AIMC Topic: Intrinsically Disordered Proteins

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cnnAlpha: Protein disordered regions prediction by reduced amino acid alphabets and convolutional neural networks.

Proteins Aug 7, 2020
Intrinsically disordered regions (IDR) play an important role in key biological processes and are closely related to human diseases. IDRs have great potential to serve as targets for drug discovery, most notably in disordered binding regions. Accurat...
ROC Curve Computational Biology Area Under Curve Humans Neural Networks, Computer Machine Learning Datasets as Topic Intrinsically Disordered Proteins Sequence Analysis, Protein Multifactor Dimensionality Reduction Benchmarking Amino Acid Sequence Data Mining
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SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning.

Genomics, proteomics & bioinformatics Mar 13, 2020
Intrinsically disordered or unstructured proteins (or regions in proteins) have been found to be important in a wide range of biological functions and implicated in many diseases. Due to the high cost and low efficiency of experimental determination ...
Internet Deep Learning Amino Acid Sequence Computational Biology Intrinsically Disordered Proteins Evolution, Molecular
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Sequence-Based Prediction of Fuzzy Protein Interactions.

Journal of molecular biology Feb 27, 2020
It is becoming increasingly recognised that disordered proteins may be fuzzy, in that they can exhibit a wide variety of binding modes. In addition to the well-known process of folding upon binding (disorder-to-order transition), many examples are em...
Humans Algorithms Intrinsically Disordered Proteins Protein Conformation Protein Folding Sequence Analysis, Protein Protein Interaction Domains and Motifs Sequence Homology Protein Binding Models, Molecular Fuzzy Logic Protein Domains Databases, Protein Amino Acid Sequence
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Decision-Tree Based Meta-Strategy Improved Accuracy of Disorder Prediction and Identified Novel Disordered Residues Inside Binding Motifs.

International journal of molecular sciences Oct 7, 2018
Using computational techniques to identify intrinsically disordered residues is practical and effective in biological studies. Therefore, designing novel high-accuracy strategies is always preferable when existing strategies have a lot of room for im...
Humans Sequence Analysis, Protein Neural Networks, Computer Software Intrinsically Disordered Proteins
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MoRFPred-plus: Computational Identification of MoRFs in Protein Sequences using Physicochemical Properties and HMM profiles.

Journal of theoretical biology Oct 16, 2017
MOTIVATION: Intrinsically Disordered Proteins (IDPs) lack stable tertiary structure and they actively participate in performing various biological functions. These IDPs expose short binding regions called Molecular Recognition Features (MoRFs) that p...
Amino Acid Sequence Intrinsically Disordered Proteins Binding Sites Models, Theoretical Support Vector Machine Protein Domains Algorithms Protein Binding Computational Biology
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The Thermodynamic Basis of the Fuzzy Interaction of an Intrinsically Disordered Protein.

Angewandte Chemie (International ed. in English) Oct 10, 2017
Many intrinsically disordered proteins (IDP) that fold upon binding retain conformational heterogeneity in IDP-target complexes. The thermodynamics of such fuzzy interactions is poorly understood. Herein we introduce a thermodynamic framework, based ...
Calorimetry Circular Dichroism Intrinsically Disordered Proteins Thermodynamics Protein Folding Protein Binding Fuzzy Logic Models, Molecular Kinetics Molecular Dynamics Simulation Amino Acid Sequence
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Predicting MoRFs in protein sequences using HMM profiles.

BMC bioinformatics Dec 22, 2016
BACKGROUND: Intrinsically Disordered Proteins (IDPs) lack an ordered three-dimensional structure and are enriched in various biological processes. The Molecular Recognition Features (MoRFs) are functional regions within IDPs that undergo a disorder-t...
Support Vector Machine Algorithms Markov Chains Computational Biology Intrinsically Disordered Proteins Models, Theoretical Humans
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Predicting Protein-Protein Interaction Sites Using Sequence Descriptors and Site Propensity of Neighboring Amino Acids.

International journal of molecular sciences Oct 26, 2016
Information about the interface sites of Protein-Protein Interactions (PPIs) is useful for many biological research works. However, despite the advancement of experimental techniques, the identification of PPI sites still remains as a challenging tas...
Protein Interaction Maps Proteins Databases, Protein Amino Acids Models, Biological Intrinsically Disordered Proteins Humans Machine Learning Animals Protein Interaction Mapping Protein Interaction Domains and Motifs
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Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics.

PloS one Nov 10, 2015
We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec) to refer to biological sequences in general with protein-vectors (ProtVec) for proteins (amino-acid sequences) and gene-vectors (Gene...
Protein Structure, Secondary Genomics Nuclear Pore Complex Proteins Computational Biology Support Vector Machine Proteomics Natural Language Processing Proteins Amino Acid Sequence Databases, Protein Intrinsically Disordered Proteins
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DisPredict: A Predictor of Disordered Protein Using Optimized RBF Kernel.

PloS one Oct 30, 2015
Intrinsically disordered proteins or, regions perform important biological functions through their dynamic conformations during binding. Thus accurate identification of these disordered regions have significant implications in proper annotation of fu...
Intrinsically Disordered Proteins Algorithms Crystallography, X-Ray Protein Structure, Secondary Amino Acid Sequence Probability Datasets as Topic ROC Curve Support Vector Machine Area Under Curve
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