Atomic Detail of Protein Folding Revealed by an Ab Initio Reappraisal of Circular Dichroism

Molecular interactions between gelatin-derived carbon quantum dots and Apo-myoglobin: Implications for carbon nanomaterial frameworks

Carbon nanomaterials (CNMs), including carbon quantum dots (CQDs), have found widespread use in biomedical research due to their low toxicity, chemical tunability, and tailored applications. Yet, there exists a gap in our understanding of the molecular interactions between biomacromolecules and these novel carbon-centered platforms. Using gelatin-derived CQDs as a model CNM, we have examined the impact of this exemplar nanomaterial on apo-myoglobin (apo-Mb), an oxygen-storage protein. Intrinsic fluorescence measurements revealed that the CQDs induced conformational changes in the tertiary structure of native, partially unfolded, and unfolded states of apo-Mb. Titration with CQDs also resulted in significant changes in the secondary structural elements in both native (holo) and apo-Mb, as evidenced by the circular dichroism (CD) analyses. These changes suggested a transition from isolated helices to coiled-coils during the loss of the helical structure of the apo-protein. Infra-red spectroscopic data further underscored the interactions between the CQDs and the amide backbone of apo-myoglobin. Importantly, the CQDs-driven structural perturbations resulted in compromised heme binding to apo-myoglobin and, therefore, potentially can attenuate oxygen storage and diffusion. However, a cytotoxicity assay demonstrated the continued viability of neuroblastoma cells exposed to these carbon nanomaterials. These results, for the first time, provide a molecular roadmap of the interplay between carbon-based nanomaterial frameworks and biomacromolecules.

Tidying up the conformational ensemble of a disordered peptide by computational prediction of spectroscopic fingerprints

The most advanced structure prediction methods are powerless in exploring the conformational ensemble of disordered peptides and proteins and for this reason the "protein folding problem" remains unsolved. We present a novel methodology that enables the accurate prediction of spectroscopic fingerprints (circular dichroism, infrared, Raman, and Raman optical activity), and by this allows for "tidying up" the conformational ensembles of disordered peptides and disordered regions in proteins. This concept is elaborated for and applied to a dodecapeptide, whose spectroscopic fingerprint is measured and theoretically predicted by means of enhanced-sampling molecular dynamics coupled with quantum mechanical calculations. Following this approach, we demonstrate that peptides lacking a clear propensity for ordered secondary-structure motifs are not randomly, but only conditionally disordered. This means that their conformational landscape, or phase-space, can be well represented by a basis-set of conformers including about 10 to 100 structures. The implications of this finding have profound consequences both for the interpretation of experimental electronic and vibrational spectral features of peptides in solution and for the theoretical prediction of these features using accurate and computationally expensive techniques. The here-derived methods and conclusions are expected to fundamentally impact the rationalization of so-far elusive structure-spectra relationships for disordered peptides and proteins, towards improved and versatile structure prediction methods.

RNA folding pathways from all-atom simulations with a variationally improved history-dependent bias

Atomically detailed simulations of RNA folding have proven very challenging in view of the difficulties of developing realistic force fields and the intrinsic computational complexity of sampling rare conformational transitions. As a step forward in tackling these issues, we extend to RNA an enhanced path-sampling method previously successfully applied to proteins. In this scheme, the information about the RNA's native structure is harnessed by a soft history-dependent biasing force promoting the generation of productive folding trajectories in an all-atom force field with explicit solvent. A rigorous variational principle is then applied to minimize the effect of the bias. Here, we report on an application of this method to RNA molecules from 20 to 47 nucleotides long and increasing topological complexity. By comparison with analog simulations performed on small proteins with similar size and architecture, we show that the RNA folding landscape is significantly more frustrated, even for relatively small chains with a simple topology. The predicted RNA folding mechanisms are found to be consistent with the available experiments and some of the existing coarse-grained models. Due to its computational performance, this scheme provides a promising platform to efficiently gather atomistic RNA folding trajectories, thus retain the information about the chemical composition of the sequence.

