Nature's Shortcut to Protein Folding

A Perspective on Interdicting in Protein Misfolding for Therapeutic Drug Design: Modulating the Formation of Nonlocal Contacts in α-Synuclein as a Strategy against Parkinson's Disease

In recent work we proposed that interdiction in the earliest contact-formation events along the folding pathway of key viral proteins could provide a novel avenue for therapeutic drug design. In this Perspective we explore the potential applicability of the protein folding interdiction strategy in the realm of neurodegenerative diseases with a specific focus on synucleinopathies. In order to fulfill this goal we review the interdiction proposal and its practical challenges, and we present new results concerning design strategies for possible peptide drugs that could be useful in preventing α-synuclein aggregation.

Interdiction in the Early Folding of the p53 DNA-Binding Domain Leads to Its Amyloid-Like Misfolding

In this article, we investigate two issues: (a) the initial contact formation events along the folding pathway of the DNA-binding domain of the tumor suppressor protein p53 (core p53); and (b) the intermolecular events leading to its conversion into a prion-like form upon incubation with peptide P8(250-257). In the case of (a), the calculations employ the sequential collapse model (SCM) to identify the segments involved in the initial contact formation events that nucleate the folding pathway. The model predicts that there are several possible initial non-local contacts of comparative stability. The most stable of these possible initial contacts involve the protein segments 159AMAIY163 and 251ILTII255, and it is the only native-like contact. Thus, it is predicted to constitute “Nature’s shortcut” to the native structure of the core domain of p53. In the case of issue (b), these findings are then combined with experimental evidence showing that the incubation of the core domain of p53 with peptide P8(250-257), which is equivalent to the native protein segment 250PILTIITL257, leads to an amyloid conformational transition. It is explained how the SCM predicts that P8(250-257) effectively interdicts in the formation of the most stable possible initial contact and, thereby, disrupts the subsequent normal folding. Interdiction by polymeric P8(250-257) seeds is also studied. It is then hypothesized that enhanced folding through one or several of the less stable contacts could play a role in P8(250-257)-promoted core p53 amyloid misfolding. These findings are compared to previous results obtained for the prion protein. Experiments are proposed to test the hypothesis presented regarding core p53 amyloid misfolding.

Protein Folding Interdiction Strategy for Therapeutic Drug Development in Viral Diseases: Ebola VP40 and Influenza A M1

In a recent paper, we proposed the folding interdiction target region (FITR) strategy for therapeutic drug design in SARS-CoV-2. This paper expands the application of the FITR strategy by proposing therapeutic drug design approaches against Ebola virus disease and influenza A. We predict target regions for folding interdicting drugs on correspondingly relevant structural proteins of both pathogenic viruses: VP40 of Ebola, and matrix protein M1 of influenza A. Identification of the protein targets employs the sequential collapse model (SCM) for protein folding. It is explained that the model predicts natural peptide candidates in each case from which to start the search for therapeutic drugs. The paper also discusses how these predictions could be tested, as well as some challenges likely to be found when designing effective therapeutic drugs from the proposed peptide candidates. The FITR strategy opens a potential new avenue for the design of therapeutic drugs that promises to be effective against infectious diseases.

Identification of Two Early Folding Stage Prion Non-Local Contacts Suggested to Serve as Key Steps in Directing the Final Fold to Be Either Native or Pathogenic

The initial steps of the folding pathway of the C-terminal domain of the murine prion protein mPrP(90–231) are predicted based on the sequential collapse model (SCM). A non-local dominant contact is found to form between the connecting region between helix 1 and β-sheet 1 and the C-terminal region of helix 3. This non-local contact nucleates the most populated molten globule-like intermediate along the folding pathway. A less stable early non-local contact between segments 120–124 and 179–183, located in the middle of helix 2, promotes the formation of a less populated molten globule-like intermediate. The formation of the dominant non-local contact constitutes an example of the postulated Nature’s Shortcut to the prion protein collapse into the native structure. The possible role of the less populated molten globule-like intermediate is explored as the potential initiation point for the folding for three pathogenic mutants (T182A, I214V, and Q211P in mouse prion numbering) of the prion protein.

The Role of Configurational Entropy in Miniprotein Stability

Predicting protein stability is a challenge due to the many competing thermodynamic effects. Through de novo protein design, one begins with a target structure and searches for a sequence that will fold into it. Previous work by Rocklin et al. introduced a data set of more than 16,000 miniproteins spanning four structural topologies with information on stability. These structures were characterized with a set of 46 structural descriptors, with no explicit inclusion of configurational entropy (S_cnf). Our work focused on creating a set of 17 descriptors intended to capture variations in S_cnf and its comparison to an extended set of 113 structural and energy model features that extend the Rocklin et al. feature set (R). The S_cnf descriptors statistically discriminate between stable and unstable distributions within topologies and best describe EEHEE topology stability (where E = β sheet and H = α helix). Between 50 and 80% of the variation in each S_cnf descriptor is described by linear combinations of R features. Despite containing useful information about minipeptide stability, providing S_cnf features as inputs to machine learning models does not improve overall performance when predicting protein stability, as the R features sufficiently capture the implicit variations.

