Presence of intrinsically disordered proteins can inhibit the nucleation phase of amyloid fibril formation of Aβ(1–42) in amino acid sequence independent manner

In recent years, there has been a growing understanding that a significant fraction of the eukaryotic proteome is intrinsically disordered, and that these conformationally dynamic proteins play a myriad of vital biological roles in both normal and pathological states. In this review, selected examples of intrinsically disordered proteins are highlighted, with particular attention for a few which are relevant in neurological disorders and in viral infection. Next, the underlying causes for intrinsic disorder are discussed, along with computational methods used to predict whether a given amino acid sequence is likely to adopt a folded or unfolded state in solution. Finally, biophysical methods for the analysis of intrinsically disordered proteins will be discussed, as well as the unique challenges they pose in this context due to their highly dynamic nature.

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Proteus: A Random Forest Classifier to Predict Disorder-to-Order Transitioning Binding Regions in Intrinsically Disordered Proteins

10.1101/080788 ◽

2016 ◽

Author(s):

Sankar Basu ◽

Fredrik Söderquist ◽

Björn Wallner

Keyword(s):

Amino Acid ◽

Random Forest ◽

Amino Acid Sequence ◽

Intrinsically Disordered Proteins ◽

Random Forest Classifier ◽

Amino Acid Sequences ◽

Order Transition ◽

Disordered Proteins ◽

Data Set ◽

Intrinsically Disordered

AbstractThe focus of the computational structural biology community has taken a dramatic shift over the past one-and-a-half decades from the classical protein structure prediction problem to the possible understanding of intrinsically disordered proteins (IDP) or proteins containing regions of disorder (IDPR). The current interest lies in the unraveling of a disorder-to-order transitioning code embedded in the amino acid sequences of IDPs / IDPRs. Disordered proteins are characterized by an enormous amount of structural plasticity which makes them promiscuous in binding to different partners, multi-functional in cellular activity and atypical in folding energy landscapes resembling partially folded molten globules. Also, their involvement in several deadly human diseases (e.g. cancer, cardiovascular and neurodegenerative diseases) makes them attractive drug targets, and important for a biochemical understanding of the disease(s). The study of the structural ensemble of IDPs is rather difficult, in particular for transient interactions. When bound to a structured partner, an IDPR adapts an ordered conformation in the complex. The residues that undergo this disorder-to-order transition are called protean residues, generally found in short contiguous stretches and the first step in understanding the modus operandi of an IDP / IDPR would be to predict these residues. There are a few available methods which predict these protean segments from their amino acid sequences; however, their performance reported in the literature leaves clear room for improvement. With this background, the current study presents 'Proteus', a random forest classifier that predicts the likelihood of a residue undergoing a disorder-to-order transition upon binding to a potential partner protein. The prediction is based on features that can be calculated using the amino acid sequence alone. Proteus compares favorably with existing methods predicting twice as many true positives as the second best method (55% vs. 27%) with a much higher precision on an independent data set. The current study also sheds some light on a possible 'disorder-to-order' transitioning consensus, untangled, yet embedded in the amino acid sequence of IDPs. Some guidelines have also been suggested for proceeding with a real-life structural modeling involving an IDPR using Proteus.Software Availabilityhttps://github.com/bjornwallner/proteus

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Amino acid sequence determinants and molecular chaperones in amyloid fibril formation

Biochemical and Biophysical Research Communications ◽

10.1016/j.bbrc.2010.02.105 ◽

2010 ◽

Vol 396 (1) ◽

pp. 2-6 ◽

Cited By ~ 22

Author(s):

Charlotte Nerelius ◽

Michael Fitzen ◽

Jan Johansson

Keyword(s):

Amino Acid ◽

Amino Acid Sequence ◽

Molecular Chaperones ◽

Amyloid Fibril ◽

Fibril Formation ◽

Amyloid Fibril Formation

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Faculty Opinions recommendation of Structure-based design of non-natural amino-acid inhibitors of amyloid fibril formation.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.11466956.14747140 ◽

2011 ◽

Author(s):

Francis Tsai ◽

Amadeo Biter

Keyword(s):

Amino Acid ◽

Amyloid Fibril ◽

Fibril Formation ◽

Natural Amino Acid ◽

Amyloid Fibril Formation

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Sequence Versus Composition: What Prescribes IDP Biophysical Properties?

