A creature with a hundred waggly tails: intrinsically disordered proteins in the ribosome

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Intrinsic disorder (i.e., lack of a unique 3-D structure) is a common phenomenon, and many biologically active proteins are disordered as a whole, or contain long disordered regions. These intrinsically disordered proteins/regions constitute a significant part of all proteomes, and their functional repertoire is complementary to functions of ordered proteins. In fact, intrinsic disorder represents an important driving force for many specific functions. An illustrative example of such disorder-centric functional class is RNA-binding proteins. In this study, we present the results of comprehensive bioinformatics analyses of the abundance and roles of intrinsic disorder in 3,411 ribosomal proteins from 32 species. We show that many ribosomal proteins are intrinsically disordered or hybrid proteins that contain ordered and disordered domains. Predicted globular domains of many ribosomal proteins contain noticeable regions of intrinsic disorder. We also show that disorder in ribosomal proteins has different characteristics compared to other proteins that interact with RNA and DNA including overall abundance, evolutionary conservation, and involvement in protein–protein interactions. Furthermore, intrinsic disorder is not only abundant in the ribosomal proteins, but we demonstrate that it is absolutely necessary for their various functions

Structural analysis of intrinsically disordered proteins: computer atomistic simulation

Intrinsically disordered proteins (IDPs) are biomolecules that do not have a definite 3D structure; their role in the biochemical network of a cell relates to their ability to switch rapidly among different secondary and tertiary structures. For this reason, applying a simulation computer program to their structural study turns out to be problematic, as their dynamical simulation cannot start from a known list of atomistic positions, as is the case for globular proteins that do crystallize and that one can analyse by X-ray spectroscopy to determine their structure. We have established a method to perform a computer simulation of these proteins, apt to gather statistically significant data on their transient structures. The only required input to start the procedure is the primary sequence of the disordered domains of the protein, and the 3D structure of the ordered domains, if any. For a fully disordered protein the method is as follows: (a) The first step is the creation of a multi-rod-like configuration of the molecule, derived from its primary sequence. This structure evolves dynamically in vacuo or in an implicit model of solvent, until its gyration radius - or any other measure of the overall configuration of the molecule - reaches the experimental average value; at this point, one may follow two different paths. (b1) If the study focuses on transient secondary structures of the molecule, one puts the structure obtained at the end of the first step in a box containing solvent molecules in explicit implementation, and a standard molecular dynamics simulation follows. (b2) If the study focuses on the tertiary structure of the molecule, a larger sampling of the phase space is required, with the molecule moving in very large and diverse regions of the phase space. To this end, the structure of the IDP is let evolve dynamically in an implicit solvent using metadynamics, an algorithm that keeps track of the regions of the phase space already sampled, and forces the system to wander in further regions of the phase space. (c) One can increase the accuracy of the statistical information gathered in both cases by fitting, where available, experimental data of the protein. In this step one extracts an ensemble of ’best’ conformers from the pool of all configurations produced in the simulated dynamics. One derives this ensemble by means of an ensemble optimization method, implementing a genetic algorithm. We have applied this procedure to the simulation of tau, one of the largest fully disordered proteins, which is involved in the development of Alzheimer’s disease and of other neurodegenerative diseases. We have combined the results of our simulation with small-angle X-ray scattering experimental data to extract from the dynamics an optimized ensemble of most probable conformers of tau. The method can be easily adapted to IDPs entailing ordered domains

Constructing ensembles for intrinsically disordered proteins

The relatively flat energy landscapes associated with intrinsically disordered proteins makes modeling these systems especially problematic. A comprehensive model for these proteins requires one to build an ensemble consisting of a finite collection of structures, and their corresponding relative stabilities, which adequately capture the range of accessible states of the protein. In this regard, methods that use computational techniques to interpret experimental data in terms of such ensembles are an essential part of the modeling process. In this review, we critically assess the advantages and limitations of current techniques and discuss new methods for the validation of these ensembles

