Analytical methods for structural ensembles and dynamics of intrinsically disordered proteins

Establishment of iPSC lines and zebrafish with loss-of-function AHDC1 variants: models for Xia-Gibbs syndrome

Xia-Gibbs syndrome (XGS) is a syndromic form of intellectual disability caused by heterozygous AHDC1 variants, but the pathophysiological mechanisms underlying this syndrome are still unclear. In this manuscript, we describe the development of two different functional models: three induced pluripotent stem cell (iPSC) lines with different loss-of-function (LoF) AHDC1 variants, derived by reprogramming peripheral blood mononuclear cells from XGS patients, and a zebrafish strain with a LoF variant in the ortholog gene (ahdc1) obtained through CRISPR/Cas9-mediated editing. The three iPSC lines showed expression of pluripotency factors (SOX2, SSEA-4, OCT3/4, and NANOG). To verify the capacity of iPSC to differentiate into the three germ layers, we obtained embryoid bodies (EBs), induced their differentiation, and confirmed the mRNA expression of ectodermal, mesodermal, and endodermal markers using the TaqMan hPSC Scorecard. The iPSC lines were also approved for the following quality tests: chromosomal microarray analysis (CMA), mycoplasma testing, and short tandem repeat (STR) DNA profiling. The zebrafish model has an insertion of four base pairs in the ahdc1 gene, is fertile, and breeding between heterozygous and wild-type (WT) animals generated offspring in a genotypic proportion in agreement with Mendelian law. The established iPSC and zebrafish lines were deposited on the hpscreg.eu and zfin.org platforms, respectively. These biological models are the first for XGS and will be used in future studies that investigate the pathophysiology of this syndrome, unraveling its underlying molecular mechanisms.

Fuzzy Drug Targets: Disordered Proteins in the Drug-Discovery Realm

Intrinsically disordered proteins (IDPs) and regions (IDRs) form a large part of the eukaryotic proteome. Contrary to the structure-function paradigm, the disordered proteins perform a myriad of functions in vivo. Consequently, they are involved in various disease pathways and are plausible drug targets. Unlike folded proteins, that have a defined structure and well carved out drug-binding pockets that can guide lead molecule selection, the disordered proteins require alternative drug-development methodologies that are based on an acceptable picture of their conformational ensemble. In this review, we discuss various experimental and computational techniques that contribute toward understanding IDP "structure" and describe representative pursuances toward IDP-targeting drug development. We also discuss ideas on developing rational drug design protocols targeting IDPs.

Efficient Purification of Cowpea Chlorotic Mottle Virus by a Novel Peptide Aptamer

The cowpea chlorotic mottle virus (CCMV) is a plant virus explored as a nanotechnological platform. The robust self-assembly mechanism of its capsid protein allows for drug encapsulation and targeted delivery. Additionally, the capsid nanoparticle can be used as a programmable platform to display different molecular moieties. In view of future applications, efficient production and purification of plant viruses are key steps. In established protocols, the need for ultracentrifugation is a significant limitation due to cost, difficult scalability, and safety issues. In addition, the purity of the final virus isolate often remains unclear. Here, an advanced protocol for the purification of the CCMV from infected plant tissue was developed, focusing on efficiency, economy, and final purity. The protocol involves precipitation with PEG 8000, followed by affinity extraction using a novel peptide aptamer. The efficiency of the protocol was validated using size exclusion chromatography, MALDI-TOF mass spectrometry, reversed-phase HPLC, and sandwich immunoassay. Furthermore, it was demonstrated that the final eluate of the affinity column is of exceptional purity (98.4%) determined by HPLC and detection at 220 nm. The scale-up of our proposed method seems to be straightforward, which opens the way to the large-scale production of such nanomaterials. This highly improved protocol may facilitate the use and implementation of plant viruses as nanotechnological platforms for in vitro and in vivo applications.