Interdiction of Protein Folding for Therapeutic Drug Development in SARS CoV-2

In this article, we predict the folding initiation events of the ribose phosphatase domain of protein Nsp3 and the receptor binding domain of the spike protein from the severe acute respiratory syndrome (SARS) coronavirus-2. The calculations employ the sequential collapse model and the crystal structures to identify the segments involved in the initial contact formation events of both viral proteins. The initial contact locations may provide good targets for therapeutic drug development. The proposed strategy is based on a drug binding to the contact location, thereby aiming to prevent protein folding. Peptides are suggested as a natural choice for such protein folding interdiction drugs.

Probing the conformational landscape and thermochemistry of DNA dinucleotide anions via helium nanodroplet infrared action spectroscopy

Isolation of biomolecules in vacuum facilitates characterization of the intramolecular interactions that determine three-dimensional structure, but experimental quantification of conformer thermochemistry remains challenging. Infrared spectroscopy of molecules trapped in helium nanodroplets is a promising methodology for the measurement of thermochemical parameters. When molecules are captured in a helium nanodroplet, the rate of cooling to an equilibrium temperature of ca. 0.4 K is generally faster than the rate of isomerization, resulting in "shock-freezing" that kinetically traps molecules in local conformational minima. This unique property enables the study of temperature-dependent conformational equilibria via infrared spectroscopy at 0.4 K, thereby avoiding the deleterious effects of spectral broadening at higher temperatures. Herein, we demonstrate the first application of this approach to ionic species by coupling electrospray ionization mass spectrometry (ESI-MS) with helium nanodroplet infrared action spectroscopy to probe the structure and thermochemistry of deprotonated DNA dinucleotides. Dinucleotide anions were generated by ESI, confined in an ion trap at temperatures between 90 and 350 K, and entrained in traversing helium nanodroplets. The infrared action spectra of the entrained ions show a strong dependence on pre-pickup ion temperature, consistent with the preservation of conformer population upon cooling to 0.4 K. Non-negative matrix factorization was utilized to identify component conformer infrared spectra and determine temperature-dependent conformer populations. Relative enthalpies and entropies of conformers were subsequently obtained from a van't Hoff analysis. IR spectra and conformer thermochemistry are compared to results from ion mobility spectrometry (IMS) and electronic structure methods. The implementation of ESI-MS as a source of dopant molecules expands the diversity of molecules accessible for thermochemical measurements, enabling the study of larger, non-volatile species.

The Molten Globule, and Two-State vs. Non-Two-State Folding of Globular Proteins

From experimental studies of protein folding, it is now clear that there are two types of folding behavior, i.e., two-state folding and non-two-state folding, and understanding the relationships between these apparently different folding behaviors is essential for fully elucidating the molecular mechanisms of protein folding. This article describes how the presence of the two types of folding behavior has been confirmed experimentally, and discusses the relationships between the two-state and the non-two-state folding reactions, on the basis of available data on the correlations of the folding rate constant with various structure-based properties, which are determined primarily by the backbone topology of proteins. Finally, a two-stage hierarchical model is proposed as a general mechanism of protein folding. In this model, protein folding occurs in a hierarchical manner, reflecting the hierarchy of the native three-dimensional structure, as embodied in the case of non-two-state folding with an accumulation of the molten globule state as a folding intermediate. The two-state folding is thus merely a simplified version of the hierarchical folding caused either by an alteration in the rate-limiting step of folding or by destabilization of the intermediate.

Successes and challenges in simulating the folding of large proteins

Computational simulations of protein folding can be used to interpret experimental folding results, to design new folding experiments, and to test the effects of mutations and small molecules on folding. However, whereas major experimental and computational progress has been made in understanding how small proteins fold, research on larger, multidomain proteins, which comprise the majority of proteins, is less advanced. Specifically, large proteins often fold via long-lived partially folded intermediates, whose structures, potentially toxic oligomerization, and interactions with cellular chaperones remain poorly understood. Molecular dynamics based folding simulations that rely on knowledge of the native structure can provide critical, detailed information on folding free energy landscapes, intermediates, and pathways. Further, increases in computational power and methodological advances have made folding simulations of large proteins practical and valuable. Here, using serpins that inhibit proteases as an example, we review native-centric methods for simulating the folding of large proteins. These synergistic approaches range from Gō and related structure-based models that can predict the effects of the native structure on folding to all-atom-based methods that include side-chain chemistry and can predict how disease-associated mutations may impact folding. The application of these computational approaches to serpins and other large proteins highlights the successes and limitations of current computational methods and underscores how computational results can be used to inform experiments. These powerful simulation approaches in combination with experiments can provide unique insights into how large proteins fold and misfold, expanding our ability to predict and manipulate protein folding.