Ruggedness in the Free Energy Landscape Dictates Misfolding of the Prion Protein

Understanding the heterogeneity intrinsic to protein folding

Relating the native fold of a protein to its amino acid sequence remains a fundamental problem in biology. While computer algorithms have demonstrated recently their prowess in predicting what structure a particular amino acid sequence will fold to, an understanding of how and why a specific protein fold is achieved remains elusive. A major challenge is to define the role of conformational heterogeneity during protein folding. Recent experimental studies, utilizing time-resolved FRET, hydrogen-exchange coupled to mass spectrometry, and single-molecule force spectroscopy, often in conjunction with simulation, have begun to reveal how conformational heterogeneity evolves during folding, and whether an intermediate ensemble of defined free energy consists of different sub-populations of molecules that may differ significantly in conformation, energy and entropy.

Mutations of evolutionarily conserved aromatic residues suggest that misfolding of the mouse prion protein may commence in multiple ways

The misfolding of the mammalian prion protein from its α-helix rich cellular isoform to its β-sheet rich infectious isoform is associated with several neurodegenerative diseases. The determination of the structural mechanism by which misfolding commences, still remains an unsolved problem. In the current study, native-state hydrogen exchange coupled with mass spectrometry has revealed that the N state of the mouse prion protein (moPrP) at pH 4 is in dynamic equilibrium with multiple partially unfolded forms (PUFs) capable of initiating misfolding. Mutation of three evolutionarily conserved aromatic residues, Tyr168, Phe174, and Tyr217 present at the interface of the β2-α2 loop and the C-terminal end of α3 in the structured C-terminal domain of moPrP significantly destabilize the native state (N) of the protein. They also reduce the free energy differences between the N state and two PUFs identified as PUF1 and PUF2**. It is shown that PUF2** in which the β2-α2 loop and the C-terminal end of α3 are disordered, has the same stability as the previously identified PUF2*, but to have a very different structure. Misfolding can commence from both PUF1 and PUF2**, as it can from PUF2*. Hence, misfolding can commence and proceed in multiple ways from structurally distinct precursor conformations. The increased extents to which PUF1 and PUF2** are populated at equilibrium in the case of the mutant variants, greatly accelerate their misfolding. The results suggest that the three aromatic residues may have been evolutionarily selected to impede the misfolding of moPrP.

Conformational landscapes of artificial peptides predicted by various force fields: are we ready to simulate β-amino acids?

With the introduction of artificial peptides as antimicrobial agents and organic catalysts, numerous efforts have been made to design foldamers with desirable structures and functions. Computational tools are a helpful proxy for revealing the dynamic structures at atomic resolution and understanding foldamer's complex structure-function relationships. However, the performance of conventional force fields in predicting the structures of artificial peptides has not been systematically evaluated. In this study, we critically assessed three popular force fields, AMBER ff14SB, CHARMM36m, and OPLS-AA/L, in predicting conformational propensities of a β-peptide foldamer at monomer and hexamer levels. Simulation results were compared to those obtained from quantum chemistry calculations and experimental data. We also utilised replica exchange molecular dynamics simulations to investigate the energy landscape of each force field and assess the similarities and differences between force fields. We compared different solvent systems in the AMBER ff14SB and CHARMM36m frameworks and confirmed the unanimous role of hydrogen bonds in shaping energy landscapes. We anticipate that our data will pave the way for further improvements to force fields and for understanding the role of solvents in peptide folding, crystallisation, and engineering.

Evolutionarily Conserved Proline Residues Impede the Misfolding of the Mouse Prion Protein by Destabilizing an Aggregation-competent Partially Unfolded Form

