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Intrinsically disordered proteins are highly dynamic biomolecules that rapidly interconvert between many structural conformations. Traditionally, these proteins have been considered un-druggable because of their lack of classical long-lived binding pockets. Recent evidence suggests that intrinsically disordered proteins can bind small, drug-like molecules, however, there are limited approaches to characterize these interactions experimentally. Here we demonstrate that ligand-detected19F transverse relaxation rates (R2) obtained from Nuclear Magnetic Resonance spectroscopy are highly sensitive to the interaction between a small-molecule and an intrinsically disordered protein, in contrast to chemical shift perturbations which are minimally sensitive for this interaction. With this method, we show that the small molecule, 5-fluoroindole, interacts with the disordered domains of non-structural protein 5A from hepatitis C virus with aKdof 260 ± 110 μM. We also demonstrate that 5-fluoroindole remains highly dynamic in the bound form. Our findings suggest that ligand-detected19F transverse relaxation measurements could represent a highly effective screening strategy to identify molecules capable of interacting with these traditionally elusive, dynamic biomolecules.

The stabilization of native states of proteins is a powerful drug discovery strategy. It is still unclear, however, whether this approach can be applied to intrinsically disordered proteins. Here, we report a small molecule that stabilizes the native state of the Aβ42 peptide, an intrinsically disordered protein fragment associated with Alzheimer's disease. We show that this stabilization takes place by a disordered binding mechanism, in which both the small molecule and the Aβ42 peptide remain disordered. This disordered binding mechanism involves enthalpically favorable local π-stacking interactions coupled with entropically advantageous global effects. These results indicate that small molecules can stabilize disordered proteins in their native states through transient non-specific interactions that provide enthalpic gain while simultaneously increasing the conformational entropy of the proteins.

Understanding the mechanism of action of compounds capable of inhibiting amyloid-fibril formation is critical to the development of potential therapeutics against protein-misfolding diseases. A fundamental challenge for progress is the range of possible target species and the disparate timescales involved, since the aggregating proteins are simultaneously the reactants, products, intermediates, and catalysts of the reaction. It is a complex problem, therefore, to choose the states of the aggregating proteins that should be bound by the compounds to achieve the most potent inhibition. We present here a comprehensive kinetic theory of amyloid-aggregation inhibition that reveals the fundamental thermodynamic and kinetic signatures characterizing effective inhibitors by identifying quantitative relationships between the aggregation and binding rate constants. These results provide general physical laws to guide the design and optimization of inhibitors of amyloid-fibril formation, revealing in particular the important role of on-rates in the binding of the inhibitors.

The stabilisation of native states of proteins is a powerful drug discovery strategy. It is still unclear, however, whether this approach can be applied to intrinsically disordered proteins. Here we report a small molecule that stabilises the native state of the Aβ42 peptide, an intrinsically disordered protein fragment associated with Alzheimer’s disease. We show that this stabilisation takes place by a dynamic binding mechanism, in which both the small molecule and the Aβ42 peptide remain disordered. This disordered binding mechanism involves enthalpically favourable local π-stacking interactions coupled with entropically advantageous global effects. These results indicate that small molecules can stabilise disordered proteins in their native states through transient non-specific interactions that provide enthalpic gain while simultaneously increasing the conformational entropy of the proteins.

Funder: Centre for Misfolding Diseases, Bicyclic peptides have great therapeutic potential since they can bridge the gap between small molecules and antibodies by combining a low molecular weight of about 2 kDa with an antibody-like binding specificity. Here we apply a recently developed in silico rational design strategy to produce a bicyclic peptide to target the C-terminal region (residues 31–42) of the 42-residue form of the amyloid β peptide (Aβ42), a protein fragment whose aggregation into amyloid plaques is linked with Alzheimer’s disease. We show that this bicyclic peptide is able to remodel the aggregation process of Aβ42 in vitro and to reduce its associated toxicity in vivo in a C. elegans worm model expressing Aβ42. These results provide an initial example of a computational approach to design bicyclic peptides to target specific epitopes on disordered proteins.

