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Information in Intrinsically Disordered Proteins and Complex Protein Networks

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Entropy and Biology".

Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 30659

Special Issue Editor


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Guest Editor
Department of Inorganic and Organic Chemistry, Universitat de Barcelona, 1-11 08028 Barcelon, Spain
Interests: intrinsically disordered proteins; protein dynamics; Src-protein kinases; nuclear magnetic resonance; one-dimensional encoding of structural and functional information

Special Issue Information

Dear Colleagues,

Intrinsically disordered proteins (IDP) challenge the classical paradigm that a well-defined folded structure is essential for functioning. Although the loss of a well-defined structure results in the loss of function in many proteins supporting the paradigm, about one third of eukaryotic proteins have long regions that do not adopt a single, well-defined structure in their native state, and another third are nearly completely disordered, yet have important functions. IDP appear functionally linked to complex regulation processes and protein networks. 

A new paradigm focusing on the information content encoded by proteins, folded or unfolded, and on their interaction networks is increasingly being recognized.

Classical, quasi-rigid structures represent one possible way of encoding information (like the shape of a key encodes the information to open a lock) but not the only one. If we accept that protein function is a manifestation of its information content, the key question to be answered is how the function-enabling information is encoded in disordered proteins and protein networks.

While the classical lock and key is hardware based, it is likely that the information in disordered proteins is more like a computer program that will interpret a number of cellular input signals to generate a context-dependent response.

In this Special Issue of Entropy, we invite contributions of basic questions related to the following: How is information encoded in the sequence of IDPs? How do conformational ensembles populated by these proteins contribute to the information flow from sequence to function?  What is the role of protein dynamics? How is entropy being modulated during the evolution of disordered proteins and their complexes? How are inter- and intra-molecular interaction networks interacting? Why have disordered proteins become essential for eukaryotic life? Is there a programming language for at least some families of intrinsically disordered proteins? Can we reverse engineer IDP software from the observed function?

Conceptual papers, reviews, and research papers presenting computer simulations or experimental approaches are welcome.

Prof. Dr. Miquel Pons
Guest Editor

Manuscript Submission Information

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Keywords

  • Intrinsically disordered proteins
  • Protein-Protein interaction networks
  • Protein dynamics
  • Network dynamics
  • Entropy in disordered protein complexes

Published Papers (7 papers)