The misfolding of the prion protein has been linked to several neurodegenerative diseases. Despite extensive studies, the mechanism of the misfolding process remains poorly understood. The present study structurally delineates the role of the conserved proline residues present in the structured C-terminal domain of the mouse prion protein (moPrP) in the misfolding process. It is shown that mutation of these Pro residues to Ala leads to destabilization of the native (N) state, and also to rapid misfolding. Using hydrogen-deuterium exchange (HDX) studies coupled with mass spectrometry (MS), it has been shown that the N state of moPrP is in rapid equilibrium with a partially unfolded form (PUF2*) at pH 4. It has been shown that the Pro to Ala mutations make PUF2* energetically more accessible from the N state by stabilizing it relative to the unfolded (U) state. The apparent rate constant of misfolding is found to be linearly proportional to the extent to which PUF2* is populated in equilibrium with the N state, strongly indicating that misfolding commences from PUF2*. It has also been shown that the Pro residues restrict the boundary of the structural core of the misfolded oligomers. Overall, this study highlights how the conserved proline residues control misfolding of the prion protein by modulating the stability of the partially unfolded form from which misfolding commences.

Microscopic origin of diffusive dynamics in the context of transition path time distributions for protein folding and unfolding

Experimentally measured transition path time distributions are usually analyzed theoretically in terms of a diffusion equation over a free energy barrier. It is though well understood that the free energy profile separating the folded and unfolded states of a protein is characterized as a transition through many stable micro-states which exist between the folded and unfolded states. Why is it then justified to model the transition path dynamics in terms of a diffusion equation, namely the Smoluchowski equation (SE)? In principle, van Kampen has shown that a nearest neighbor Markov chain of thermal jumps between neighboring microstates will lead in a continuum limit to the SE, such that the friction coefficient is proportional to the mean residence time in each micro-state. However, the practical question of how many microstates are needed to justify modeling the transition path dynamics in terms of an SE has not been addressed. This is a central topic of this paper where we compare numerical results for transition paths based on the diffusion equation on the one hand and the nearest neighbor Markov jump model on the other. Comparison of the transition path time distributions shows that one needs at least a few dozen microstates to obtain reasonable agreement between the two approaches. Using the Markov nearest neighbor model one also obtains good agreement with the experimentally measured transition path time distributions for a DNA hairpin and PrP protein. As found previously when using the diffusion equation, the Markov chain model used here also reproduces the experimentally measured long time tail and confirms that the transition path barrier height is ∼3k_BT. This study indicates that in the future, when attempting to model experimentally measured transition path time distributions, one should perhaps prefer a nearest neighbor Markov model which is well defined also for rough energy landscapes. Such studies can also shed light on the minimal number of microstates needed to unravel the experimental data.

l-Arginine inhibits the activity of α-amylase: Rapid kinetics, interaction and functional implications

In this work, the rapid unfolding kinetics of pancreas α-amylase (PPA) induced by l-arginine and the interaction mechanism were investigated. The unfolding followed a first-level reaction kinetics equation, without intermediates. l-arginine interacted with PPA though diffusion-controlled process rather than complexion. The interaction between l-arginine and PPA resulted in a pronounced decrease in β-sheet and a significant increase in random coil, and thereby the enzyme activity decreased. However, the unfolding of PPA could be compensated and the second structure change could be recovered to some extent by the macromolecular crowded medium of Pluronics. Further insight into the mechanism disclosed that the broken H-bond network of water may contribute to PPA unfolding. This work provides a new perspective on the interaction of l-arginine with digestive enzyme. The unfolding mechanism of enzymes by may help to understand the effects of other structurally similar drugs, which is of concern in food-drug interactions.

Heterogeneity in Protein Folding and Unfolding Reactions

Proteins have dynamic structures that undergo chain motions on time scales spanning from picoseconds to seconds. Resolving the resultant conformational heterogeneity is essential for gaining accurate insight into fundamental mechanistic aspects of the protein folding reaction. The use of high-resolution structural probes, sensitive to population distributions, has begun to enable the resolution of site-specific conformational heterogeneity at different stages of the folding reaction. Different states populated during protein folding, including the unfolded state, collapsed intermediate states, and even the native state, are found to possess significant conformational heterogeneity. Heterogeneity in protein folding and unfolding reactions originates from the reduced cooperativity of various kinds of physicochemical interactions between various structural elements of a protein, and between a protein and solvent. Heterogeneity may arise because of functional or evolutionary constraints. Conformational substates within the unfolded state and the collapsed intermediates that exchange at rates slower than the subsequent folding steps give rise to heterogeneity on the protein folding pathways. Multiple folding pathways are likely to represent distinct sequences of structure formation. Insight into the nature of the energy barriers separating different conformational states populated during (un)folding can also be obtained by resolving heterogeneity.

