scholarly journals Quantitative proteome-based guidelines for intrinsic disorder characterization

2015 ◽  
Author(s):  
Michael Vincent ◽  
Mark Whidden ◽  
Santiago Schnell

AbstractIntrinsically disordered proteins fail to adopt a stable three-dimensional structure under physiological conditions. It is now understood that many disordered proteins are not dysfunctional, but instead engage in numerous cellular processes, including signaling and regulation. Disorder characterization from amino acid sequence relies on computational disorder prediction algorithms. While numerous large-scale investigations of disorder have been performed using these algorithms, and have offered valuable insight regarding the prevalence of protein disorder in many organisms, critical proteome-based descriptive statistical guidelines that would enable the objective assessment of intrinsic disorder in a protein of interest remain to be established. Here we present a quantitative characterization of numerous disorder features using a rigorous non-parametric statistical approach, providing expected values and percentile cutoffs for each feature in ten eukaryotic proteomes. Our estimates utilize multiple ab initio disorder prediction algorithms grounded on physicochemical principles. Furthermore, we present novel threshold values, specific to both the prediction algorithms and the proteomes, defining the longest primary sequence length in which the significance of a continuous disordered region can be evaluated on the basis of length alone. The guidelines presented here are intended to improve the interpretation of disorder content and continuous disorder predictions from the proteomic point of view.

2016 ◽  
Author(s):  
Michael Vincent ◽  
Santiago Schnell

AbstractIntrinsically disordered proteins lack a stable three-dimensional structure under physiological conditions. While this property has gained considerable interest within the past two decades, disorder poses substantial challenges to experimental characterization efforts. In effect, numerous computational tools have been developed to predict disorder from primary sequences, however, interpreting the output of these algorithms remains a challenge. To begin to bridge this gap, we present Disorder Atlas, web-based software that facilitates the interpretation of intrinsic disorder predictions using proteome-based descriptive statistics. This service is also equipped to facilitate large-scale systematic exploratory searches for proteins encompassing disorder features of interest, and further allows users to browse the prevalence of multiple disorder features at the proteome level. As a result, Disorder Atlas provides a user-friendly tool that places algorithm-generated disorder predictions in the context of the proteome, thereby providing an instrument to compare the results of a query protein against predictions made for an entire population. Disorder Atlas currently supports ten eukaryotic proteomes and is freely available for non-commercial users at http://www.disorderatlas.org.


2020 ◽  
Author(s):  
Marco Necci ◽  
Damiano Piovesan ◽  
Silvio C.E. Tosatto ◽  
◽  

AbstractIntrinsically disordered proteins defying the traditional protein structure-function paradigm represent a challenge to study experimentally. As a large part of our knowledge rests on computational predictions, it is crucial for their accuracy to be high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in predicting intrinsically disordered regions in proteins and the subset of disordered residues involved in binding other molecules. A total of 43 methods, 32 for disorder and 11 for binding regions, were evaluated on a dataset of 646 novel manually curated proteins from DisProt. The best methods use deep learning techniques and significantly outperform widely used earlier physicochemical methods across different types of targets. Disordered binding regions remain hard to predict correctly. Depending on the definition used, the top disorder predictor has an FMax of 0.483 (DisProt) or 0.792 (DisProt-PDB). As the top binding predictor only attains an FMax of 0.231, this suggests significant potential for improvement. Intriguingly, computing times among the top performing methods vary by up to four orders of magnitude.


Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 591
Author(s):  
Hao-Bo Guo ◽  
Yue Ma ◽  
Gerald Tuskan ◽  
Hong Qin ◽  
Xiaohan Yang ◽  
...  

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.


Author(s):  
Marco Necci ◽  
◽  
Damiano Piovesan ◽  
Silvio C. E. Tosatto ◽  

AbstractIntrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has Fmax = 0.483 on the full dataset and Fmax = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with Fmax = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.


2012 ◽  
Vol 40 (5) ◽  
pp. 955-962 ◽  
Author(s):  
Nathalie Sibille ◽  
Pau Bernadó

In recent years, IDPs (intrinsically disordered proteins) have emerged as pivotal actors in biology. Despite IDPs being present in all kingdoms of life, they are more abundant in eukaryotes where they are involved in the vast majority of regulation and signalling processes. The realization that, in some cases, functional states of proteins were partly or fully disordered was in contradiction to the traditional view where a well defined three-dimensional structure was required for activity. Several experimental evidences indicate, however, that structural features in IDPs such as transient secondary-structural elements and overall dimensions are crucial to their function. NMR has been the main tool to study IDP structure by probing conformational preferences at residue level. Additionally, SAXS (small-angle X-ray scattering) has the capacity to report on the three-dimensional space sampled by disordered states and therefore complements the local information provided by NMR. The present review describes how the synergy between NMR and SAXS can be exploited to obtain more detailed structural and dynamic models of IDPs in solution. These combined strategies, embedded into computational approaches, promise the elucidation of the structure–function properties of this important, but elusive, family of biomolecules.