Entropy ◽

10.3390/e21070654 ◽

2019 ◽

Vol 21 (7) ◽

pp. 654 ◽

Cited By ~ 2

Author(s):

Jiří Vymětal ◽

Jiří Vondrášek ◽

Klára Hlouchová

Keyword(s):

Amino Acid ◽

Secondary Structure ◽

Intrinsically Disordered Proteins ◽

Random Sequence ◽

Bioinformatic Analysis ◽

Globular Proteins ◽

Disordered Proteins ◽

Compositional Bias ◽

Intrinsically Disordered ◽

Sequence Versus

Intrinsically disordered proteins (IDPs) represent a distinct class of proteins and are distinguished from globular proteins by conformational plasticity, high evolvability and a broad functional repertoire. Some of their properties are reminiscent of early proteins, but their abundance in eukaryotes, functional properties and compositional bias suggest that IDPs appeared at later evolutionary stages. The spectrum of IDP properties and their determinants are still not well defined. This study compares rudimentary physicochemical properties of IDPs and globular proteins using bioinformatic analysis on the level of their native sequences and random sequence permutations, addressing the contributions of composition versus sequence as determinants of the properties. IDPs have, on average, lower predicted secondary structure contents and aggregation propensities and biased amino acid compositions. However, our study shows that IDPs exhibit a broad range of these properties. Induced fold IDPs exhibit very similar compositions and secondary structure/aggregation propensities to globular proteins, and can be distinguished from unfoldable IDPs based on analysis of these sequence properties. While amino acid composition seems to be a major determinant of aggregation and secondary structure propensities, sequence randomization does not result in dramatic changes to these properties, but for both IDPs and globular proteins seems to fine-tune the tradeoff between folding and aggregation.

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Analysis of Heterodimeric “Mutual Synergistic Folding”-Complexes

International Journal of Molecular Sciences ◽

10.3390/ijms20205136 ◽

2019 ◽

Vol 20 (20) ◽

pp. 5136 ◽

Cited By ~ 3

Author(s):

Mentes ◽

Magyar ◽

Fichó ◽

Simon

Keyword(s):

Amino Acid ◽

Amino Acid Composition ◽

Acid Composition ◽

Intrinsically Disordered Proteins ◽

Driving Forces ◽

Disordered Proteins ◽

Subunit Interactions ◽

Amino Acid Compositions ◽

Intrinsically Disordered ◽

Β Sheet

Several intrinsically disordered proteins (IDPs) are capable to adopt stable structures without interacting with a folded partner. When the folding of all interacting partners happens at the same time, coupled with the interaction in a synergistic manner, the process is called Mutual Synergistic Folding (MSF). These complexes represent a discrete subset of IDPs. Recently, we collected information on their complexes and created the MFIB (Mutual Folding Induced by Binding) database. In a previous study, we compared homodimeric MSF complexes with homodimeric and monomeric globular proteins with similar amino acid sequence lengths. We concluded that MSF homodimers, compared to globular homodimeric proteins, have a greater solvent accessible main-chain surface area on the contact surface of the subunits, which becomes buried during dimerization. The main driving force of the folding is the mutual shielding of the water-accessible backbones, but the formation of further intermolecular interactions can also be relevant. In this paper, we will report analyses of heterodimeric MSF complexes. Our results indicate that the amino acid composition of the heterodimeric MSF monomer subunits slightly diverges from globular monomer proteins, while after dimerization, the amino acid composition of the overall MSF complexes becomes more similar to overall amino acid compositions of globular complexes. We found that inter-subunit interactions are strengthened, and additionally to the shielding of the solvent accessible backbone, other factors might play an important role in the stabilization of the heterodimeric structures, likewise energy gain resulting from the interaction of the two subunits with different amino acid compositions. We suggest that the shielding of the β-sheet backbones and the formation of a buried structural core along with the general strengthening of inter-subunit interactions together could be the driving forces of MSF protein structural ordering upon dimerization.