The Perturbed Free-Energy Landscape: Linking Ligand Binding to Biomolecular Folding

The effects of ligand binding on biomolecular conformation are crucial in drug design, enzyme mechanisms, the regulation of gene expression, and other biological processes. Descriptive models such as "lock and key", "induced fit", and "conformation selection" are common ways to interpret such interactions. Another historical model, linked equilibria, proposes that the free-energy landscape (FEL) is perturbed by the addition of ligand binding energy for the bound population of biomolecules. This principle leads to a unified, quantitative theory of ligand-induced conformation change, building upon the FEL concept. We call the map of binding free energy over biomolecular conformational space the "binding affinity landscape" (BAL). The perturbed FEL predicts/explains ligand-induced conformational changes conforming to all common descriptive models. We review recent experimental and computational studies that exemplify the perturbed FEL, with emphasis on RNA. This way of understanding ligand-induced conformation dynamics motivates new experimental and theoretical approaches to ligand design, structural biology and systems biology.

Mapping Distinct Sequences of Structure Formation Differentiating Multiple Folding Pathways of a Small Protein

To determine experimentally how the multiple folding pathways of a protein differ, in the order in which the structural parts are assembled, has been a long-standing challenge. To resolve whether structure formation during folding can progress in multiple ways, the complex folding landscape of monellin has been characterized, structurally and temporally, using the multisite time-resolved FRET methodology. After an initial heterogeneous polypeptide chain collapse, structure formation proceeds on parallel pathways. Kinetic analysis of the population evolution data across various protein segments provides a clear structural distinction between the parallel pathways. The analysis leads to a phenomenological model that describes how and when discrete segments acquire structure independently of each other in different subensembles of protein molecules. When averaged over all molecules, structure formation is seen to progress as α-helix formation, followed by core consolidation, then β-sheet formation, and last end-to-end distance compaction. Parts of the protein that are closer in the primary sequence acquire structure before parts separated by longer sequence.

On the Conformational Dynamics of β-Amyloid Forming Peptides: A Computational Perspective

Understanding the conformational dynamics of proteins and peptides involved in important functions is still a difficult task in computational structural biology. Because such conformational transitions in β-amyloid (Aβ) forming peptides play a crucial role in many neurological disorders, researchers from different scientific fields have been trying to address issues related to the folding of Aβ forming peptides together. Many theoretical models have been proposed in the recent years for studying Aβ peptides using mathematical, physicochemical, and molecular dynamics simulation, and machine learning approaches. In this article, we have comprehensively reviewed the developmental advances in the theoretical models for Aβ peptide folding and interactions, particularly in the context of neurological disorders. Furthermore, we have extensively reviewed the advances in molecular dynamics simulation as a tool used for studying the conversions between polymorphic amyloid forms and applications of using machine learning approaches in predicting Aβ peptides and aggregation-prone regions in proteins. We have also provided details on the theoretical advances in the study of Aβ peptides, which would enhance our understanding of these peptides at the molecular level and eventually lead to the development of targeted therapies for certain acute neurological disorders such as Alzheimer's disease in the future.

Microsecond sub-domain motions and the folding and misfolding of the mouse prion protein

Protein aggregation appears to originate from partially unfolded conformations that are sampled through stochastic fluctuations of the native protein. It has been a challenge to characterize these fluctuations, under native like conditions. Here, the conformational dynamics of the full-length (23-231) mouse prion protein were studied under native conditions, using photoinduced electron transfer coupled to fluorescence correlation spectroscopy (PET-FCS). The slowest fluctuations could be associated with the folding of the unfolded state to an intermediate state, by the use of microsecond mixing experiments. The two faster fluctuations observed by PET-FCS, could be attributed to fluctuations within the native state ensemble. The addition of salt, which is known to initiate the aggregation of the protein, resulted in an enhancement in the time scale of fluctuations in the core of the protein. The results indicate the importance of native state dynamics in initiating the aggregation of proteins.