4.7 Article

CoMemMoRFPred: Sequence-based Prediction of MemMoRFs by Combining Predictors of Intrinsic Disorder, MoRFs and Disordered Lipid-binding Regions

Related references

Note: Only part of the references are listed.
Article Biochemistry & Molecular Biology

DeepPRObind: Modular Deep Learner that Accurately Predicts Structure and Disorder-Annotated Protein Binding Residues

Fuhao Zhang et al.

Summary: Current sequence-based predictors of protein-binding residues (PBRs) can be categorized into structure-trained and disorder-trained methods. However, these methods provide inaccurate results for the other annotation type. In this study, we propose a novel deep learning model, DeepPRObind, which accurately predicts both structured and disordered PBRs and outperforms existing predictors. We also validate the results of DeepPRObind using an analysis of putative PBRs in the yeast proteome.

JOURNAL OF MOLECULAR BIOLOGY (2023)

Review Biochemistry & Molecular Biology

Computational prediction of disordered binding regions

Sushmita Basu et al.

Summary: One important characteristic of intrinsically disordered regions (IDRs) is their ability to interact with various molecules. In recent years, the prediction of binding IDRs in protein sequences has become more significant. These prediction tools utilize various predictive architectures, including scoring functions, regular expressions, traditional and deep machine learning, and meta-models. Efforts are currently focused on developing deep neural network-based architectures and expanding the coverage to include RNA, DNA, and lipid-binding IDRs.

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2023)

Review Cell Biology

Intrinsically disordered proteins play diverse roles in cell signaling

Sarah E. Bondos et al.

Summary: Signaling pathways allow cells to detect and respond to various chemical and physical stimuli, forming a communication network that regulates cell activities and coordinates cell function. Successful signaling requires proteins that can form active and inactive states and engage in multiple interactions. Intrinsically disordered proteins play a critical role in cell signaling, present in diverse organisms and stages of signaling pathways.

CELL COMMUNICATION AND SIGNALING (2022)

Article Biochemical Research Methods

DisoLipPred: accurate prediction of disordered lipid-binding residues in protein sequences with deep recurrent networks and transfer learning

Akila Katuwawala et al.

Summary: DisoLipPred is the first predictor of disordered lipid-binding residues, utilizing innovative features including transfer learning, a bypass module, and expanded inputs to improve predictive quality. The results are accurate and surpass existing tools, providing complementary predictions to current methods.

BIOINFORMATICS (2022)

Article Biochemistry & Molecular Biology

Prediction of Disordered Regions in Proteins with Recurrent Neural Networks and Protein Dynamics

Gabriele Orlando et al.

Summary: The role of intrinsically disordered protein regions (IDRs) in cellular processes is becoming increasingly important, but accurately defining them remains a challenge. DisoMine is a method that predicts long disordered proteins using simple predictions of protein dynamics, secondary structure, and early folding, making it fast and applicable for large-scale screening.

JOURNAL OF MOLECULAR BIOLOGY (2022)

Review Cell Biology

Where protein structure and cell diversity meet

Jorge A. Holguin-Cruz et al.

Summary: Protein-protein interaction networks, or interactomes, are mapped to understand phenotypes and their alterations in diseases. Recent studies have found that interactomes vary greatly across different cell types and tissues due to protein-protein interaction rewiring. Alternative splicing and phosphorylation, which regulate protein structural and functional diversity, play key roles in defining cell type- and tissue-specific interactomes. Intrinsically disordered protein regions act as hubs for interactome rewiring.

TRENDS IN CELL BIOLOGY (2022)

Article Biochemical Research Methods

Resources for computational prediction of intrinsic disorder in proteins

Lukasz Kurgan

Summary: This review provides an overview of the development and practical resources in the field of intrinsic disorder prediction. These resources include predictors, meta webservers, databases, and quality assessment tools, which will facilitate the application of disorder predictions in various fields such as rational drug design, systems medicine, and structural genomics.

METHODS (2022)

Article Biochemistry & Molecular Biology

Compositional Bias of Intrinsically Disordered Proteins and Regions and Their Predictions

Bi Zhao et al.

Summary: This study analyzed the compositional biases of intrinsically disordered regions (IDRs) in protein sequences and identified variations between different classes of disorder. The accuracy of disorder predictions was found to be correlated with the correctness of the compositional bias, highlighting the importance of this bias. Predictive quality was lower for disorder classes with more different compositional bias from the generic disorder bias, while higher for classes with more similar bias. The study also discovered that different predictors perform best for different disorder classes, suggesting a need for new architectures that target specific disorder classes.

