Molecular dynamics simulation of intrinsically disordered proteins

Intrinsically disordered proteins are biomolecules that do not have a definite 3D structure; therefore, their dynamical simulation cannot start from a known list of atomistic positions, such as a Protein Data Bank file. We describe a method to start a computer simulation of these proteins. The first step of the procedure is the creation of a multi-rod configuration of the molecule, derived from its primary sequence. This structure is dynamically evolved in vacuo until its gyration radius reaches the experimental average value; at this point solvent molecules, in explicit or implicit implementation, are added to the protein and a regular molecular dynamics simulation follows. We have applied this procedure to the simulation of tau, one of the largest totally disordered proteins.     

Prediction of the location of structural domains in globular proteins

The location of structural domains in proteins is predicted from the amino acid sequence, based on the analysis of a computed contact map for the protein, the average distance map (ADM). Interactions between residues i and j in a protein are subdivided into several ranges, according to the separation |i-j| in the amino acid sequence. Within each range, average spatial distances between every pair of amino acid residues are computed from a data base of known protein structures. Infrequently occurring pairs are omitted as being statistically insignificant. The average distances are used to construct a predicted ADM. The ADM is analyzed for the occurrence of regions with high densities of contacts (compact regions). Locations of rapid changes of density between various parts of the map are determined by the use of scanning plots of contact densities. These locations serve to pinpoint the distribution of compact regions. This distribution, in turn, is used to predict boundaries of domains in the protein. The technique provides an objective method for the location of domains both on a contact map derived from a known three-dimensional protein structure, the real distance map (RDM), and on an ADM. While most other published methods for the identification of domains locate them in the known three-dimensional structure of a protein, the technique presented here also permits the prediction of domains in proteins of unknown spatial structure, as the construction of the ADM for a given protein requires knowledge of only its amino acid sequence.     

Uncoupled binding and folding of immune signaling-related intrinsically disordered proteins

The classical protein structure-function paradigm has been challenged by the emergence of intrinsically disordered proteins (IDPs), the proteins that do not adopt well-defined three-dimensional structures under physiological conditions. This development was accompanied by the introduction of a “coupled binding and folding” paradigm that suggests folding of IDPs upon binding to their partners. However, our recent studies challenge this general view by revealing a novel, previously unrecognized phenomenon – uncoupled binding and folding. This biologically important mechanism is characteristic of members of a new family of IDPs involved in immune signaling and underlies their unusual properties including: (1) specific homodimerization, (2) the lack of folding upon binding to a well-folded protein, another IDP molecule, or to lipid bilayer membranes, and (3) the “scissors-cut paradox”. The third phenomenon occurs in diverse IDP interactions and suggests that properties of IDP fragments are not necessarily additive in the context of the entire protein. The “no disorder-to-order transition” type of binding is distinct from known IDP interactions and is characterized by an unprecedented observation of the lack of chemical shift and peak intensity changes in multidimensional NMR spectra, a fingerprint of proteins, upon complex formation. Here, I focus on those interactions of IDPs with diverse biological partners where the binding phase driven by electrostatic interactions is not be necessarily followed by the hydrophobic folding phase. I also review new multidisciplinary knowledge about immune signaling-related IDPs and show how it expands our understanding of cell function with multiple applications in biology and medicine.     

Cold stability of intrinsically disordered proteins

Contrary to globular proteins, intrinsically disordered proteins (IDPs) lack a folded structure and they do not lose solubility at elevated temperatures. Although this should also be true at low temperatures, cold stability of IDPs has not been addressed in any scientific work so far. As direct characterization of cold-denaturation is difficult, we approached the problem through a freezing-induced loss-of-function model of globular-disordered functional protein pairs (m-calpain-calpastatin, tubulin-Map2c, Hsp90-ERD14). Our results affirm that in contrast with globular proteins IDPs are resistant to cold treatment. The theoretical and functional aspects of this observation are discussed.     