Calibrated Langevin dynamics simulations of intrinsically disordered proteins

We perform extensive coarse-grained (CG) Langevin dynamics simulations of intrinsically disordered proteins (IDPs), which possess fluctuating conformational statistics between that for excluded volume random walks and collapsed globules. Our CG model includes repulsive steric, attractive hydrophobic, and electrostatic interactions between residues and is calibrated to a large collection of single-molecule fluorescence resonance energy transfer data on the inter-residue separations for 36 pairs of residues in five IDPs: $\alpha$-, $\beta$-, and $\gamma$-synuclein, the microtubule-associated protein $\tau$, and prothymosin $\alpha$. We find that our CG model is able to recapitulate the average inter-residue separations regardless of the choice of the hydrophobicity scale, which shows that our calibrated model can robustly capture the conformational dynamics of IDPs. We then employ our model to study the scaling of the radius of gyration with chemical distance in 11 known IDPs. We identify a strong correlation between the distance to the dividing line between folded proteins and IDPs in the mean charge and hydrophobicity space and the scaling exponent of the radius of gyration with chemical distance along the protein.Comment: 16 pages, 10 figure

Intrinsically Disordered Proteins: Where Computation Meets Experiment

Proteins are heteropolymers that play important roles in virtually every biological reaction. While many proteins have well-defined three-dimensional structures that are inextricably coupled to their function, intrinsically disordered proteins (IDPs) do not have a well-defined structure, and it is this lack of structure that facilitates their function. As many IDPs are involved in essential cellular processes, various diseases have been linked to their malfunction, thereby making them important drug targets. In this review we discuss methods for studying IDPs and provide examples of how computational methods can improve our understanding of IDPs. We focus on two intensely studied IDPs that have been implicated in very different pathologic pathways. The first, p53, has been linked to over 50% of human cancers, and the second, Amyloid-β (Aβ), forms neurotoxic aggregates in the brains of patients with Alzheimer’s disease. We use these representative proteins to illustrate some of the challenges associated with studying IDPs and demonstrate how computational tools can be fruitfully applied to arrive at a more comprehensive understanding of these fascinating heteropolymers.National Science Foundation (U.S.). Directorate for Biological Sciences. Postdoctoral Research Fellowship (Grant 1309247

Structural characterization of intrinsically disordered proteins by NMR spectroscopy.

Recent advances in NMR methodology and techniques allow the structural investigation of biomolecules of increasing size with atomic resolution. NMR spectroscopy is especially well-suited for the study of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) which are in general highly flexible and do not have a well-defined secondary or tertiary structure under functional conditions. In the last decade, the important role of IDPs in many essential cellular processes has become more evident as the lack of a stable tertiary structure of many protagonists in signal transduction, transcription regulation and cell-cycle regulation has been discovered. The growing demand for structural data of IDPs required the development and adaption of methods such as 13C-direct detected experiments, paramagnetic relaxation enhancements (PREs) or residual dipolar couplings (RDCs) for the study of 'unstructured' molecules in vitro and in-cell. The information obtained by NMR can be processed with novel computational tools to generate conformational ensembles that visualize the conformations IDPs sample under functional conditions. Here, we address NMR experiments and strategies that enable the generation of detailed structural models of IDPs

Foreword

Proteins that contain long disordered regions are prevalent in the proteome and frequently associated with diseases. However, the mechanisms by which such intrinsically disordered proteins (IDPs) recognize their targets are not well understood. Here, we report the first experimental investigation of the interaction kinetics of the nuclear co-activator binding domain of CREB-binding protein and the activation domain from the p160 transcriptional co-activator for thyroid hormone and retinoid receptors. Both protein domains are intrinsically disordered in the free state and synergistically fold upon binding each other. Using the stopped-flow technique, we found that the binding reaction is fast, with an association rate constant of 3 x 10(7) M-1 s(-1) at 277 K. Mutation of a conserved buried intermolecular salt bridge showed that electrostatics govern the rapid association. Furthermore, upon mutation of the salt bridge or at high salt concentration, an additional kinetic phase was detected (similar to 20 and similar to 40 s(-1), respectively, at 277 K), suggesting that the salt bridge may steer formation of the productive bimolecular complex in an intramolecular step. Finally, we directly measured slow kinetics for the IDP domains (similar to 1 s(-1) at 277 K) related to conformational transitions upon binding. Together, the experiments demonstrate that the interaction involves several steps and accumulation of intermediate states. Our data are consistent with an induced fit mechanism, in agreement with previous simulations. We propose that the slow transitions may be a consequence of the multipartner interactions of IDPs