Study on the Interaction Mechanism of Methoxy Polyethylene Glycol Maleimide with Sweet Potato β-Amylase

In this study, sweet potato β-amylase (SPA) was modified by methoxy polyethylene glycol maleimide (molecular weight 5000, Mal-mPEG5000) to obtain the Mal-mPEG5000-SPA modified β-amylase and the interaction mechanism between SPA and Mal-mPEG5000 was investigated. the changes in the functional groups of different amide bands and modifications in the secondary structure of enzyme protein were analyzed using infrared spectroscopy and circular dichroism spectroscopy. The addition of Mal-mPEG5000 transformed the random curl in the SPA secondary structure into a helix structure, forming a folded structure. The Mal-mPEG5000 improved the thermal stability of SPA and protected the structure of the protein from breaking by the surrounding. The thermodynamic analysis further implied that the intermolecular forces between SPA and Mal-mPEG5000 were hydrophobic interactions and hydrogen bonds due to the positive values of ΔH^θ and ΔS^θ. Furthermore, the calorie titration data showed that the binding stoichiometry for the complexation of Mal-mPEG5000 to SPA was 1.26, and the binding constant was 1.256 × 10⁷ mol/L. The binding reaction resulted from negative enthalpy, indicating that the interaction of SPA and Mal-mPEG5000 was induced by the van der Waals force and hydrogen bonding. The UV results showed the formation of non-luminescent material during the interaction, the Fluorescence results confirmed that the mechanism between SPA and Mal-mPEG5000 was static quenching. According to the fluorescence quenching measurement, the binding constant (K_A) values were 4.65 × 10⁴ L·mol^-1 (298K), 5.56 × 10⁴ L·mol^-1 (308K), and 6.91 × 10⁴ L·mol^-1 (318K), respectively.

Nanopore single-molecule biosensor in protein denaturation analysis

Unclear issues in protein studies include but not limited to the stability and denaturation mechanism in the presence of denaturants. Herein, we report a dynamic monitoring approach based on nanopore single-molecule biosensor, which can detect the protein's folding and unfolding transitions by recording a nanopore ionic current. When gradually increasing the concentration of denaturant guanidine hydrochloride (GdmCl), sensitive responses were observed with lysozyme unfolding. The emergence of the featured biphasic-pulse demonstrated the existence of a stable intermediate. It was the first time to experimentally confirm the dynamic equilibrium between the intermediate and the native states at single molecule level, therefore consolidating the standpoint of lysozyme denaturation process following the three-state model. Additionally, we got more insights into the conformation about the intermediate as globular-like structure, larger gyration radius, and enhanced positive charge density. We considered that the manner of denaturant toward lysozyme adopts the "direct" model based on stronger electrostatic and van der Waals forces. Nanopore biosensor exhibited excellent sensitivity with a low detection concentration of 280 pM and reproducibility in analysing the folding intermediate of lysozyme.

Functional, pathogenic, and pharmacological roles of protein folding intermediates

Protein expression and function in eukaryotic cells are tightly harmonized processes modulated by the combination of different layers of regulation, including transcription, processing, stability, and translation of messenger RNA, as well as assembly, maturation, sorting, recycling, and degradation of polypeptides. Integrating all these pathways and the protein quality control machinery, deputed to avoid the production and accumulation of aberrantly folded proteins, determines protein homeostasis. Over the last decade, the combined development of accurate time-resolved experimental techniques and efficient computer simulations has opened the possibility of investigating biological mechanisms at atomic resolution with physics-based models. A meaningful example is the reconstruction of protein folding pathways at atomic resolution, which has enabled the characterization of the folding kinetics of biologically relevant globular proteins consisting of a few hundred amino acids. Combining these innovative computational technologies with rigorous experimental approaches reveals the existence of non-native metastable states transiently appearing along the folding process of such proteins. Here, we review the primary evidence indicating that these protein folding intermediates could play roles in disparate biological processes, from the posttranslational regulation of protein expression to disease-relevant protein misfolding mechanisms. Finally, we discuss how the information encoded into protein folding pathways could be exploited to design an entirely new generation of pharmacological agents capable of promoting the selective degradation of protein targets.