BIOMOLECULES (2022)

Article Biochemical Research Methods

CLIP: accurate prediction of disordered linear interacting peptides from protein sequences using co-evolutionary information

Zhenling Peng et al.

Summary: This paper introduces a new method for predicting intrinsically disordered regions (IDRs) called CLIP. CLIP uses inputs such as co-evolutionary information, physicochemical profiles, and disorder predictions to predict linear interacting peptides (LIPs) in protein sequences. Experimental results show that CLIP achieves good performance in predicting LIPs and outperforms current tools for predicting MoRFs and disordered protein-binding regions.

BRIEFINGS IN BIOINFORMATICS (2022)

Article Biochemistry & Molecular Biology

Deep learning in prediction of intrinsic disorder in proteins

Bi Zhao et al.

Summary: The study highlights the development and effectiveness of deep neural network (DNN)-based methods in intrinsic disorder prediction. The diversity in topologies, network sizes, and inputs suggests that deep learners are more accurate than other predictors. Well-rounded and accessible DNN-based predictors are popular and demonstrate the potential for future advancements in disorder prediction. The scarcity of DNN-based methods for predicting disordered binding regions is identified, emphasizing the need for more accurate prediction methods.

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2022)

Review Biochemical Research Methods

Surveying over 100 predictors of intrinsic disorder in proteins

Bi Zhao et al.

Summary: The field of intrinsic disorder prediction has seen a consistent trend of improvement in predictive quality with the development of newer and more advanced predictors. The focus has shifted from machine learning methods to meta-predictors in the early 2010s, and most recently to deep learning. The use of deep learners is expected to continue in the foreseeable future due to their recent success. Additionally, there is a wide range of resources available to facilitate accurate disorder predictions for users, including web servers, standalone programs, and databases of pre-computed predictions. Addressing the shortage of accurate methods for predicting disordered binding regions is also highlighted as a need.

EXPERT REVIEW OF PROTEOMICS (2021)

Article Biochemistry & Molecular Biology

MemDis: Predicting Disordered Regions in Transmembrane Proteins

Laszlo Dobson et al.

Summary: Transmembrane proteins play crucial roles in cells, with their functions often mediated by intrinsically disordered regions. MemDis, a novel prediction method utilizing convolutional neural network and long short-term memory networks, achieved the highest prediction accuracy on a specific dataset of TMPs. By defining TMP-specific features, MemDis further enhanced the accuracy of predicting disordered regions in TMPs compared to other popular IDR prediction methods.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2021)

Article Multidisciplinary Sciences

Intrinsic disorder in protein domains contributes to both organism complexity and clade-specific functions

Chao Gao et al.

Summary: The study reveals that intrinsic domain disorder is associated with both organism complexity and clade-specific functions. Additionally, the disorder degree of protein domains may differ in different clades, with some domains being highly disordered in specific clades.

SCIENTIFIC REPORTS (2021)

Editorial Material Biochemical Research Methods

A community effort to bring structure to disorder

Benjamin Lang et al.

NATURE METHODS (2021)

Article Biochemical Research Methods

Critical assessment of protein intrinsic disorder prediction

Marco Necci et al.

Summary: Intrinsically disordered proteins present a challenge to traditional protein structure-function analysis, with computational methods, particularly deep learning techniques, showing superior performance in predicting disorder. However, predicting disordered binding regions remains difficult, and there is a significant variation in computational times among methods.

NATURE METHODS (2021)

Article Biochemical Research Methods

DNAgenie: accurate prediction of DNA-type-specific binding residues in protein sequences

Jian Zhang et al.

Summary: Efforts to elucidate protein-DNA interactions at the molecular level rely on accurate predictions of DNA-binding residues in protein sequences. DNAgenie, a new predictor utilizing a custom-designed machine learning architecture, outperforms current methods in predicting residue-level interactions with A-DNA, B-DNA, and single-stranded DNA, reducing cross-predictions and generating promising leads for potential DNA-binding proteins.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Biochemistry & Molecular Biology

IUPred3: prediction of protein disorder enhanced with unambiguous experimental annotation and visualization of evolutionary conservation

Gabor Erdos et al.