Alzheimer's-disease-associated conformation of intrinsically disordered tau protein studied by intrinsically disordered protein liquid-phase competitive enzyme-linked immunosorbent assay

Tau protein, the major constituent of paired helical filaments in Alzheimer's disease, belongs to the intrinsically disordered proteins (IDPs). IDPs are an emerging group in the protein kingdom characterized by the absence of a rigid three-dimensional structure. Disordered proteins usually acquire a "functional fold" upon binding to their interaction partner(s). This property of IDPs implies the need for innovative approaches to measure their binding affinity. We have mapped and measured the Alzheimer's-disease-associated epitope on intrinsically disordered tau protein with a novel two-step sandwich competitive enzyme-linked immunosorbent assay (ELISA). This approach allowed us to determine the binding affinity of disordered tau protein in liquid phase without any disturbance to the competitive equilibrium and without any need for covalent or noncovalent modification of tau protein. Furthermore, the global fitting method, used for the reconstruction of tau binding curves, significantly improved the assay readout. The proposed novel competitive ELISA allowed us to determine the changes in the standard Gibbs energy of binding, thus enabling measurement of tau protein conformation in the core of paired helical filaments. IDP competitive ELISA results showed, for the first time, that the tau protein C terminus of the Alzheimer's-disease-derived paired helical filaments core subunit adopts beta-turn type I' fold and is accessible from solution.     

An N-terminal, 830 residues intrinsically disordered region of the cytoskeleton-regulatory protein supervillin contains Myosin II- and F-actin-binding sites

Supervillin, the largest member of the villin/gelsolin family, is a cytoskeleton regulating, peripheral membrane protein. Supervillin increases cell motility and promotes invasive activity in tumors. Major cytoskeletal interactors, including filamentous actin and myosin II, bind within the unique supervillin amino terminus, amino acids 1–830. The structural features of this key region of the supervillin polypeptide are unknown. Here, we utilize circular dichroism and bioinformatics sequence analysis to demonstrate that the N-terminal part of supervillin forms an extended intrinsically disordered region (IDR). Our combined data indicate that the N-terminus of human and bovine supervillin sequences (positions 1–830) represents an IDR, which is the largest IDR known to date in the villin/gelsolin family. Moreover, this result suggests a potentially novel mechanism of regulation of myosin II and F-actin via the intrinsically disordered N-terminal region of hub protein supervillin.     

Using Bayesian multinomial classifier to predict whether a given protein sequence is intrinsically disordered

Intrinsically disordered proteins (IDPs) lack a well-defined three-dimensional structure under physiological conditions. Intrinsic disorder is a common phenomenon, particularly in multicellular eukaryotes, and is responsible for important protein functions including regulation and signaling. Many disease-related proteins are likely to be intrinsically disordered or to have disordered regions. In this paper, a new predictor model based on the Bayesian classification methodology is introduced to predict for a given protein or protein region if it is intrinsically disordered or ordered using only its primary sequence. The method allows to incorporate length-dependent amino acid compositional differences of disordered regions by including separate statistical representations for short, middle and long disordered regions. The predictor was trained on the constructed data set of protein regions with known structural properties. In a Jack-knife test, the predictor achieved the sensitivity of 89.2% for disordered and 81.4% for ordered regions. Our method outperformed several reported predictors when evaluated on the previously published data set of Prilusky et al. [2005. FoldIndex: a simple tool to predict whether a given protein sequence is intrinsically unfolded. Bioinformatics 21 (16), 3435-3438]. Further strength of our approach is the ease of implementation.     

Conformational response to charge clustering in synthetic intrinsically disordered proteins

Background

Recent theoretical and computational studies have shown that the charge content and, most importantly, the linear distribution of opposite charges are major determinants of conformational properties of intrinsically disordered proteins (IDPs). Charge segregation in a sequence can be measured through κ, which represents a normalized measure of charge asymmetry. A strong inverse correlation between κ and radius of gyration has been previously demonstrated for two independent sets of permutated IDP sequences.

Modeling of protein loops by simulated annealing.

A method is presented to model loops of protein to be used in homology modeling of proteins. This method employs the ESAP program of Higo et al. (Higo, J., Collura, V., & Garnier, J., 1992, Biopolymers 32, 33-43) and is based on a fast Monte Carlo simulation and a simulated annealing algorithm. The method is tested on different loops or peptide segments from immunoglobulin, bovine pancreatic trypsin inhibitor, and bovine trypsin. The predicted structure is obtained from the ensemble average of the coordinates of the Monte Carlo simulation at 300 K, which exhibits the lowest internal energy. The starting conformation of the loop prior to modeling is chosen to be completely extended, and a closing harmonic potential is applied to N, CA, C, and O atoms of the terminal residues. A rigid geometry potential of Robson and Platt (1986, J. Mol. Biol. 188, 259-281) with a united atom representation is used. This we demonstrate to yield a loop structure with good hydrogen bonding and torsion angles in the allowed regions of the Ramachandran map. The average accuracy of the modeling evaluated on the eight modeled loops is 1 A root mean square deviation (rmsd) for the backbone atoms and 2.3 A rmsd for all heavy atoms.     

