Comparing the energy landscapes for native folding and aggregation of PrP

Protein sequences are evolved to encode generally one folded structure, out of a nearly infinite array of possible folds. Underlying this code is a funneled free energy landscape that guides folding to the native conformation. Protein misfolding and aggregation are also a manifestation of free-energy landscapes. The detailed mechanisms of these processes are poorly understood, but often involve rare, transient species and a variety of different pathways. The inherent complexity of misfolding has hampered efforts to measure aggregation pathways and the underlying energy landscape, especially using traditional methods where ensemble averaging obscures important rare and transient events. We recently studied the misfolding and aggregation of prion protein by examining 2 monomers tethered in close proximity as a dimer, showing how the steps leading to the formation of a stable aggregated state can be resolved in the single-molecule limit and the underlying energy landscape thereby reconstructed. This approach allows a more quantitative comparison of native folding versus misfolding, including fundamental differences in the dynamics for misfolding. By identifying key steps and interactions leading to misfolding, it should help to identify potential drug targets. Here we describe the importance of characterizing free-energy landscapes for aggregation and the challenges involved in doing so, and we discuss how single-molecule studies can help test proposed structural models for PrP aggregates.     

Using motion planning to map protein folding landscapes and analyze folding kinetics of known native structures.

We investigate a novel approach for studying the kinetics of protein folding. Our framework has evolved from robotics motion planning techniques called probabilistic roadmap methods (PRMs) that have been applied in many diverse fields with great success. In our previous work, we presented our PRM-based technique and obtained encouraging results studying protein folding pathways for several small proteins. In this paper, we describe how our motion planning framework can be used to study protein folding kinetics. In particular, we present a refined version of our PRM-based framework and describe how it can be used to produce potential energy landscapes, free energy landscapes, and many folding pathways all from a single roadmap which is computed in a few hours on a desktop PC. Results are presented for 14 proteins. Our ability to produce large sets of unrelated folding pathways may potentially provide crucial insight into some aspects of folding kinetics, such as proteins that exhibit both two-state and three-state kinetics that are not captured by other theoretical techniques.     

Effects of macromolecular crowding agents on protein folding in vitro and in silico

Proteins fold and function inside cells which are environments very different from that of dilute buffer solutions most often used in traditional experiments. The crowded milieu results in excluded-volume effects, increased bulk viscosity and amplified chances for inter-molecular interactions. These environmental factors have not been accounted for in most mechanistic studies of protein folding executed during the last decades. The question thus arises as to how these effects—present when polypeptides normally fold in vivo—modulate protein biophysics. To address excluded volume effects, we use synthetic macromolecular crowding agents, which take up significant volume but do not interact with proteins, in combination with strategically selected proteins and a range of equilibrium and time-resolved biophysical (spectroscopic and computational) methods. In this review, we describe key observations on macromolecular crowding effects on protein stability, folding and structure drawn from combined in vitro and in silico studies. As expected based on Minton’s early predictions, many proteins (apoflavodoxin, VlsE, cytochrome c, and S16) became more thermodynamically stable (magnitude depends inversely on protein stability in buffer) and, unexpectedly, for apoflavodoxin and VlsE, the folded states changed both secondary structure content and, for VlsE, overall shape in the presence of macromolecular crowding. For apoflavodoxin and cytochrome c, which have complex kinetic folding mechanisms, excluded volume effects made the folding energy landscapes smoother (i.e., less misfolding and/or kinetic heterogeneity) than in buffer.     

