger Mutagenesis High-Throughput Screening Assays Protein Biosynthesis Intrinsically Disordered Proteins RNA Stability
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Deep learning tools predict variants in disordered regions with lower sensitivity.

BMC genomics Apr 12, 2025
BACKGROUND: The recent AI breakthrough of AlphaFold2 has revolutionized 3D protein structural modeling, proving crucial for protein design and variant effects prediction. However, intrinsically disordered regions-known for their lack of well-defined ...
Intrinsically Disordered Proteins Methionine Protein Conformation, alpha-Helical Models, Molecular Mutation Humans Computational Biology Proteome Deep Learning
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Deep Learning-Based Comparative Prediction and Functional Analysis of Intrinsically Disordered Regions in SARS-CoV-2.

International journal of molecular sciences Apr 5, 2025
This study explores the role of intrinsically disordered regions (IDRs) in the SARS-CoV-2 proteome and their potential as targets for small-molecule drug discovery. Experimentally validated intrinsic disordered regions from the literature were utiliz...
Viroporin Proteins Deep Learning Intrinsically Disordered Proteins Humans Viral Proteins COVID-19 SARS-CoV-2
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Machine learning methods to study sequence-ensemble-function relationships in disordered proteins.

Current opinion in structural biology Mar 12, 2025
Recent years have seen tremendous developments in the use of machine learning models to link amino-acid sequence, structure, and function of folded proteins. These methods are, however, rarely applicable to the wide range of proteins and sequences th...
Computational Biology Models, Molecular Amino Acid Sequence Humans Machine Learning Protein Folding Intrinsically Disordered Proteins Protein Conformation
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Accelerated Missense Mutation Identification in Intrinsically Disordered Proteins Using Deep Learning.

Biomacromolecules Mar 12, 2025
We use a combination of Brownian dynamics (BD) simulation results and deep learning (DL) strategies for the rapid identification of large structural changes caused by missense mutations in intrinsically disordered proteins (IDPs). We used ∼6500 IDP s...
Humans Neural Networks, Computer Deep Learning Molecular Dynamics Simulation Algorithms Intrinsically Disordered Proteins Mutation, Missense
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PredIDR2: Improving accuracy of protein intrinsic disorder prediction by updating deep convolutional neural network and supplementing DisProt data.

International journal of biological macromolecules Mar 5, 2025
Intrinsically disordered proteins (IDPs) or regions (IDRs) are widespread in proteomes, and involved in several important biological processes and implicated in many diseases. Many computational methods for IDR prediction are being developed to decre...
ROC Curve Computational Biology Neural Networks, Computer Intrinsically Disordered Proteins Databases, Protein Software Convolutional Neural Networks
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Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning.

Journal of chemical information and modeling Feb 21, 2025
Proteins are inherently dynamic, and their conformational ensembles play a crucial role in biological function. Large-scale motions may govern the protein structure-function relationship, and numerous transient but stable conformations of intrinsical...
Molecular Dynamics Simulation Amyloid beta-Peptides Intrinsically Disordered Proteins Deep Learning Peptide Fragments Protein Conformation
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An integrated machine learning approach delineates an entropic expansion mechanism for the binding of a small molecule to α-synuclein.

eLife Dec 18, 2024
The mis-folding and aggregation of intrinsically disordered proteins (IDPs) such as α-synuclein (αS) underlie the pathogenesis of various neurodegenerative disorders. However, targeting αS with small molecules faces challenges due to the lack of defi...
Protein Conformation Thermodynamics 1-(5-Isoquinolinesulfonyl)-2-Methylpiperazine Entropy Protein Binding alpha-Synuclein Humans Intrinsically Disordered Proteins Machine Learning
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PICNIC accurately predicts condensate-forming proteins regardless of their structural disorder across organisms.

Nature communications Dec 11, 2024
Biomolecular condensates are membraneless organelles that can concentrate hundreds of different proteins in cells to operate essential biological functions. However, accurate identification of their components remains challenging and biased towards p...
Animals Computational Biology Intrinsically Disordered Proteins Proteome Humans Biomolecular Condensates Machine Learning Proteins Algorithms Amino Acid Sequence
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