Upon DFT-D3 dispersion correction and ECD spectral confirmation, only several conformers can stably coexist for three fungal cycloaspeptides (A, D, G)

Dispersion correction in theoretical determination of cyclopeptide conformations is emphasized. Whether in gas approximation or in solvation simulation, the density functional theory with London dispersion correction (DFT-D3) demonstrates that only 2-3 conformers can stably coexist for cycloaspeptides (A, D, G) at B3LYP-D3 and CAM-B3LYP-D3. Conformational rationality is confirmed by electronic circular dichroism (ECD). Whether for Cotton effect or for excitation energy, TD-B3LYP-D3 has better performances than TD-CAM-B3LYP-D3 because the former can better reproduce the experiment. A molecular orbital analysis is used to interpret ECD, where two energy bands observed in experiment originates from the ππ* transitions other than the σπ* transitions. Long-range correction and solvent effect make H-bonds shorten, and dispersion correction makes them further shorten.

Long-range allostery mediates the regulation of plasminogen activator inhibitor-1 by cell adhesion factor vitronectin

The serpin plasminogen activator inhibitor 1 (PAI-1) spontaneously undergoes a massive structural change from a metastable and active conformation, with a solvent-accessible reactive center loop (RCL), to a stable, inactive, or latent conformation, with the RCL inserted into the central β-sheet. Physiologically, conversion to the latent state is regulated by the binding of vitronectin, which hinders the latency transition rate approximately twofold. The molecular mechanisms leading to this rate change are unclear. Here, we investigated the effects of vitronectin on the PAI-1 latency transition using all-atom path sampling simulations in explicit solvent. In simulated latency transitions of free PAI-1, the RCL is quite mobile as is the gate, the region that impedes RCL access to the central β-sheet. This mobility allows the formation of a transient salt bridge that facilitates the transition; this finding rationalizes existing mutagenesis results. Vitronectin binding reduces RCL and gate mobility by allosterically rigidifying structural elements over 40 Å away from the binding site, thus blocking transition to the latent conformation. The effects of vitronectin are propagated by a network of dynamically correlated residues including a number of conserved sites that were previously identified as important for PAI-1 stability. Simulations also revealed a transient pocket populated only in the vitronectin-bound state, corresponding to a cryptic drug-binding site identified by crystallography. Overall, these results shed new light on PAI-1 latency transition regulation by vitronectin and illustrate the potential of path sampling simulations for understanding functional protein conformational changes and for facilitating drug discovery.

Accurate Machine Learning Prediction of Protein Circular Dichroism Spectra with Embedded Density Descriptors

A data-driven approach to simulate circular dichroism (CD) spectra is appealing for fast protein secondary structure determination, yet the challenge of predicting electric and magnetic transition dipole moments poses a substantial barrier for the goal. To address this problem, we designed a new machine learning (ML) protocol in which ordinary pure geometry-based descriptors are replaced with alternative embedded density descriptors and electric and magnetic transition dipole moments are successfully predicted with an accuracy comparable to first-principle calculation. The ML model is able to not only simulate protein CD spectra nearly 4 orders of magnitude faster than conventional first-principle simulation but also obtain CD spectra in good agreement with experiments. Finally, we predicted a series of CD spectra of the Trp-cage protein associated with continuous changes of protein configuration along its folding path, showing the potential of our ML model for supporting real-time CD spectroscopy study of protein dynamics.