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17 pages, 1960 KiB  
Article
Bayesian-Maximum-Entropy Reweighting of IDP Ensembles Based on NMR Chemical Shifts
by Ramon Crehuet, Pedro J. Buigues, Xavier Salvatella and Kresten Lindorff-Larsen
Entropy 2019, 21(9), 898; https://doi.org/10.3390/e21090898 - 17 Sep 2019
Cited by 26 | Viewed by 5076
Abstract
Bayesian and Maximum Entropy approaches allow for a statistically sound and systematic fitting of experimental and computational data. Unfortunately, assessing the relative confidence in these two types of data remains difficult as several steps add unknown error. Here we propose the use of [...] Read more.
Bayesian and Maximum Entropy approaches allow for a statistically sound and systematic fitting of experimental and computational data. Unfortunately, assessing the relative confidence in these two types of data remains difficult as several steps add unknown error. Here we propose the use of a validation-set method to determine the balance, and thus the amount of fitting. We apply the method to synthetic NMR chemical shift data of an intrinsically disordered protein. We show that the method gives consistent results even when other methods to assess the amount of fitting cannot be applied. Finally, we also describe how the errors in the chemical shift predictor can lead to an incorrect fitting and how using secondary chemical shifts could alleviate this problem. Full article
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13 pages, 563 KiB  
Article
Entropy, Fluctuations, and Disordered Proteins
by Eshel Faraggi, A. Keith Dunker, Robert L. Jernigan and Andrzej Kloczkowski
Entropy 2019, 21(8), 764; https://doi.org/10.3390/e21080764 - 06 Aug 2019
Cited by 3 | Viewed by 3039
Abstract
Entropy should directly reflect the extent of disorder in proteins. By clustering structurally related proteins and studying the multiple-sequence-alignment of the sequences of these clusters, we were able to link between sequence, structure, and disorder information. We introduced several parameters as measures of [...] Read more.
Entropy should directly reflect the extent of disorder in proteins. By clustering structurally related proteins and studying the multiple-sequence-alignment of the sequences of these clusters, we were able to link between sequence, structure, and disorder information. We introduced several parameters as measures of fluctuations at a given MSA site and used these as representative of the sequence and structure entropy at that site. In general, we found a tendency for negative correlations between disorder and structure, and significant positive correlations between disorder and the fluctuations in the system. We also found evidence for residue-type conservation for those residues proximate to potentially disordered sites. Mutation at the disorder site itself appear to be allowed. In addition, we found positive correlation for disorder and accessible surface area, validating that disordered residues occur in exposed regions of proteins. Finally, we also found that fluctuations in the dihedral angles at the original mutated residue and disorder are positively correlated while dihedral angle fluctuations in spatially proximal residues are negatively correlated with disorder. Our results seem to indicate permissible variability in the disordered site, but greater rigidity in the parts of the protein with which the disordered site interacts. This is another indication that disordered residues are involved in protein function. Full article
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16 pages, 992 KiB  
Article
Occurrence of Ordered and Disordered Structural Elements in Postsynaptic Proteins Supports Optimization for Interaction Diversity
by Annamária Kiss-Tóth, Laszlo Dobson, Bálint Péterfia, Annamária F. Ángyán, Balázs Ligeti, Gergely Lukács and Zoltán Gáspári
Entropy 2019, 21(8), 761; https://doi.org/10.3390/e21080761 - 06 Aug 2019
Cited by 3 | Viewed by 3106
Abstract
The human postsynaptic density is an elaborate network comprising thousands of proteins, playing a vital role in the molecular events of learning and the formation of memory. Despite our growing knowledge of specific proteins and their interactions, atomic-level details of their full three-dimensional [...] Read more.
The human postsynaptic density is an elaborate network comprising thousands of proteins, playing a vital role in the molecular events of learning and the formation of memory. Despite our growing knowledge of specific proteins and their interactions, atomic-level details of their full three-dimensional structure and their rearrangements are mostly elusive. Advancements in structural bioinformatics enabled us to depict the characteristic features of proteins involved in different processes aiding neurotransmission. We show that postsynaptic protein-protein interactions are mediated through the delicate balance of intrinsically disordered regions and folded domains, and this duality is also imprinted in the amino acid sequence. We introduce Diversity of Potential Interactions (DPI), a structure and regulation based descriptor to assess the diversity of interactions. Our approach reveals that the postsynaptic proteome has its own characteristic features and these properties reliably discriminate them from other proteins of the human proteome. Our results suggest that postsynaptic proteins are especially susceptible to forming diverse interactions with each other, which might be key in the reorganization of the postsynaptic density (PSD) in molecular processes related to learning and memory. Full article
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8 pages, 1594 KiB  
Communication