Monitoring α-synuclein aggregation

Synucleinopathies, including Parkinson's disease (PD), dementia with Lewy Bodies (DLB), and multiple system atrophy (MSA), are characterized by the misfolding and subsequent aggregation of alpha-synuclein (α-syn) that accumulates in cytoplasmic inclusions bodies in the cells of affected brain regions. Since the seminal report of likely-aggregated α-syn presence within the Lewy bodies by Spillantini et al. in 1997, the keyword "synuclein aggregation" has appeared in over 6000 papers (Source: PubMed October 2022). Studying, observing, describing, and quantifying α-syn aggregation is therefore of paramount importance, whether it happens in tubo, in vitro, in post-mortem samples, or in vivo. The past few years have witnessed tremendous progress in understanding aggregation mechanisms and identifying various polymorphs. In this context of growing complexity, it is of utmost importance to understand what tools we possess, what exact information they provide, and in what context they may be applied. Nonetheless, it is also crucial to rationalize the relevance of the information and the limitations of these methods for gauging the final result. In this review, we present the main techniques that have shaped the current views about α-syn structure and dynamics, with particular emphasis on the recent breakthroughs that may change our understanding of synucleinopathies.

[Aggregation and spread of synuclein in Parkinson's disease]

The vast majority of neurodegenerative diseases are associated with an accumulation of undegraded and aggregated proteins. Hence the word proteinopathies is now used to refer to these neurodegenerative diseases. The synucleinopathies are one component of them, in particular in Parkinson's disease. The neuropathological features of Parkinson's disease are the progressive loss of dopamine neurons in the midbrain and the formation of aggregates composed mainly of a-synuclein protein. Experimental evidence suggests that under pathological conditions, normal soluble a-synuclein protein adopts an abnormal folding and subsequently aggregates, with a propensity to spread throughout the central nervous system. This review article discusses the specifics of a-synuclein aggregation and emerging mechanisms for understanding its spread and aims at providing a molecular explanation for the progression of the disease in humans.

The Two-Step Clustering Approach for Metastable States Learning

Understanding the energy landscape and the conformational dynamics is crucial for studying many biological or chemical processes, such as protein-protein interaction and RNA folding. Molecular Dynamics (MD) simulations have been a major source of dynamic structure. Although many methods were proposed for learning metastable states from MD data, some key problems are still in need of further investigation. Here, we give a brief review on recent progresses in this field, with an emphasis on some popular methods belonging to a two-step clustering framework, and hope to draw more researchers to contribute to this area.

Transient multimers modulate conformer abundances of prion protein monomer through conformational selection

Prions are known to be involved in neurodegenerative pathologies such as Creutzfeld-Jakob disease. Current models point to a molecular event which rely on a transmissible structural change that leads to the production of β-sheet-rich prion conformer (PrP^Sc). PrP^Sc itself has the capability to trigger the structural rearrangement of the ubiquitously present prion (PrP^c) substrate in a self-perpetuating cascade. In this article, we demonstrate that recombinant PrP^c exists in a conformational equilibrium. The conformers’ abundances were shown to be dependent on PrP^c concentration through the formation of transient multimers leading to conformational selection. The study of PrP^c mutants that follow dedicated oligomerization pathways demonstrated that the conformers’ relative abundances are modified, thus reinforcing the assertion that the nature of conformers’ interactions orient the oligomerization pathways. Further this result can be viewed as the “signature” of an aborted oligomerization process. This discovery sheds a new light on the possible origin of prion protein diseases, namely that a change in prion protein structure could be transmitted through the formation of transient multimers having different conformer compositions. This could explain the selection of a transient multimeric type that could be viewed as the precursor of PrP^Sc responsible for structural information transmission, and strain apparition.