Summary: Intrinsically disordered proteins and protein regions carry out important biological functions and exhibit multifaceted roles in evolutionary behavior. Computational methods, such as IUPred, play crucial roles in characterizing IDRs. The updated version of IUPred introduces new features to enhance prediction capabilities, including novel smoothing functions and tools for exploring evolutionary conservation of protein disorder.

NUCLEIC ACIDS RESEARCH (2021)

Article Multidisciplinary Sciences

flDPnn: Accurate intrinsic disorder prediction with putative propensities of disorder functions

Gang Hu et al.

Summary: flDPnn is a computational tool that provides accurate, fast and comprehensive disorder and disorder function predictions from protein sequences. Evaluation based on the CAID experiment and other test datasets demonstrates that flDPnn offers high predictive accuracy in predicting disorder, fully disordered proteins, and common disorder functions.

NATURE COMMUNICATIONS (2021)

Article Biochemistry & Molecular Biology

The MemMoRF database for recognizing disordered protein regions interacting with cellular membranes

Georgina Csizmadia et al.

Summary: Protein and lipid membrane interactions are vital for cellular processes, where Intrinsically Disordered Protein Regions (IDRs) play key roles. MemMoRFs are IDRs involved in disorder-to-order transitions induced by membrane lipids. Characterization of the dynamics of MemMoRFs involves secondary structure propensity and flexibility calculated from nuclear magnetic resonance chemical shifts.

NUCLEIC ACIDS RESEARCH (2021)

Article Biochemistry & Molecular Biology

Structural and functional analysis of non-smelly proteins

Jing Yan et al.

CELLULAR AND MOLECULAR LIFE SCIENCES (2020)

Review Biochemistry & Molecular Biology

Comprehensive Survey and Comparative Assessment of RNA-Binding Residue Predictions with Analysis by RNA Type

Kui Wang et al.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2020)

Review Biochemistry & Molecular Biology

Intrinsically disordered proteins and membranes: a marriage of convenience for cell signalling?

Jasmine Cornish et al.

BIOCHEMICAL SOCIETY TRANSACTIONS (2020)

Review Biochemical Research Methods

Accuracy of protein-level disorder predictions

Akila Katuwawala et al.

BRIEFINGS IN BIOINFORMATICS (2020)

Review Biochemistry & Molecular Biology

RNA-protein interactions: disorder, moonlighting and junk contribute to eukaryotic complexity

Anna Balcerak et al.

OPEN BIOLOGY (2019)

Article Multidisciplinary Sciences

rawMSA: End-to-end Deep Learning using raw Multiple Sequence Alignments

Claudio Mirabello et al.

PLOS ONE (2019)

Article Biochemistry & Molecular Biology

IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding

Balint Meszaros et al.

NUCLEIC ACIDS RESEARCH (2018)

Article Biochemical Research Methods

A comprehensive assessment of long intrinsic protein disorder from the DisProt database

Marco Necci et al.

BIOINFORMATICS (2018)

Article Biochemistry & Molecular Biology

Functional Analysis of Human Hub Proteins and Their Interactors Involved in the Intrinsic Disorder-Enriched Interactions

Gang Hu et al.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2017)

Review Biochemistry & Molecular Biology

Functions of intrinsic disorder in transmembrane proteins

Magnus Kjaergaard et al.

CELLULAR AND MOLECULAR LIFE SCIENCES (2017)

Review Biochemistry & Molecular Biology

Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions

Fanchi Meng et al.

CELLULAR AND MOLECULAR LIFE SCIENCES (2017)

Article Biochemistry & Molecular Biology

Mechanistic roles of protein disorder within transcription

Sarah L. Shammas

CURRENT OPINION IN STRUCTURAL BIOLOGY (2017)

Review Biochemistry & Molecular Biology

The contribution of intrinsically disordered regions to protein function, cellular complexity, and human disease

M. Madan Babu

BIOCHEMICAL SOCIETY TRANSACTIONS (2016)

Review Biochemistry & Molecular Biology

A structural perspective of RNA recognition by intrinsically disordered proteins

Sushmita Basu et al.

CELLULAR AND MOLECULAR LIFE SCIENCES (2016)

Article Biochemistry & Molecular Biology

Molecular recognition features (MoRFs) in three domains of life

Jing Yan et al.

MOLECULAR BIOSYSTEMS (2016)

Article Biochemistry & Molecular Biology

MoRFchibi SYSTEM: software tools for the identification of MoRFs in protein sequences

Nawar Malhis et al.