Sequence Versus Composition: What Prescribes IDP Biophysical Properties?
by Jiří Vymětal, Jiří Vondrášek and Klára Hlouchová
Entropy 2019, 21(7), 654; https://doi.org/10.3390/e21070654 - 03 Jul 2019
Cited by 7 | Viewed by 3858
Abstract
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 [...] Read more.
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. Full article
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11 pages, 2197 KiB  
Article
Prediction of MoRFs in Protein Sequences with MLPs Based on Sequence Properties and Evolution Information
by Hao He, Jiaxiang Zhao and Guiling Sun
Entropy 2019, 21(7), 635; https://doi.org/10.3390/e21070635 - 27 Jun 2019
Cited by 9 | Viewed by 2481
Abstract
Molecular recognition features (MoRFs) are one important type of intrinsically disordered proteins functional regions that can undergo a disorder-to-order transition through binding to their interaction partners. Prediction of MoRFs is crucial, as the functions of MoRFs are associated with many diseases and can [...] Read more.
Molecular recognition features (MoRFs) are one important type of intrinsically disordered proteins functional regions that can undergo a disorder-to-order transition through binding to their interaction partners. Prediction of MoRFs is crucial, as the functions of MoRFs are associated with many diseases and can therefore become the potential drug targets. In this paper, a method of predicting MoRFs is developed based on the sequence properties and evolutionary information. To this end, we design two distinct multi-layer perceptron (MLP) neural networks and present a procedure to train them. We develop a preprocessing process which exploits different sizes of sliding windows to capture various properties related to MoRFs. We then use the Bayes rule together with the outputs of two trained MLP neural networks to predict MoRFs. In comparison to several state-of-the-art methods, the simulation results show that our method is competitive. Full article
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14 pages, 2053 KiB  
Article
A Suggestion of Converting Protein Intrinsic Disorder to Structural Entropy Using Shannon’s Information Theory
by Hao-Bo Guo, Yue Ma, Gerald A. Tuskan, Hong Qin, Xiaohan Yang and Hong Guo
Entropy 2019, 21(6), 591; https://doi.org/10.3390/e21060591 - 14 Jun 2019
Cited by 2 | Viewed by 3446
Abstract
We propose a framework to convert the protein intrinsic disorder content to structural entropy (H) using Shannon’s information theory (IT). The structural capacity (C), which is the sum of H and structural information (I), is equal to [...] Read more.
We propose a framework to convert the protein intrinsic disorder content to structural entropy (H) using Shannon’s information theory (IT). The structural capacity (C), which is the sum of H and structural information (I), is equal to the amino acid sequence length of the protein. The structural entropy of the residues expands a continuous spectrum, ranging from 0 (fully ordered) to 1 (fully disordered), consistent with Shannon’s IT, which scores the fully-determined state 0 and the fully-uncertain state 1. The intrinsically disordered proteins (IDPs) in a living cell may participate in maintaining the high-energy-low-entropy state. In addition, under this framework, the biological functions performed by proteins and associated with the order or disorder of their 3D structures could be explained in terms of information-gains or entropy-losses, or the reverse processes. Full article
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24 pages, 1866 KiB  
Perspective
Entropy and Information within Intrinsically Disordered Protein Regions
by Iva Pritišanac, Robert M. Vernon, Alan M. Moses and Julie D. Forman Kay
Entropy 2019, 21(7), 662; https://doi.org/10.3390/e21070662 - 06 Jul 2019
Cited by 31 | Viewed by 9002
Abstract
Bioinformatics and biophysical studies of intrinsically disordered proteins and regions (IDRs) note the high entropy at individual sequence positions and in conformations sampled in solution. This prevents application of the canonical sequence-structure-function paradigm to IDRs and motivates the development of new methods to [...] Read more.
Bioinformatics and biophysical studies of intrinsically disordered proteins and regions (IDRs) note the high entropy at individual sequence positions and in conformations sampled in solution. This prevents application of the canonical sequence-structure-function paradigm to IDRs and motivates the development of new methods to extract information from IDR sequences. We argue that the information in IDR sequences cannot be fully revealed through positional conservation, which largely measures stable structural contacts and interaction motifs. Instead, considerations of evolutionary conservation of molecular features can reveal the full extent of information in IDRs. Experimental quantification of the large conformational entropy of IDRs is challenging but can be approximated through the extent of conformational sampling measured by a combination of NMR spectroscopy and lower-resolution structural biology techniques, which can be further interpreted with simulations. Conformational entropy and other biophysical features can be modulated by post-translational modifications that provide functional advantages to IDRs by tuning their energy landscapes and enabling a variety of functional interactions and modes of regulation. The diverse mosaic of functional states of IDRs and their conformational features within complexes demands novel metrics of information, which will reflect the complicated sequence-conformational ensemble-function relationship of IDRs. Full article
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