Slow Escape from a Helical Misfolded State of the Pore-Forming Toxin Cytolysin A

The pore-forming toxin cytolysin A (ClyA) is expressed as a large α-helical monomer that, upon interaction with membranes, undergoes a major conformational rearrangement into the protomer conformation, which then assembles into a cytolytic pore. Here, we investigate the folding kinetics of the ClyA monomer with single-molecule Förster resonance energy transfer spectroscopy in combination with microfluidic mixing, stopped-flow circular dichroism experiments, and molecular simulations. The complex folding process occurs over a broad range of time scales, from hundreds of nanoseconds to minutes. The very slow formation of the native state occurs from a rapidly formed and highly collapsed intermediate with large helical content and nonnative topology. Molecular dynamics simulations suggest pronounced non-native interactions as the origin of the slow escape from this deep trap in the free-energy surface, and a variational enhanced path-sampling approach enables a glimpse of the folding process that is supported by the experimental data.

A Machine-Learning Protocol for Ultraviolet Protein-Backbone Absorption Spectroscopy under Environmental Fluctuations

Ultraviolet (UV) absorption spectra are commonly used for characterizing the global structure of proteins. However, the theoretical interpretation of UV spectra is hindered by the large number of required expensive ab initio calculations of excited states spanning a huge conformation space. We present a machine-learning (ML) protocol for far-UV (FUV) spectra of proteins, which can predict FUV spectra of proteins with comparable accuracy to density functional theory (DFT) calculations but with 3-4 orders of magnitude reduced computational cost. It further shows excellent predictive power and transferability that can be used to probe structural mutations and protein folding pathways.

Pump-Probe Circular Dichroism Spectroscopy of Cyanobacteriochrome TePixJ Yields: Insights into Its Photoconversion

The bilin-containing photoreceptor TePixJ, a member of the cyanobacteriochrome (CBCR) family of phytochromes, switches between blue-light-absorbing and green-light-absorbing states in order to drive phototaxis in Thermosynechococcus elongatus. Its photoswitching process involves the formation of a thioether linkage between the C10 carbon of phycoviolobilin and the sidechain of Cys494 during the change in state from green-absorbing to blue-absorbing forms. Complex changes in the binding pocket propagate the signal to other domains for downstream signaling. Here, we report time-resolved circular dichroism experiments in addition to pump-probe absorption measurements for interpretation of the biophysical mechanism of the green-to-blue photoconversion process of this receptor.

Pharmacological inactivation of the prion protein by targeting a folding intermediate

Recent computational advancements in the simulation of biochemical processes allow investigating the mechanisms involved in protein regulation with realistic physics-based models, at an atomistic level of resolution. These techniques allowed us to design a drug discovery approach, named Pharmacological Protein Inactivation by Folding Intermediate Targeting (PPI-FIT), based on the rationale of negatively regulating protein levels by targeting folding intermediates. Here, PPI-FIT was tested for the first time on the cellular prion protein (PrP), a cell surface glycoprotein playing a key role in fatal and transmissible neurodegenerative pathologies known as prion diseases. We predicted the all-atom structure of an intermediate appearing along the folding pathway of PrP and identified four different small molecule ligands for this conformer, all capable of selectively lowering the load of the protein by promoting its degradation. Our data support the notion that the level of target proteins could be modulated by acting on their folding pathways, implying a previously unappreciated role for folding intermediates in the biological regulation of protein expression.

Spagnolli, Massignan, Astolfi et al. design a new drug discovery approach, termed Pharmacological Protein Inactivation by Folding Intermediate Targeting, in which folding intermediates of disease-causing proteins are targeted. They test it on the cellular prion protein, identifying ligands stabilizing a folding intermediate and consequently promoting its degradation by the cellular quality control machinery.