Energy Landscapes of Protein Aggregation and Conformation Switching in Intrinsically Disordered Proteins

The protein folding problem was apparently solved recently by the advent of a deep learning method for protein structure prediction called AlphaFold. However, this program is not able to make predictions about the protein folding pathways. Moreover, it only treats about half of the human proteome, as the remaining proteins are intrinsically disordered or contain disordered regions. By definition these proteins differ from natively folded proteins and do not adopt a properly folded structure in solution. However these intrinsically disordered proteins (IDPs) also systematically differ in amino acid composition and uniquely often become folded upon binding to an interaction partner. These factors preclude solving IDP structures by current machine-learning methods like AlphaFold, which also cannot solve the protein aggregation problem, since this meta-folding process can give rise to different aggregate sizes and structures. An alternative computational method is provided by molecular dynamics simulations that already successfully explored the energy landscapes of IDP conformational switching and protein aggregation in multiple cases. These energy landscapes are very different from those of ‘simple’ protein folding, where one energy funnel leads to a unique protein structure. Instead, the energy landscapes of IDP conformational switching and protein aggregation feature a number of minima for different competing low-energy structures. In this review, I discuss the characteristics of these multifunneled energy landscapes in detail, illustrated by molecular dynamics simulations that elucidated the underlying conformational transitions and aggregation processes.     

The Proteome Folding Problem and Cellular Proteostasis

Stunning advances have been achieved in addressing the protein folding problem, providing deeper understanding of the mechanisms by which proteins navigate energy landscapes to reach their native states and enabling powerful algorithms to connect sequence to structure. However, the realities of the in vivo protein folding problem remain a challenge to reckon with. Here, we discuss the concept of the “proteome folding problem”—the problem of how organisms build and maintain a functional proteome—by admitting that folding energy landscapes are characterized by many misfolded states and that cells must deploy a network of chaperones and degradation enzymes to minimize deleterious impacts of these off-pathway species. The resulting proteostasis network is an inextricable part of in vivo protein folding and must be understood in detail if we are to solve the proteome folding problem. We discuss how the development of computational models for the proteostasis network’s actions and the relationship to the biophysical properties of the proteome has begun to offer new insights and capabilities.     

Prediction of the aggregation propensity of proteins from the primary sequence: aggregation properties of proteomes

In the cell, protein folding into stable globular conformations is in competition with aggregation into non-functional and usually toxic structures, since the biophysical properties that promote folding also tend to favor intermolecular contacts, leading to the formation of β-sheet-enriched insoluble assemblies. The formation of protein deposits is linked to at least 20 different human disorders, ranging from dementia to diabetes. Furthermore, protein deposition inside cells represents a major obstacle for the biotechnological production of polypeptides. Importantly, the aggregation behavior of polypeptides appears to be strongly influenced by the intrinsic properties encoded in their sequences and specifically by the presence of selective short regions with high aggregation propensity. This allows computational methods to be used to analyze the aggregation properties of proteins without the previous requirement for structural information. Applications range from the identification of individual amyloidogenic regions in disease-linked polypeptides to the analysis of the aggregation properties of complete proteomes. Herein, we review these theoretical approaches and illustrate how they have become important and useful tools in understanding the molecular mechanisms underlying protein aggregation.     

Simple physical models connect theory and experiment in protein folding kinetics

Our understanding of the principles underlying the protein-folding problem can be tested by developing and characterizing simple models that make predictions which can be compared to experimental data. Here we extend our earlier model of folding free energy landscapes, in which each residue is considered to be either folded as in the native state or completely disordered, by investigating the role of additional factors representing hydrogen bonding and backbone torsion strain, and by using a hybrid between the master equation approach and the simple transition state theory to evaluate kinetics near the free energy barrier in greater detail. Model calculations of folding phi-values are compared to experimental data for 19 proteins, and for more than half of these, experimental data are reproduced with correlation coefficients between r=0.41 and 0.88; calculations of transition state free energy barriers correlate with rates measured for 37 single domain proteins (r=0.69). The model provides insight into the contribution of alternative-folding pathways, the validity of quasi-equilibrium treatments of the folding landscape, and the magnitude of the Arrhenius prefactor for protein folding. Finally, we discuss the limitations of simple native-state-based models, and as a more general test of such models, provide predictions of folding rates and mechanisms for a comprehensive set of over 400 small protein domains of known structure.     

Matching theory and experiment in protein folding.

There has been considerable progress made over the past year in linking experimental and theoretical approaches to protein folding. Recent results from several independent lines of investigation suggest that protein folding mechanisms and landscapes are largely determined by the topology of the native state and are relatively insensitive to details of the interatomic interactions. This dependence on low-resolution structural features, rather than high-resolution detail, suggests that it should be possible to describe the fundamental physics of the folding process using relatively low-resolution models. Recent experiments have set benchmarks for testing new models and progress has been made in developing theoretical models for interpreting and predicting experimental results.     