Significance The accurate quantification of the amounts of small oligomeric assemblies formed by the amyloid β (Aβ) peptide represents a major challenge in the Alzheimer’s field. There is therefore great interest in the development of methods to specifically detect these oligomers by distinguishing them from larger aggregates. The availability of these methods will enable the development of effective diagnostic and therapeutic interventions for this and other diseases related to protein misfolding and aggregation. We describe here a single-domain antibody able to selectively quantify oligomers of the Aβ peptide in isolation and in complex protein mixtures from animal models of disease., Protein misfolding and aggregation is the hallmark of numerous human disorders, including Alzheimer’s disease. This process involves the formation of transient and heterogeneous soluble oligomers, some of which are highly cytotoxic. A major challenge for the development of effective diagnostic and therapeutic tools is thus the detection and quantification of these elusive oligomers. Here, to address this problem, we develop a two-step rational design method for the discovery of oligomer-specific antibodies. The first step consists of an “antigen scanning” phase in which an initial panel of antibodies is designed to bind different epitopes covering the entire sequence of a target protein. This procedure enables the determination through in vitro assays of the regions exposed in the oligomers but not in the fibrillar deposits. The second step involves an “epitope mining” phase, in which a second panel of antibodies is designed to specifically target the regions identified during the scanning step. We illustrate this method in the case of the amyloid β (Aβ) peptide, whose oligomers are associated with Alzheimer’s disease. Our results show that this approach enables the accurate detection and quantification of Aβ oligomers in vitro, and in Caenorhabditis elegans and mouse hippocampal tissues.

The discovery that disordered proteins are widespread in the human proteome has prompted the quest for methods to characterize the conformational properties that determine their functional and dysfunctional behaviour. It has become customary to describe these proteins in terms of structural ensembles and free energy landscapes, which offer conformational and thermodynamic insight. However, a current major challenge is to generalize this description to ‘kinetic ensembles’, thereby also providing information on transition rates between states. Approaches based on the theory of stochastic processes can be particularly suitable for this purpose. Here, we develop a Markov state model and illustrate its application by determining a kinetic ensemble of the 42-residue form of the amyloid-β peptide (Aβ42), whose aggregation is associated with Alzheimer’s disease. Using the Google Compute Engine, we generated 315 μs all-atom, explicit solvent molecular dynamics trajectories, validated with experimental data from nuclear magnetic resonance spectroscopy. Using a probabilistic-based definition of conformational states in a neural network approach, we found that Aβ42 is characterized by inter-state transitions no longer than the microsecond timescale, exhibiting only fully unfolded or short-lived, partially-folded states. We contextualize our findings by performing additional simulations of the oxidized form of Aβ42. Our results illustrate how the use of kinetic ensembles offers an effective means to provide information about the structure, thermodynamics, and kinetics of disordered proteins towards an understanding of these ubiquitous biomolecules.

The PLUMED consortium unifies developers and contributors to PLUMED, an open-source library for enhanced-sampling, free-energy calculations and the analysis of molecular dynamics simulations. Here, we outline our efforts to promote transparency and reproducibility by disseminating protocols for enhanced-sampling molecular simulations.

A small molecule binds to a disordered protein in its monomeric form, preventing its aggregation linked to Alzheimer’s disease., Disordered proteins are challenging therapeutic targets, and no drug is currently in clinical use that modifies the properties of their monomeric states. Here, we identify a small molecule (10074-G5) capable of binding and sequestering the intrinsically disordered amyloid-β (Aβ) peptide in its monomeric, soluble state. Our analysis reveals that this compound interacts with Aβ and inhibits both the primary and secondary nucleation pathways in its aggregation process. We characterize this interaction using biophysical experiments and integrative structural ensemble determination methods. We observe that this molecule increases the conformational entropy of monomeric Aβ while decreasing its hydrophobic surface area. We also show that it rescues a Caenorhabditis elegans model of Aβ-associated toxicity, consistent with the mechanism of action identified from the in silico and in vitro studies. These results illustrate the strategy of stabilizing the monomeric states of disordered proteins with small molecules to alter their behavior for therapeutic purposes.

Disordered proteins are challenging therapeutic targets, and no drug is currently in clinical use that has been shown to modify the properties of their monomeric states. Here, we identify a small molecule capable of binding and sequestering the amyloid-β peptide (Aβ) in its monomeric, soluble state. Our analysis reveals that this compound interacts with Aβ and inhibits both the primary and secondary nucleation pathways in its aggregation process. We characterise this interaction using biophysical experiments and integrative structural ensemble determination methods. We thus observe that this small molecule has the remarkable effect of increasing the conformational entropy of monomeric Aβ while decreasing its hydrophobic surface area. We then show that this small molecule rescues a Caenorhabditis elegans model of Aβ-associated toxicity in a manner consistent with the mechanism of action identified from the in silico and in vitro studies. These results provide an illustration of the strategy of targeting the monomeric states of disordered proteins with small molecules to alter their behaviour for therapeutic purposes.

