AIMC Topic: Intrinsically Disordered Proteins

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PredIDR: Accurate prediction of protein intrinsic disorder regions using deep convolutional neural network.

International journal of biological macromolecules Nov 19, 2024
The involvement of protein intrinsic disorder in essential biological processes, it is well known in structural biology. However, experimental methods for detecting intrinsic structural disorder and directly measuring highly dynamic behavior of prote...
Neural Networks, Computer Software Proteins Databases, Protein Algorithms Computational Biology Intrinsically Disordered Proteins
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Emerging Frontiers in Conformational Exploration of Disordered Proteins: Integrating Autoencoder and Molecular Simulations.

ACS chemical neuroscience Nov 18, 2024
Intrinsically disordered proteins (IDPs) are closely associated with a number of neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease. Due to the highly dynamic nature of IDPs, their structural determination and conformatio...
Intrinsically Disordered Proteins Protein Conformation Machine Learning Molecular Dynamics Simulation Humans
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Deep learning for intrinsically disordered proteins: From improved predictions to deciphering conformational ensembles.

Current opinion in structural biology Nov 12, 2024
Intrinsically disordered proteins (IDPs) lack a stable three-dimensional structure under physiological conditions, challenging traditional structure-based prediction methods. This review explores how modern deep learning approaches, which have revolu...
Protein Conformation Models, Molecular Intrinsically Disordered Proteins Humans Deep Learning
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Physics-Based Machine Learning Trains Hamiltonians and Decodes the Sequence-Conformation Relation in the Disordered Proteome.

Journal of chemical theory and computation Nov 6, 2024
Intrinsically disordered proteins and regions (IDPs) are involved in vital biological processes. To understand the IDP function, often controlled by conformation, we need to find the link between sequence and conformation. We decode this link by inte...
Machine Learning Intrinsically Disordered Proteins Protein Conformation Static Electricity Proteome Molecular Dynamics Simulation
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Decoding Missense Variants by Incorporating Phase Separation via Machine Learning.

Nature communications Sep 27, 2024
Computational models have made significant progress in predicting the effect of protein variants. However, deciphering numerous variants of uncertain significance (VUS) located within intrinsically disordered regions (IDRs) remains challenging. To ad...
Mutation, Missense Phase Separation Humans Machine Learning Computational Biology Intrinsically Disordered Proteins
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Predicting Conformational Ensembles of Intrinsically Disordered Proteins: From Molecular Dynamics to Machine Learning.

The journal of physical chemistry letters Aug 2, 2024
Intrinsically disordered proteins and regions (IDP/IDRs) are ubiquitous across all domains of life. Characterized by a lack of a stable tertiary structure, IDP/IDRs populate a diverse set of transiently formed structural states that can promiscuously...
Intrinsically Disordered Proteins Protein Conformation Machine Learning Molecular Dynamics Simulation Humans
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Protein embeddings predict binding residues in disordered regions.

Scientific reports Jun 12, 2024
The identification of protein binding residues helps to understand their biological processes as protein function is often defined through ligand binding, such as to other proteins, small molecules, ions, or nucleotides. Methods predicting binding re...
Computational Biology Databases, Protein Binding Sites Machine Learning Intrinsically Disordered Proteins Humans Protein Binding
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Application of artificial intelligence and machine learning techniques to the analysis of dynamic protein sequences.

Proteins May 29, 2024
We apply methods of Artificial Intelligence and Machine Learning to protein dynamic bioinformatics. We rewrite the sequences of a large protein data set, containing both folded and intrinsically disordered molecules, using a representation developed ...
Databases, Protein Amino Acid Sequence Artificial Intelligence Protein Folding Computational Biology Machine Learning Intrinsically Disordered Proteins Sequence Analysis, Protein Proteins Algorithms Fourier Analysis
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MoRF_ESM: Prediction of MoRFs in disordered proteins based on a deep transformer protein language model.

Journal of bioinformatics and computational biology May 28, 2024
Molecular recognition features (MoRFs) are particular functional segments of disordered proteins, which play crucial roles in regulating the phase transition of membrane-less organelles and frequently serve as central sites in cellular interaction ne...
Intrinsically Disordered Proteins Computational Biology Algorithms Databases, Protein Deep Learning
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Transferable deep generative modeling of intrinsically disordered protein conformations.

PLoS computational biology May 23, 2024
Intrinsically disordered proteins have dynamic structures through which they play key biological roles. The elucidation of their conformational ensembles is a challenging problem requiring an integrated use of computational and experimental methods. ...
Computational Biology Databases, Protein Models, Molecular Intrinsically Disordered Proteins Algorithms Deep Learning Protein Conformation Neural Networks, Computer Machine Learning
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