High pressure, an alternative approach to understand protein misfolding diseases.

Protein folding is essential for the flow of genetic information to biological activity. A failure in this process can result in disease, by causing cell damage and sometimes death. The misfolding of proteins often induces their aggregation, initiating the fibril formation seen in a range of human and animal diseases. Because misfolding and aggregation are of fundamental importance in vivo, there is currently great interest in understanding their mechanisms. To gain insight into the folding and unfolding processes of proteins, for nearly a century, an original biophysical approach has been successfully used: the application of high hydrostatic pressure combined with various spectroscopic and kinetic techniques. Because high pressure provides new insight into protein structure and folding which cannot be obtained by other techniques, the conformations of pressure-induced unfolding intermediates and species involved in the initial states of aggregation of proteins associated with specific diseases are currently being investigated. Our contention is that by exploring folding kinetics, misfolding pathways and stability under pressure, it will be possible to understand the mechanisms of amyloidogenesis, with the ultimate goal to design therapeutic strategies to prevent progression of the disease.     

Untangling the complexity of membrane protein folding

Delineating the folding steps of helical-bundle membrane proteins has been a challenging task. Many questions remain unanswered, including the conformation and stability of the states populated during folding, the shape of the energy barriers between the states, and the role of lipids as a solvent in mediating the folding. Recently, theoretical frames have matured to a point that permits detailed dissection of the folding steps, and advances in experimental techniques at both single-molecule and ensemble levels enable selective modulation of specific steps for quantitative determination of the folding energy landscapes. We also discuss how lipid molecules would play an active role in shaping the folding energy landscape of membrane proteins, and how folding of multi-domain membrane proteins can be understood based on our current knowledge. We conclude this review by offering an outlook for emerging questions in the study of membrane protein folding.     

Protein folding in the post-genomic era

Protein folding is a topic of fundamental interest since it concerns the mechanisms by which the genetic message is translated into the three-dimensional and functional structure of proteins. In these post-genomic times, the knowledge of the fundamental principles are required in the exploitation of the information contained in the increasing number of sequenced genomes. Protein folding also has practical applications in the understanding of different pathologies and the development of novel therapeutics to prevent diseases associated with protein misfolding and aggregation. Significant advances have been made ranging from the Anfinsen postulate to the "new view" which describes the folding process in terms of an energy landscape. These new insights arise from both theoretical and experimental studies. The problem of folding in the cellular environment is briefly discussed. The modern view of misfolding and aggregation processes that are involved in several pathologies such as prion and Alzheimer diseases. Several approaches of structure prediction, which is a very active field of research, are described.     

Repeat-protein folding: new insights into origins of cooperativity, stability, and topology

Although our understanding of globular protein folding continues to advance, the irregular tertiary structures and high cooperativity of globular proteins complicates energetic dissection. Recently, proteins with regular, repetitive tertiary structures have been identified that sidestep limitations imposed by globular protein architecture. Here we review recent studies of repeat-protein folding. These studies uniquely advance our understanding of both the energetics and kinetics of protein folding. Equilibrium studies provide detailed maps of local stabilities, access to energy landscapes, insights into cooperativity, determination of nearest-neighbor interaction parameters using statistical thermodynamics, relationships between consensus sequences and repeat-protein stability. Kinetic studies provide insight into the influence of short-range topology on folding rates, the degree to which folding proceeds by parallel (versus localized) pathways, and the factors that select among multiple potential pathways. The recent application of force spectroscopy to repeat-protein unfolding is providing a unique route to test and extend many of these findings.     