International audience; The conformational fluctuations of proteins can be described by structural ensembles. To address the major challenge of determining these ensembles accurately, a wide range of strategies have recently been proposed to combine molecular dynamics simulations with experimental data. Quite generally, there are two ways of implementing this type of approach, either by applying structural restraints during a simulation, or by reweighting a posteriori the conformations from an a priori ensemble. It is not yet clear, however, whether these two approaches can offer ensembles of equivalent quality. The advantages of the reweighting method are that it can involve any type of starting simulation and that it enables the integration of experimental data after the simulations are run. A disadvantage, however, is that this procedure may be inaccurate when the a priori ensemble is of poor quality. Here, our goal is to systematically compare the restraining and reweighting approaches and to explore the conditions required for the reweighting ensembles to be accurate. Our results indicate that the reweighting approach is computationally efficient and can perform as well as the restraining approach when the a priori sampling is accurate. More generally, to enable an effective use of the reweighting approach by avoiding the pitfalls of poor sampling, we suggest metrics for the quality control of the reweighted ensembles.

Over the past decade, there has been a growing interest in investigating whether disordered proteins can be targeted for clinical purposes using small molecules [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] . While small-molecule binding to disordered proteins can be seen as unorthodox, examples of this phenomenon have been reported. In order to rationalize these observations, a variety of models are emerging, sometimes in apparent contradiction. Here, we offer a “structural ensemble modulation” view as an attempt to clarify the language, organize concepts, and facilitate the comparison of different studies. In doing so, we hope to promote the understanding of the general principles underlying this phenomenon toward the development of novel therapeutic compounds targeting disordered proteins, which are prevalent in a wide range of human diseases [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] .

It is generally recognized that a large fraction of the human proteome is made up of proteins that remain disordered in their native states. Despite the fact that such proteins play key biological roles and are involved in many major human diseases, they still represent challenging targets for drug discovery. A major bottleneck for the identification of compounds capable of interacting with these proteins and modulating their disease-promoting behaviour is the development of effective techniques to probe such interactions. The difficulties in carrying out binding measurements have resulted in a poor understanding of the mechanisms underlying these interactions. In order to facilitate further methodological advances, here we review the most commonly used techniques to probe three types of interactions involving small molecules: (1) those that disrupt functional interactions between disordered proteins; (2) those that inhibit the aberrant aggregation of disordered proteins, and (3) those that lead to binding disordered proteins in their monomeric states. In discussing these techniques, we also point out directions for future developments.

Approximately one-third of the human proteome is made up of proteins that are entirely disordered or that contain extended disordered regions. Although these disordered proteins are closely linked with many major diseases, their binding mechanisms with small molecules remain poorly understood, and a major concern is whether their specificity can be sufficient for drug development. Here, by studying the interaction of a small molecule and a disordered peptide from the oncogene protein c-Myc, we describe a “specific-diffuse” binding mechanism that exhibits sequence specificity despite being of entropic nature. By combining NMR spectroscopy, biophysical measurements, statistical inference, and molecular simulations, we provide a quantitative measure of such sequence specificity and compare it to the case of the interaction of urea, which is diffuse but not specific. To investigate whether this type of binding can generally modify intermolecular interactions, we show that it leads to an inhibition of the aggregation of the peptide. These results suggest that the binding mechanism that we report may create novel opportunities to discover drugs that target disordered proteins in their monomeric states in a specific manner.

The self-Assembly of α-synuclein is closely associated with Parkinson's disease and related syndromes. We show that squalamine, a natural product with known anticancer and antiviral activity, dramatically affects α-synuclein aggregation in vitro and in vivo. We elucidate the mechanism of action of squalamine by investigating its interaction with lipid vesicles, which are known to stimulate nucleation, and find that this compound displaces α-synuclein from the surfaces of such vesicles, thereby blocking the first steps in its aggregation process. We also show that squalamine almost completely suppresses the toxicity of α-synuclein oligomers in human neuroblastoma cells by inhibiting their interactions with lipid membranes. We further examine the effects of squalamine in a Caenorhabditis elegans strain overexpressing α-synuclein, observing a dramatic reduction of α-synuclein aggregation and an almost complete elimination of muscle paralysis. These findings suggest that squalamine could be a means of therapeutic intervention in Parkinson's disease and related conditions.

International audience; The biological functions of protein molecules are intimately contingent on their conformational dynamics. This aspect is particularly evident for disordered proteins, which constitute about one-third of the human proteome. Therefore, structural ensembles often offer more useful representations of proteins than individual conformations. Here, we describe how the well-established principles of protein structure determination should be extended to the case of protein structural ensembles determination. These principles concern primarily how to deal with conformationally heterogeneous states, and with experimental measurements that are averaged over such states and affected by a variety of errors. We first review the vast literature of recent methods that combine experimental and computational information to model structural ensembles, highlighting their similarities and differences. We then address some conceptual problems in the determination of structural ensembles and define future goals towards the establishment of objective criteria for the comparison, validation, visualization, and dissemination of such ensembles.