DNP-Enhanced MAS NMR: A Tool to Snapshot Conformational Ensembles of α-Synuclein in Different States

Intrinsically disordered proteins dynamically sample a wide conformational space and therefore do not adopt a stable and defined three-dimensional conformation. The structural heterogeneity is related to their proper functioning in physiological processes. Knowledge of the conformational ensemble is crucial for a complete comprehension of this kind of proteins. We here present an approach that utilizes dynamic nuclear polarization-enhanced solid-state NMR spectroscopy of sparsely isotope-labeled proteins in frozen solution to take snapshots of the complete structural ensembles by exploiting the inhomogeneously broadened line-shapes. We investigated the intrinsically disordered protein α-synuclein (α-syn), which plays a key role in the etiology of Parkinson’s disease, in three different physiologically relevant states. For the free monomer in frozen solution we could see that the so-called “random coil conformation” consists of α-helical and β-sheet-like conformations, and that secondary chemical shifts of neighboring amino acids tend to be correlated, indicative of frequent formation of secondary structure elements. Based on these results, we could estimate the number of disordered regions in fibrillar α-syn as well as in α-syn bound to membranes in different protein-to-lipid ratios. Our approach thus provides quantitative information on the propensity to sample transient secondary structures in different functional states. Molecular dynamics simulations rationalize the results.

Molecular Dynamics Simulations Combined with Nuclear Magnetic Resonance and/or Small-Angle X-ray Scattering Data for Characterizing Intrinsically Disordered Protein Conformational Ensembles

The concept of intrinsically disordered proteins (IDPs) has emerged relatively slowly, but over the past 20 years, it has become an intense research area in structural biology. Indeed, because of their considerable flexibility and structural heterogeneity, the determination of IDP conformational ensemble is particularly challenging and often requires a combination of experimental measurements and computational approaches. With the improved accuracy of all-atom force fields and the increasing computing performances, molecular dynamics (MD) simulations have become more and more reliable to generate realistic conformational ensembles. And the combination of MD simulations with experimental approaches, such as nuclear magnetic resonance (NMR) and/or small-angle X-ray scattering (SAXS) allows one to converge toward a more accurate and exhaustive description of IDP structures. In this Review, we discuss the state of the art of MD simulations of IDP conformational ensembles, with a special focus on studies that back-calculated and directly compared theoretical and experimental NMR or SAXS observables, such as chemical shifts (CS), ³J-couplings (³Jc), residual dipolar couplings (RDC), or SAXS intensities. We organize the review in three parts. In the first section, we discuss the studies which used NMR and/or SAXS data to test and validate the development of force fields or enhanced sampling techniques. In the second part, we explore different methods for the refinement of MD-derived structural ensembles, such as NMR or SAXS data-restrained MD simulations or ensemble reweighting to better fit experiments. Finally, we survey some recent studies combining MD simulations with NMR and/or SAXS measurements to investigate the relationship between IDP conformational ensemble and biological activity, as well as their implication in human diseases. From this review, we noticed that quite a few studies compared MD-generated conformational ensembles with both NMR and SAXS measurements to validate IDP structures at both local and global levels. Yet, beside the IDP propensity to form local secondary structures, their dynamic extension or compactness also appears important for their activity. Thus, we believe that a close synergy between MD simulations, NMR, and SAXS experiments would be greatly appropriate to address the challenges of characterizing the disordered structures of proteins and their complexes, relative to their biological functions.

Metadynamic metainference: Convergence towards force field independent structural ensembles of a disordered peptide

Metadynamic metainference has been recently introduced as a theoretical framework to determine structural ensembles by combining and weighting their noise multiple sources of experimental data with molecular mechanics force fields and metadynamics simulations. Here we build upon these initial developments to further extend and streamline the computational approach. We also show that metadynamic metainference can actually determine a structural ensemble for a disordered peptide that is essentially independent from the employed force field. We further show that it is possible to use a very computationally efficient implicit solvent force field in the place of very expensive state-of-the-art explicit solvent ones without a significant loss in accuracy.

Foreword to 'Quantitative and analytical relations in biochemistry'-a special issue in honour of Donald J. Winzor's 80th birthday

The purpose of this special issue is to honour Professor Donald J. Winzor's long career as a researcher and scientific mentor, and to celebrate the milestone of his 80th birthday. Throughout his career, Don has been renowned for his development of clever approximations to difficult quantitative relations governing a range of biophysical measurements. The theme of this special issue, 'Quantitative and analytical relations in biochemistry', was chosen to reflect this aspect of Don's scientific approach.