Single-Molecule Force Spectroscopy of Protein Folding

The use of force probes to induce unfolding and refolding of single molecules through the application of mechanical tension, known as single-molecule force spectroscopy (SMFS), has proven to be a powerful tool for studying the dynamics of protein folding. Here we provide an overview of what has been learned about protein folding using SMFS, from small, single-domain proteins to large, multi-domain proteins. We highlight the ability of SMFS to measure the energy landscapes underlying folding, to map complex pathways for native and non-native folding, to probe the mechanisms of chaperones that assist with native folding, to elucidate the effects of the ribosome on co-translational folding, and to monitor the folding of membrane proteins.     

Aggregated proteins accelerate but do not increase the aggregation of D-glyceraldehyde-3-phosphate dehydrogenase. Specificity of protein aggregation

The effect of protein aggregates on the aggregation of d-glyceraldehyde-3-phosphate dehydrogenase (GAPDH) during unfolding and refolding has been studied. The aggregation of GAPDH follows a sigmoid course. The presence of protein aggregates increases the aggregation rate during unfolding and refolding of GAPDH but does not change the extent of aggregation and the final renaturation yield. It is suggested that protein aggregates function as seeds for aggregation via hydrophobic interaction with only GAPDH folding intermediates destined to aggregate and do not affect the distribution between pathways leading to correct folding and aggregation. Moreover, two different proteins do not interfere with each other during their simultaneous refolding together in a buffer. These findings provide insight into a mechanism by which cells prevent protein folding against the interference from aggregation of other proteins.     

Water and molecular chaperones act as weak links of protein folding networks: energy landscape and punctuated equilibrium changes point towards a game theory of proteins

Water molecules and molecular chaperones efficiently help the protein folding process. Here we describe their action in the context of the energy and topological networks of proteins. In energy terms water and chaperones were suggested to decrease the activation energy between various local energy minima smoothing the energy landscape, rescuing misfolded proteins from conformational traps and stabilizing their native structure. In kinetic terms water and chaperones may make the punctuated equilibrium of conformational changes less punctuated and help protein relaxation. Finally, water and chaperones may help the convergence of multiple energy landscapes during protein-macromolecule interactions. We also discuss the possibility of the introduction of protein games to narrow the multitude of the energy landscapes when a protein binds to another macromolecule. Both water and chaperones provide a diffuse set of rapidly fluctuating weak links (low affinity and low probability interactions), which allow the generalization of all these statements to a multitude of networks.     

Protein folding: then and now

Over the past three decades the protein folding field has undergone monumental changes. Originally a purely academic question, how a protein folds has now become vital in understanding diseases and our abilities to rationally manipulate cellular life by engineering protein folding pathways. We review and contrast past and recent developments in the protein folding field. Specifically, we discuss the progress in our understanding of protein folding thermodynamics and kinetics, the properties of evasive intermediates, and unfolded states. We also discuss how some abnormalities in protein folding lead to protein aggregation and human diseases.     

Direct visualization and profiling of protein misfolding and aggregation in live cells

Over the past few years, research tools have been developed to monitor the multistep protein aggregation process in live cells, a process that has been associated with a growing number of human diseases. Herein, we describe recent advances in methods that can either survey the distribution of aggregation at the level of the cellular proteome using mass spectroscopy or discern the multistep aggregation process of specific proteins of interest via fluorescence signals. Future development and application of such technologies are expected to provide insights on mechanisms, diagnosis, and treatment of diseases rooted in protein aggregation.     

Making the invisible visible: Toward structural characterization of allosteric states,interaction networks,and allosteric regulatory mechanisms in protein kinases

Despite the established view of protein kinases as dynamic and versatile allosteric regulatory machines, our knowledge of allosteric functional states, allosteric interaction networks, and the intrinsic folding energy landscapes is surprisingly limited. We discuss the latest developments in structural characterization of allosteric molecular events underlying protein kinase dynamics and functions using structural, biophysical, and computational biology approaches. The recent studies highlighted progress in making the invisible aspects of protein kinase ‘life’ visible, including the determination of hidden allosteric states and mapping of allosteric energy landscapes, discovery of new mechanisms underlying ligand-induced modulation of allosteric activity, evolutionary adaptation of kinase allostery, and characterization of allosteric interaction networks as the intrinsic driver of kinase adaptability and signal transmission in the regulatory assemblies.