The human proteome includes many disordered proteins. Although these proteins are closely linked with a range of human diseases, no clinically approved drug targets them in their monomeric forms. This situation arises, at least in part, from the current lack of understanding of the mechanisms by which small molecules bind proteins that do not fold into well-defined conformations. To explore possible solutions to this problem, we discuss quite generally how an overall decrease in the free energy associated with intermolecular binding can originate from different combinations of enthalpic and entropic contributions. We then consider more specifically a mechanism of binding by which small molecules can affect the conformational space of a disordered protein by creating an entropic expansion in which more conformations of the protein become populated.

For DNA molecules, topological complexity occurs exclusively as the result of knotting or linking of the polynucleotide backbone. By contrast, while a few knots and links have been found within the polypeptide backbones of some protein structures, non-planarity can also result from the connectivity between a polypeptide chain and inter- and intra-chain linking via cofactors and disulfide bonds. In this article, we survey the known types of knots, links, and non-planar graphs in protein structures with and without including such bonds and cofactors. Then we present new examples of protein structures containing Möbius ladders and other non-planar graphs as a result of these cofactors. Finally, we propose hypothetical structures illustrating specific disulfide connectivities that would result in the key ring link, the Whitehead link and the 51 knot, the latter two of which have thus far not been identified within protein structures.

Quartz crystal microbalance with dissipation monitoring (QCM-D) is a useful technique for observing the adsorption of molecules onto a protein-functionalized surface in real time. This technique is based on relating changes in the frequency of a piezoelectric sensor chip, onto which molecules are adsorbing, to changes in mass using the Sauerbrey equation. Here, we outline the cleaning, preparation, and analysis involved in a typical QCM-D experiment, from which one can obtain mass adsorption and kinetic binding information.

This study examines the role of a particular kind of linguistic input--talk about the past and future, pretend, and explanations, that is, talk that is decontextualized--in the development of vocabulary, syntax, and narrative skill in typically developing (TD) children and children with pre- or perinatal brain injury (BI). Decontextualized talk has been shown to be particularly effective in predicting children's language skills, but it is not clear why. We first explored the nature of parent decontextualized talk and found it to be linguistically richer than contextualized talk in parents of both TD and BI children. We then found, again for both groups, that parent decontextualized talk at child age 30 months was a significant predictor of child vocabulary, syntax, and narrative performance at kindergarten, above and beyond the child's own early language skills, parent contextualized talk and demographic factors. Decontextualized talk played a larger role in predicting kindergarten syntax and narrative outcomes for children with lower syntax and narrative skill at age 30 months, and also a larger role in predicting kindergarten narrative outcomes for children with BI than for TD children. The difference between the 2 groups stemmed primarily from the fact that children with BI had lower narrative (but not vocabulary or syntax) scores than TD children. When the 2 groups were matched in terms of narrative skill at kindergarten, the impact that decontextualized talk had on narrative skill did not differ for children with BI and for TD children. Decontextualized talk is thus a strong predictor of later language skill for all children, but may be particularly potent for children at the lower-end of the distribution for language skill. The findings also suggest that variability in the language development of children with BI is influenced not only by the biological characteristics of their lesions, but also by the language input they receive.

Previous methods for analyzing protein–ligand binding events using the quartz crystal microbalance with dissipation monitoring (QCM-D) fail to account for unintended binding that inevitably occurs during surface measurements and obscure kinetic information. In this article, we present a system of differential equations that accounts for both reversible and irreversible unintended interactions. This model is tested on three protein–ligand systems, each of which has different features, to establish the feasibility of using the QCM-D for protein binding analysis. Based on this analysis, we were able to obtain kinetic information for the intended interaction that is consistent with those obtained in literature via bulk-phase methods. In the appendix , we include a method for decoupling these from the intended binding events and extracting relevant affinity information.

Both lysine and arginine residues are particularly important at receptor sites for binding anionic ligands. These receptor sites may become compromised via non-enzymatic glycation. While lysine residues are glycated in the presence of glucose, arginine residues are predominantly glycated by α-oxoaldehydes like glyoxal. This study used a quartz crystal microbalance with dissipation monitoring (QCM-D) to examine the binding affinity of surface immobilized human serum albumin (HSA) to hemin after the HSA was pre-incubated with glucose or glyoxal. We found it necessary to pre-expose the HSA functionalized crystal surface to hemin to block irreversible unintended interactions. Glycation with glucose showed little affect on HSA’s affinity for hemin, however, modification with glyoxal showed diminished hemin binding capacity. Despite the hemin-blocking step, we were unable to obtain K d values consistent with those in literature, which we attribute to other unaccounted for nonspecific interactions. This study highlights the need for a kinetic QCM-D analysis method that accounts for unintended interactions at the sensor surface so that the hemin-blocking step may be eliminated.