NUCLEIC ACIDS RESEARCH (2016)

Article Multidisciplinary Sciences

Intrinsic Disorder in Transmembrane Proteins: Roles in Signaling and Topology Prediction

Jerome Burgi et al.

PLOS ONE (2016)

Article Biochemistry & Molecular Biology

High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder

Zhenling Peng et al.

NUCLEIC ACIDS RESEARCH (2015)

Review Biochemistry & Molecular Biology

Emerging Roles of Disordered Sequences in RNA-Binding Proteins

Sara Calabretta et al.

TRENDS IN BIOCHEMICAL SCIENCES (2015)

Article Biochemical Research Methods

Comprehensive large-scale assessment of intrinsic protein disorder

Ian Walsh et al.

BIOINFORMATICS (2015)

Article Biochemistry & Molecular Biology

Exceptionally abundant exceptions: comprehensive characterization of intrinsic disorder in all domains of life

Zhenling Peng et al.

CELLULAR AND MOLECULAR LIFE SCIENCES (2015)

Review Chemistry, Multidisciplinary

Introducing Protein Intrinsic Disorder

Johnny Habchi et al.

CHEMICAL REVIEWS (2014)

Article Pharmacology & Pharmacy

Intrinsic Disorder-based Protein Interactions and their Modulators

Vladimir N. Uversky

CURRENT PHARMACEUTICAL DESIGN (2013)

Article Biochemistry & Molecular Biology

Exploring the binding diversity of intrinsically disordered proteins involved in one-to-many binding

Wei-Lun Hsu et al.

PROTEIN SCIENCE (2013)

Article Biochemical Research Methods

ESpritz: accurate and fast prediction of protein disorder

Ian Walsh et al.

BIOINFORMATICS (2012)

Article Biochemical Research Methods

CD-HIT: accelerated for clustering the next-generation sequencing data

Limin Fu et al.

BIOINFORMATICS (2012)

Review Biochemistry & Molecular Biology

Comprehensive Comparative Assessment of In-Silico Predictors of Disordered Regions

Zhen-Ling Peng et al.

CURRENT PROTEIN & PEPTIDE SCIENCE (2012)

Article Biochemistry & Molecular Biology

Direct MinE-membrane interaction contributes to the proper localization of MinDE in E. coli

Cheng-Wei Hsieh et al.

MOLECULAR MICROBIOLOGY (2010)

Article Biochemical Research Methods

ANCHOR: web server for predicting protein binding regions in disordered proteins

Zsuzsanna Dosztanyi et al.

BIOINFORMATICS (2009)

Review Cell Biology

Predicting intrinsic disorder in proteins: an overview

Bo He et al.

CELL RESEARCH (2009)

Article Biochemistry & Molecular Biology

TOP-IDP-scale: A new amino acid scale measuring propensity for intrinsic disorder

Andrew Campen et al.

PROTEIN AND PEPTIDE LETTERS (2008)

Review Biochemistry & Molecular Biology

Fuzzy complexes: polymorphism and structural disorder in protein-protein interactions

Peter Tompa et al.

TRENDS IN BIOCHEMICAL SCIENCES (2008)

Article Biochemical Research Methods

Characterization of molecular recognition features, MoRFs, and their binding partners

Vladimir Vacic et al.

JOURNAL OF PROTEOME RESEARCH (2007)

Review Biochemistry & Molecular Biology

Analysis of molecular recognition features (MoRFs)

Amrita Mohan et al.

JOURNAL OF MOLECULAR BIOLOGY (2006)

Article Computer Science, Artificial Intelligence

An introduction to ROC analysis

Tom Fawcett

PATTERN RECOGNITION LETTERS (2006)

Review Cell Biology

Intrinsically unstructured proteins and their functions

HJ Dyson et al.

NATURE REVIEWS MOLECULAR CELL BIOLOGY (2005)

Review Biochemistry & Molecular Biology

Showing your ID: intrinsic disorder as an ID for recognition, regulation and cell signaling

VN Uversky et al.

JOURNAL OF MOLECULAR RECOGNITION (2005)

Article Multidisciplinary Sciences

Simulating disorder-order transitions in molecular recognition of unstructured proteins: Where folding meets binding

GM Verkhivker et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2003)

Review Biochemistry & Molecular Biology

Intrinsic disorder and protein function

AK Dunker et al.

BIOCHEMISTRY (2002)

Article Biochemical Research Methods

Intrinsically disordered protein

AK Dunker et al.

JOURNAL OF MOLECULAR GRAPHICS & MODELLING (2001)