2012 ◽  
Vol 40 (5) ◽  
pp. 995-999 ◽  
Author(s):  
Brigitte Gontero ◽  
Stephen C. Maberly

Many proteins contain disordered regions under physiological conditions and lack specific three-dimensional structure. These are referred to as IDPs (intrinsically disordered proteins). CP12 is a chloroplast protein of approximately 80 amino acids and has a molecular mass of approximately 8.2–8.5 kDa. It is enriched in charged amino acids and has a small number of hydrophobic residues. It has a high proportion of disorder-promoting residues, but has at least two (often four) cysteine residues forming one (or two) disulfide bridge(s) under oxidizing conditions that confers some order. However, CP12 behaves like an IDP. It appears to be universally distributed in oxygenic photosynthetic organisms and has recently been detected in a cyanophage. The best studied role of CP12 is its regulation of the Calvin cycle responsible for CO2 assimilation. Oxidized CP12 forms a supramolecular complex with two key Calvin cycle enzymes, GAPDH (glyceraldehyde-3-phosphate dehydrogenase) and PRK (phosphoribulokinase), down-regulating their activity. Association–dissociation of this complex, induced by the redox state of CP12, allows the Calvin cycle to be inactive in the dark and active in the light. CP12 is promiscuous and interacts with other enzymes such as aldolase and malate dehydrogenase. It also plays other roles in plant metabolism such as protecting GAPDH from inactivation and scavenging metal ions such as copper and nickel, and it is also linked to stress responses. Thus CP12 seems to be involved in many functions in photosynthetic cells and behaves like a jack of all trades as well as being a master of the Calvin cycle.


Biomolecules ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 77 ◽  
Author(s):  
Xingcheng Lin ◽  
Prakash Kulkarni ◽  
Federico Bocci ◽  
Nicholas Schafer ◽  
Susmita Roy ◽  
...  

Folded proteins show a high degree of structural order and undergo (fairly constrained) collective motions related to their functions. On the other hand, intrinsically disordered proteins (IDPs), while lacking a well-defined three-dimensional structure, do exhibit some structural and dynamical ordering, but are less constrained in their motions than folded proteins. The larger structural plasticity of IDPs emphasizes the importance of entropically driven motions. Many IDPs undergo function-related disorder-to-order transitions driven by their interaction with specific binding partners. As experimental techniques become more sensitive and become better integrated with computational simulations, we are beginning to see how the modest structural ordering and large amplitude collective motions of IDPs endow them with an ability to mediate multiple interactions with different partners in the cell. To illustrate these points, here, we use Prostate-associated gene 4 (PAGE4), an IDP implicated in prostate cancer (PCa) as an example. We first review our previous efforts using molecular dynamics simulations based on atomistic AWSEM to study the conformational dynamics of PAGE4 and how its motions change in its different physiologically relevant phosphorylated forms. Our simulations quantitatively reproduced experimental observations and revealed how structural and dynamical ordering are encoded in the sequence of PAGE4 and can be modulated by different extents of phosphorylation by the kinases HIPK1 and CLK2. This ordering is reflected in changing populations of certain secondary structural elements as well as in the regularity of its collective motions. These ordered features are directly correlated with the functional interactions of WT-PAGE4, HIPK1-PAGE4 and CLK2-PAGE4 with the AP-1 signaling axis. These interactions give rise to repeated transitions between (high HIPK1-PAGE4, low CLK2-PAGE4) and (low HIPK1-PAGE4, high CLK2-PAGE4) cell phenotypes, which possess differing sensitivities to the standard PCa therapies, such as androgen deprivation therapy (ADT). We argue that, although the structural plasticity of an IDP is important in promoting promiscuous interactions, the modulation of the structural ordering is important for sculpting its interactions so as to rewire with agility biomolecular interaction networks with significant functional consequences.


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.


2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Jacqueline F. Pelham ◽  
Jay C. Dunlap ◽  
Jennifer M. Hurley

Abstract Introduction The circadian circuit, a roughly 24 h molecular feedback loop, or clock, is conserved from bacteria to animals and allows for enhanced organismal survival by facilitating the anticipation of the day/night cycle. With circadian regulation reportedly impacting as high as 80% of protein coding genes in higher eukaryotes, the protein-based circadian clock broadly regulates physiology and behavior. Due to the extensive interconnection between the clock and other cellular systems, chronic disruption of these molecular rhythms leads to a decrease in organismal fitness as well as an increase of disease rates in humans. Importantly, recent research has demonstrated that proteins comprising the circadian clock network display a significant amount of intrinsic disorder. Main body In this work, we focus on the extent of intrinsic disorder in the circadian clock and its potential mechanistic role in circadian timing. We highlight the conservation of disorder by quantifying the extent of computationally-predicted protein disorder in the core clock of the key eukaryotic circadian model organisms Drosophila melanogaster, Neurospora crassa, and Mus musculus. We further examine previously published work, as well as feature novel experimental evidence, demonstrating that the core negative arm circadian period drivers FREQUENCY (Neurospora crassa) and PERIOD-2 (PER2) (Mus musculus), possess biochemical characteristics of intrinsically disordered proteins. Finally, we discuss the potential contributions of the inherent biophysical principals of intrinsically disordered proteins that may explain the vital mechanistic roles they play in the clock to drive their broad evolutionary conservation in circadian timekeeping. Conclusion The pervasive conservation of disorder amongst the clock in the crown eukaryotes suggests that disorder is essential for optimal circadian timing from fungi to animals, providing vital homeostatic cellular maintenance and coordinating organismal physiology across phylogenetic kingdoms. Graphical abstract


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