scholarly journals Conformational Entropy of Intrinsically Disordered Proteins from Amino Acid Triads

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Anupaul Baruah ◽  
Pooja Rani ◽  
Parbati Biswas
Entropy ◽  
2019 ◽  
Vol 21 (7) ◽  
pp. 654 ◽  
Author(s):  
Jiří Vymětal ◽  
Jiří Vondrášek ◽  
Klára Hlouchová

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.


2019 ◽  
Vol 20 (20) ◽  
pp. 5136 ◽  
Author(s):  
Mentes ◽  
Magyar ◽  
Fichó ◽  
Simon

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.


2019 ◽  
Vol 17 (01) ◽  
pp. 1950004 ◽  
Author(s):  
Chun Fang ◽  
Yoshitaka Moriwaki ◽  
Aikui Tian ◽  
Caihong Li ◽  
Kentaro Shimizu

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 .


Life ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 320
Author(s):  
Frederik Lermyte

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.


ChemBioChem ◽  
2012 ◽  
Vol 13 (16) ◽  
pp. 2425-2432 ◽  
Author(s):  
Wolfgang Bermel ◽  
Ivano Bertini ◽  
Jordan Chill ◽  
Isabella C. Felli ◽  
Noam Haba ◽  
...  

2012 ◽  
Vol 20 (04) ◽  
pp. 471-511 ◽  
Author(s):  
MARK HOWELL ◽  
RYAN GREEN ◽  
ALEXIS KILLEEN ◽  
LAMAR WEDDERBURN ◽  
VINCENT PICASCIO ◽  
...  

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.


Author(s):  
Kundlik Gadhave ◽  
Prateek Kumar ◽  
Ankur Kumar ◽  
Taniya Bhardwaj ◽  
Neha Garg ◽  
...  

AbstractThe intrinsically disordered proteins/regions (IDPs/IDPRs) are known to be responsible for multiple cellular processes and are associated with many chronic diseases. In viruses, the existence of disordered proteome is also proven and are related with its conformational dynamics inside the host. The SARS-CoV-2 virus has a large proteome, in which, structure and functions of many proteins are not known as of yet. Previously, we have investigated the dark proteome of SARS-CoV-2. However, the disorder status of non-structural protein 11 (nsp11) was not possible because of very small in size, just 13 amino acid long, and for most of the IDP predictors, the protein size should be at least 30 amino acid long. Also, the structural dynamics and function status of nsp11 was not known. Hence, we have performed extensive experimentation on nsp11. Our results, based on the Circular dichroism spectroscopy gives characteristic disordered spectrum for IDPs. Further, we investigated the conformational behaviour of nsp11 in the presence of membrane mimetic environment, alpha helix inducer, and natural osmolyte. In the presence of negatively charged and neutral liposomes, nsp11 remains disordered. However, with SDS micelle, it adopted an α-helical conformation, suggesting the helical propensity of nsp11. At the end, we again confirmed the IDP behaviour of nsp11 using molecular dynamics simulations.


2019 ◽  
Vol 55 (54) ◽  
pp. 7820-7823
Author(s):  
Sujeesh Sukumaran ◽  
Shahid A. Malik ◽  
Shankararama Sharma R. ◽  
Kousik Chandra ◽  
Hanudatta S. Atreya

An approach for rapid resonance assignments in proteins based on 2D13C-detected NMR experiments combined with amino acid selective unlabeling.


2012 ◽  
Vol 134 (36) ◽  
pp. 15138-15148 ◽  
Author(s):  
Valéry Ozenne ◽  
Robert Schneider ◽  
Mingxi Yao ◽  
Jie-rong Huang ◽  
Loïc Salmon ◽  
...  

Author(s):  
Andrei Vovk ◽  
Anton Zilman

AbstractUnlike the well defined structures of classical natively folded proteins, Intrinsically Disordered Proteins (IDP) and Intrinsically Disordered Regions (IDR) dynamically span large conformational and structural ensembles. This dynamic disorder impedes the study of the relationship between the amino acid sequences of the IDPs and their spatial structures, dynamics, and function. Multiple experimental and theoretical evidence points in many cases to the overall importance of the general properties of the amino acid sequence of the IPDs rather than their precise atomistic details. However, while different experimental techniques can probe aspects of the IDP conformations, often different techniques or conditions offer seemingly contradictory results. Using coarse-grained polymer models informed by experimental observations, we investigate the effects of several key variables on the dimensions and the dynamics of IDPs. The coarse-grained simulations are in a good agreement with the results of atomistic MD. We show that the sequence composition and patterning are well reflected in the global conformational variables such as the radius of gyration and hydrodynamic radius, while the end-to-end distance and dynamics are highly sequence specific. We identify the conditions that allow mapping of highly heterogeneous sequences of IDPs onto averaged minimal polymer models. We discuss the implications of these results for the interpretation of the recent experimental measurements, and for further development of appropriate mesoscopic models of IDPs.


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