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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 ◽

10.1142/s0219720019500045 ◽

2019 ◽

Vol 17 (01) ◽

pp. 1950004 ◽

Cited By ~ 2

Author(s):

Chun Fang ◽

Yoshitaka Moriwaki ◽

Aikui Tian ◽

Caihong Li ◽

Kentaro Shimizu

Keyword(s):

Neural Network ◽

Amino Acid ◽

Convolutional Neural Network ◽

Intrinsically Disordered Proteins ◽

Protein Sequences ◽

Interaction Network ◽

Deep Convolutional Neural Network ◽

Disordered Proteins ◽

Related Factors ◽

Intrinsically Disordered

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 MoRFs is essential for both functional studies of IDPs and drug design. This study adopts the cutting-edge machine learning method of artificial intelligence to develop a powerful model for improving MoRFs prediction. We proposed a method, named as en_DCNNMoRF (ensemble deep convolutional neural network-based MoRF predictor). It combines the outcomes of two independent deep convolutional neural network (DCNN) classifiers that take advantage of different features. The first, DCNNMoRF1, employs position-specific scoring matrix (PSSM) and 22 types of amino acid-related factors to describe protein sequences. The second, DCNNMoRF2, employs PSSM and 13 types of amino acid indexes to describe protein sequences. For both single classifiers, DCNN with a novel two-dimensional attention mechanism was adopted, and an average strategy was added to further process the output probabilities of each DCNN model. Finally, en_DCNNMoRF combined the two models by averaging their final scores. When compared with other well-known tools applied to the same datasets, the accuracy of the novel proposed method was comparable with that of state-of-the-art methods. The related web server can be accessed freely via http://vivace.bi.a.u-tokyo.ac.jp:8008/fang/en_MoRFs.php .

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Inhibition of Amyloid Fibril Formation of Human Amylin by N-Alkylated Amino Acid and -Hydroxy Acid Residue Containing Peptides

Chemistry - A European Journal ◽

10.1002/1521-3765(20020916)8:18<4285::aid-chem4285>3.0.co;2-0 ◽

2002 ◽

Vol 8 (18) ◽

pp. 4285-4291 ◽

Cited By ~ 55

Author(s):

Dirk T. S. Rijkers ◽

Jo W. M. Höppener ◽

George Posthuma ◽

Cornelis J. M. Lips ◽

Rob M. J. Liskamp

Keyword(s):

Amino Acid ◽

Hydroxy Acid ◽

Amyloid Fibril ◽

Fibril Formation ◽

Amyloid Fibril Formation ◽

Human Amylin

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Exclusively Heteronuclear13C-Detected Amino-Acid-Selective NMR Experiments for the Study of Intrinsically Disordered Proteins (IDPs)

ChemBioChem ◽

10.1002/cbic.201200447 ◽

2012 ◽

Vol 13 (16) ◽

pp. 2425-2432 ◽

Cited By ~ 35

Author(s):

Wolfgang Bermel ◽

Ivano Bertini ◽

Jordan Chill ◽

Isabella C. Felli ◽

Noam Haba ◽

...

Keyword(s):

Amino Acid ◽

Intrinsically Disordered Proteins ◽

Disordered Proteins ◽

Intrinsically Disordered

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NOT THAT RIGID MIDGETS AND NOT SO FLEXIBLE GIANTS: ON THE ABUNDANCE AND ROLES OF INTRINSIC DISORDER IN SHORT AND LONG PROTEINS

Journal of Biological System ◽

10.1142/s0218339012400086 ◽

2012 ◽

Vol 20 (04) ◽

pp. 471-511 ◽

Cited By ~ 12

Author(s):

MARK HOWELL ◽

RYAN GREEN ◽

ALEXIS KILLEEN ◽

LAMAR WEDDERBURN ◽

VINCENT PICASCIO ◽

...

Keyword(s):

Amino Acid ◽

Intrinsically Disordered Proteins ◽

Biological Activities ◽

Intrinsic Disorder ◽

Amino Acid Sequences ◽

Disordered Proteins ◽

Biological Functions ◽

Intrinsically Disordered ◽

Eukaryotic Proteins ◽

Disordered Regions

Intrinsically disordered proteins or proteins with disordered regions are very common in nature. These proteins have numerous biological functions which are complementary to the biological activities of traditional ordered proteins. A noticeable difference in the amino acid sequences encoding long and short disordered regions was found and this difference was used in the development of length-dependent predictors of intrinsic disorder. In this study, we analyze the scaling of intrinsic disorder in eukaryotic proteins and investigate the presence of length-dependent functions attributed to proteins containing long disordered regions.

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