The balance between side-chain and backbone-driven association in folding of the α-helical influenza A transmembrane peptide

The correct balance between attractive, repulsive and peptide hydrogen bonding interactions must be attained for proteins to fold correctly. To investigate these important contributors, we sought a comparison of the folding between two 25-residues peptides, the influenza A M2 protein transmembrane domain (M2TM) and the 25-Ala (Ala₂₅ ). M2TM forms a stable α-helix as is shown by circular dichroism (CD) experiments. Molecular dynamics (MD) simulations with adaptive tempering show that M2TM monomer is more dynamic in nature and quickly interconverts between an ensemble of various α-helical structures, and less frequently turns and coils, compared to one α-helix for Ala₂₅ . DFT calculations suggest that folding from the extended structure to the α-helical structure is favored for M2TM compared with Ala₂₅ . This is due to CH⋯O attractive interactions which favor folding to the M2TM α-helix, and cannot be described accurately with a force field. Using natural bond orbital (NBO) analysis and quantum theory atoms in molecules (QTAIM) calculations, 26 CH⋯O interactions and 22 NH⋯O hydrogen bonds are calculated for M2TM. The calculations show that CH⋯O hydrogen bonds, although individually weaker, have a cumulative effect that cannot be ignored and may contribute as much as half of the total hydrogen bonding energy, when compared to NH⋯O, to the stabilization of the α-helix in M2TM. Further, a strengthening of NH⋯O hydrogen bonding interactions is calculated for M2TM compared to Ala₂₅ . Additionally, these weak CH⋯O interactions can dissociate and associate easily leading to the ensemble of folded structures for M2TM observed in folding MD simulations.

All-atom simulation of the HET-s prion replication

Prions are self-replicative protein particles lacking nucleic acids. Originally discovered for causing infectious neurodegenerative disorders, they have also been found to play several physiological roles in a variety of species. Functional and pathogenic prions share a common mechanism of replication, characterized by the ability of an amyloid conformer to propagate by inducing the conversion of its physiological, soluble counterpart. Since time-resolved biophysical experiments are currently unable to provide full reconstruction of the physico-chemical mechanisms responsible for prion replication, one must rely on computer simulations. In this work, we show that a recently developed algorithm called Self-Consistent Path Sampling (SCPS) overcomes the computational limitations of plain MD and provides a viable tool to investigate prion replication processes using state-of-the-art all-atom force fields in explicit solvent. First, we validate the reliability of SCPS simulations by characterizing the folding of a class of small proteins and comparing against the results of plain MD simulations. Next, we use SCPS to investigate the replication of the prion forming domain of HET-s, a physiological fungal prion for which high-resolution structural data are available. Our atomistic reconstruction shows remarkable similarities with a previously reported mechanism of mammalian PrP^Sc propagation obtained using a simpler and more approximate path sampling algorithm. Together, these results suggest that the propagation of prions generated by evolutionary distant proteins may share common features. In particular, in both these cases, prions propagate their conformation through a very similar templating mechanism.

Prions are proteins capable of replicating in absence of nucleic acids. By propagating the information encoded in their conformation, prions exemplify the phenomenon of protein-based inheritance. These peculiar agents are associated with neurodegenerative pathologies in mammals, but also involved in a wide variety of physiological processes occurring in various biological contexts along the evolutionary scale. In this work, we apply a recently developed computational method to study the propagation mechanism of the fungal prion HET-s, using a realistic all-atom model. We find that the replication of HET-s shares fundamental features with the templated conversion of the mammalian prion PrP^Sc.

Unfolding Dynamics of a Photoswitchable Helical Peptide

We present an atomistic force field for the azo-moiety of the photoswitchable FK-11-X peptide. We use the parameters to study the unfolding of the peptide through molecular dynamics simulations. The unfolded ensemble contains many different structures, ranging from a partially unfolded peptide to a fully unfolded structure. The averaged computed far-ultraviolet circular dichroism (CD) spectrum of the set of structures, which was simulated using the newly developed force field, agrees well with experiment. The rate of the simulated unfolding process was estimated to have a time constant of 5.80 ± 0.03 ns from the time evolution of the CD spectrum of the peptide, computed from the backbone conformations sampled over 40 simulated trajectories. Our estimated time constant is faster than, but not inconsistent with, previous experimental estimates from time-resolved infrared and optical rotatory dispersion spectroscopy.

