AIMC Topic: Intrinsically Disordered Proteins

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TIDGN: A Transfer Learning Framework for Predicting Interactions of Intrinsically Disordered Proteins with High Conformational Dynamics.

Journal of chemical information and modeling May 26, 2025
Interactions between intrinsically disordered proteins (IDPs) are crucial for biological processes, such as intracellular liquid-liquid phase separation (LLPS). Experiments (e.g., NMR) and simulations used to study IDP interactions encounter a variet...
Molecular Dynamics Simulation Machine Learning Intrinsically Disordered Proteins Protein Binding Protein Conformation
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Small Molecules Targeting the Structural Dynamics of AR-V7 Partially Disordered Proteins Using Deep Ensemble Docking.

Journal of chemical theory and computation May 13, 2025
The extensive conformational dynamics of partially disordered proteins hinders the efficiency of traditional in-silico structure-based drug discovery approaches due to the challenge of screening large chemical spaces of compounds, albeit with an exce...
Molecular Dynamics Simulation Intrinsically Disordered Proteins Molecular Docking Simulation Binding Sites Small Molecule Libraries Receptors, Androgen Protein Conformation Humans
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IDP-EDL: enhancing intrinsically disordered protein prediction by combining protein language model and ensemble deep learning.

Briefings in bioinformatics Mar 4, 2025
Identification of intrinsically disordered regions (IDRs) in proteins is essential for understanding fundamental cellular processes. The IDRs can be divided into long disordered regions (LDRs) and short disordered regions (SDRs) according to their le...
Software Computational Biology Databases, Protein Algorithms Deep Learning Intrinsically Disordered Proteins
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AIUPred: combining energy estimation with deep learning for the enhanced prediction of protein disorder.

Nucleic acids research Jul 5, 2024
Intrinsically disordered proteins and protein regions (IDPs/IDRs) carry out important biological functions without relying on a single well-defined conformation. As these proteins are a challenge to study experimentally, computational methods play im...
Thermodynamics Binding Sites Computational Biology Internet Intrinsically Disordered Proteins Protein Conformation Software Deep Learning
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DeepDISOBind: accurate prediction of RNA-, DNA- and protein-binding intrinsically disordered residues with deep multi-task learning.

Briefings in bioinformatics Jan 17, 2022
Proteins with intrinsically disordered regions (IDRs) are common among eukaryotes. Many IDRs interact with nucleic acids and proteins. Annotation of these interactions is supported by computational predictors, but to date, only one tool that predicts...
Nucleic Acids Humans Neural Networks, Computer Deep Learning Protein Binding DNA DNA-Binding Proteins RNA Intrinsically Disordered Proteins RNA-Binding Proteins Computational Biology Proteome
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IDRMutPred: predicting disease-associated germline nonsynonymous single nucleotide variants (nsSNVs) in intrinsically disordered regions.

Bioinformatics (Oxford, England) Dec 22, 2020
MOTIVATION: Despite of the lack of folded structure, intrinsically disordered regions (IDRs) of proteins play versatile roles in various biological processes, and many nonsynonymous single nucleotide variants (nsSNVs) in IDRs are associated with huma...
Algorithms Humans Nucleotides Sequence Alignment Machine Learning Intrinsically Disordered Proteins Germ Cells
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Identifying short disorder-to-order binding regions in disordered proteins with a deep convolutional neural network method.

Journal of bioinformatics and computational biology Feb 1, 2019
Molecular recognition features (MoRFs) are key functional regions of intrinsically disordered proteins (IDPs), which play important roles in the molecular interaction network of cells and are implicated in many serious human diseases. Identifying MoR...
Intrinsically Disordered Proteins Protein Binding Binding Sites Computational Biology Amino Acid Sequence Membrane Proteins Neural Networks, Computer Humans Databases, Protein Deep Learning
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