Temporary secondary structures in tau,an intrinsically disordered protein

The tau protein belongs to the category of intrinsically disordered proteins, which in their native state do not have an average stable structure and fluctuate between many conformations. In its physiological state, tau helps nucleating and stabilising the microtubules in the axons of the neurons. On the other hand, the same tau is involved in the development of Alzheimer disease, when it aggregates in paired helical filaments forming fibrils, which form insoluble tangles. The beginning of the pathological aggregation of tau has been attributed to a local transition of protein portions from random coil to a β-sheet. These structures would very likely be transient; therefore, we performed a molecular dynamics simulation of tau to gather information on the existence of segments of tau endowed with a secondary structure. We combined the results of our simulation with small-angle X-ray scattering experimental data to extract from the dynamics a set of most probable conformations of tau. The analysis of these conformations highlights the presence of transient secondary structures such as turns, β-bridges, β-sheets and α-helices. It also shows that a large segment of the N-terminal region is found near the repeats domain in a globular-like shape.     

CDF it all: Consensus prediction of intrinsically disordered proteins based on various cumulative distribution functions

Many biologically active proteins are intrinsically disordered. A reasonable understanding of the disorder status of these proteins may be beneficial for better understanding of their structures and functions. The disorder contents of disordered proteins vary dramatically, with two extremes being fully ordered and fully disordered proteins. Often, it is necessary to perform a binary classification and classify a whole protein as ordered or disordered. Here, an improved error estimation technique was applied to develop the cumulative distribution function (CDF) algorithms for several established disorder predictors. A consensus binary predictor, based on the artificial neural networks, NN-CDF, was developed by using output of the individual CDFs. The consensus method outperforms the individual predictors by 4-5% in the averaged accuracy.     

The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins

The structural stability of a protein requires a large number of interresidue interactions. The energetic contribution of these can be approximated by low-resolution force fields extracted from known structures, based on observed amino acid pairing frequencies. The summation of such energies, however, cannot be carried out for proteins whose structure is not known or for intrinsically unstructured proteins. To overcome these limitations, we present a novel method for estimating the total pairwise interaction energy, based on a quadratic form in the amino acid composition of the protein. This approach is validated by the good correlation of the estimated and actual energies of proteins of known structure and by a clear separation of folded and disordered proteins in the energy space it defines. As the novel algorithm has not been trained on unstructured proteins, it substantiates the concept of protein disorder, i.e. that the inability to form a well-defined 3D structure is an intrinsic property of many proteins and protein domains. This property is encoded in their sequence, because their biased amino acid composition does not allow sufficient stabilizing interactions to form. By limiting the calculation to a predefined sequential neighborhood, the algorithm was turned into a position-specific scoring scheme that characterizes the tendency of a given amino acid to fall into an ordered or disordered region. This application we term IUPred and compare its performance with three generally accepted predictors, PONDR VL3H, DISOPRED2 and GlobPlot on a database of disordered proteins.     

A tool for the prediction of functionally important sites in proteins using a library of functional templates

Understanding and characterizing the biochemical and evolutionary information within the wealth of protein sequence and structural data, particularly at functionally important sites, is very important. A comprehensive analysis of physico-chemical properties and evolutionary conservation patterns at the molecular and biological function level is expected to yield important clues for identifying similar sites in as-yet uncharacterized proteins. We present a library of protein functional templates (PFTs) designed to represent the compositional and evolutionary conservation patterns of functional sites at the molecular and biological function level. Subsequently we developed LIMACS (LInear MAtching of Conservation Scores), a software tool that uses the template library for the prediction of functionally important sites in a multiple sequence alignment, transferring the molecular function annotation from the most-similar functional site in the template library to a predicted site.     

Targeting intrinsically disordered proteins in neurodegenerative and protein dysfunction diseases: another illustration of the D2 concept

Many biologically active proteins, which are usually called intrinsically disordered or natively unfolded proteins, lack stable tertiary and/or secondary structure under physiological conditions in vitro. Their functions complement the functional repertoire of ordered proteins, with intrinsically disordered proteins (IDPs) often being involved in regulation, signaling and control. Their amino acid sequences and compositions are very different from those of ordered proteins, making reliable identification of IDPs possible at the proteome level. IDPs are highly abundant in various human diseases, including neurodegeneration and other protein dysfunction maladies and, therefore, represent attractive novel drug targets. Some of the aspects of IDPs, as well as their roles in neurodegeneration and protein dysfunction diseases, are discussed in this article, together with the peculiarities of IDPs as potential drug targets.