How to learn from inconsistencies: Integrating molecular simulations with experimental data

Molecular simulations and biophysical experiments can be used to provide independent and complementary insights into the molecular origin of biological processes. A particularly useful strategy is to use molecular simulations as a modeling tool to interpret experimental measurements, and to use experimental data to refine our biophysical models. Thus, explicit integration and synergy between molecular simulations and experiments is fundamental for furthering our understanding of biological processes. This is especially true in the case where discrepancies between measured and simulated observables emerge. In this chapter, we provide an overview of some of the core ideas behind methods that were developed to improve the consistency between experimental information and numerical predictions. We distinguish between situations where experiments are used to refine our understanding and models of specific systems, and situations where experiments are used more generally to refine transferable models. We discuss different philosophies and attempt to unify them in a single framework. Until now, such integration between experiments and simulations have mostly been applied to equilibrium data, and we discuss more recent developments aimed to analyze time-dependent or time-resolved data.

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.

Full atomistic model of prion structure and conversion

Prions are unusual protein assemblies that propagate their conformationally-encoded information in absence of nucleic acids. The first prion identified, the scrapie isoform (PrPSc) of the cellular prion protein (PrPC), caused epidemic and epizootic episodes [1]. Most aggregates of other misfolding-prone proteins are amyloids, often arranged in a Parallel-In-Register-β-Sheet (PIRIBS) [2] or β-solenoid conformations [3]. Similar folding models have also been proposed for PrPSc, although none of these have been confirmed experimentally. Recent cryo-electron microscopy (cryo-EM) and X-ray fiber-diffraction studies provided evidence that PrPSc is structured as a 4-rung β-solenoid (4RβS) [4, 5]. Here, we combined different experimental data and computational techniques to build the first physically-plausible, atomic resolution model of mouse PrPSc, based on the 4RβS architecture. The stability of this new PrPSc model, as assessed by Molecular Dynamics (MD) simulations, was found to be comparable to that of the prion forming domain of Het-s, a naturally-occurring β-solenoid. Importantly, the 4RβS arrangement allowed the first simulation of the sequence of events underlying PrPC conversion into PrPSc. This study provides the most updated, experimentally-driven and physically-coherent model of PrPSc, together with an unprecedented reconstruction of the mechanism underlying the self-catalytic propagation of prions.

Ab Initio Study of Circular Dichroism and Circularly Polarized Luminescence of Spin-Allowed and Spin-Forbidden Transitions: From Organic Ketones to Lanthanide Complexes

Complete and restricted active space self-consistent field (CAS-/RAS-SCF) wave function methods are applied for the calculation of circular dichroism (CD) and circularly polarized luminescence (CPL) of a series of molecules comprising four organic ketones, the chiral cobalt(III) complex [Co(en)₃]³⁺, and the europium(III) complex [Eu(DPA)₃]^3-. The ab initio results are in good agreement with the experimental data and previous results obtained with Kohn-Sham density functional theory in the case of the spin-allowed transitions. CD and CPL properties are calculated ab initio for the spin-forbidden transitions of both a transition metal and a lanthanide complex.

All-Atom Simulations Reveal How Single-Point Mutations Promote Serpin Misfolding

Protein misfolding is implicated in many diseases, including serpinopathies. For the canonical inhibitory serpin α₁-antitrypsin, mutations can result in protein deficiencies leading to lung disease, and misfolded mutants can accumulate in hepatocytes, leading to liver disease. Using all-atom simulations based on the recently developed bias functional algorithm, we elucidate how wild-type α₁-antitrypsin folds and how the disease-associated S (Glu264Val) and Z (Glu342Lys) mutations lead to misfolding. The deleterious Z mutation disrupts folding at an early stage, whereas the relatively benign S mutant shows late-stage minor misfolding. A number of suppressor mutations ameliorate the effects of the Z mutation, and simulations on these mutants help to elucidate the relative roles of steric clashes and electrostatic interactions in Z misfolding. These results demonstrate a striking correlation between atomistic events and disease severity and shine light on the mechanisms driving chains away from their correct folding routes.