Early Folding Biases in the Folding Free-Energy Surface of βα-Repeat Proteins: A Dissertation

Early events in folding can determine if a protein is going to fold, misfold, or aggregate. Understanding these deterministic events is paramount for de novo protein engineering, the enhancement of biopharmaceutical stabilities, and understanding neurodegenerative diseases including amyotrophic lateral sclerosis and Alzheimer\u27s disease. However, the physicochemical and structural biases within high energy states of protein biopolymers are poorly understood. A combined experimental and computational study was conducted on the small β/α-repeat protein CheY to determine the structural basis of its submillisecond misfolding reaction to an off-pathway intermediate. Using permutations, we were able to discriminate between the roles of two proposed mechanisms of folding; a nucleation condensation model, and a hydrophobic collapse model driven by the formation of clusters of isoleucine, leucine, and valine (ILV) residues. We found that by altering the ILV cluster connectivity we could bias the early folding events to either favor on or off-pathway intermediates. Structural biases were also experimentally observed in the unfolded state of a de novo designed synthetic β/α-repeat protein, Di-III_14. Although thermodynamically and kinetically 2-state, Di-III_14 has a well structured unfolded state that is only observable under native-favoring conditions. This unfolded state appears to retain native-like structure, consisting of a hydrophobic 7 core (69% ILV) stabilized by solvent exposed polar groups and long range electrostatic interactions. Together, these results suggest that early folding events are largely deterministic in these two systems. Generally, low contact order ILV clusters favor local compaction and, in specific cases, long range electrostatic interactions may have stabilizing effects in higher energy states

Disordered proteins and network disorder in network descriptions of protein structure, dynamics and function. Hypotheses and a comprehensive review

During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here we review the links between disordered proteins and the associated networks, and describe the consequences of local, mesoscopic and global network disorder on changes in protein structure and dynamics. We introduce a new classification of protein networks into ‘cumulus-type’, i.e., those similar to puffy (white) clouds, and ‘stratus-type’, i.e., those similar to flat, dense (dark) low-lying clouds, and relate these network types to protein disorder dynamics and to differences in energy transmission processes. In the first class, there is limited overlap between the modules, which implies higher rigidity of the individual units; there the conformational changes can be described by an ‘energy transfer’ mechanism. In the second class, the topology presents a compact structure with significant overlap between the modules; there the conformational changes can be described by ‘multi-trajectories’; that is, multiple highly populated pathways. We further propose that disordered protein regions evolved to help other protein segments reach ‘rarely visited’ but functionally-related states. We also show the role of disorder in ‘spatial games’ of amino acids; highlight the effects of intrinsically disordered proteins (IDPs) on cellular networks and list some possible studies linking protein disorder and protein structure networks

Frustration in Biomolecules

Biomolecules are the prime information processing elements of living matter. Most of these inanimate systems are polymers that compute their structures and dynamics using as input seemingly random character strings of their sequence, following which they coalesce and perform integrated cellular functions. In large computational systems with a finite interaction-codes, the appearance of conflicting goals is inevitable. Simple conflicting forces can lead to quite complex structures and behaviors, leading to the concept of "frustration" in condensed matter. We present here some basic ideas about frustration in biomolecules and how the frustration concept leads to a better appreciation of many aspects of the architecture of biomolecules, and how structure connects to function. These ideas are simultaneously both seductively simple and perilously subtle to grasp completely. The energy landscape theory of protein folding provides a framework for quantifying frustration in large systems and has been implemented at many levels of description. We first review the notion of frustration from the areas of abstract logic and its uses in simple condensed matter systems. We discuss then how the frustration concept applies specifically to heteropolymers, testing folding landscape theory in computer simulations of protein models and in experimentally accessible systems. Studying the aspects of frustration averaged over many proteins provides ways to infer energy functions useful for reliable structure prediction. We discuss how frustration affects folding, how a large part of the biological functions of proteins are related to subtle local frustration effects and how frustration influences the appearance of metastable states, the nature of binding processes, catalysis and allosteric transitions. We hope to illustrate how Frustration is a fundamental concept in relating function to structural biology.Comment: 97 pages, 30 figure

Environment matters : the impact of urea and macromolecular crowding on proteins

[eng] This work aims to analytically understand the impact of two diametric opposite environments on protein structure and dynamics and compared them to the most common solvent on earth: water. The first environment is a popular denaturing solution (urea 8M), which has served for years in protein-science laboratories to investigate protein stability; still many open questions regarding its mechanism of action remained unclear. The second environment instead moves towards a more physiological representation of proteins. The cell interior, in fact, is a crowded solution highly populated prevalently by proteins, but studies on protein structure and dynamics have lead so far to confusing or even opposite observations. The lack of a consensus view in both phenomena possibly derives from the bias of the system under study. This work is an attempt of a comparative study using the most general systems: a diverse spectrum of proteins folds, different stages along the reaction path (early stages or end-point) and/or different protein force-fields. Our main objective was to derive common pattern and general rules valid at proteome level, focusing on three major aspects of proteins: the structure, the dynamic and the interactions with the solvent molecules. Molecular dynamics simulation appeared then as the most suitable tool because of its ability to i) analyze proteins at broad range of resolutions; ii) access the direct time-resolved dynamic of the system and iii) dissect the specific interactions that arise in the new settings. Specifically, the case of urea-induced unfolding needs a system for which is possible to clearly identify folded and unfolded state – globular proteins are then the most suitable ones. We extracted general rules on the folded/unfolded transition by studying independently the two end-points of folded/unfolded reaction. We simulated the urea-induced unfolded state of a model protein, ubiquitin to understand the energetics stabilizing unfolded structures in urea. We found that the unfolded ubiquitin in 8M urea is fully extend and flexible and capturing efficiently urea molecules to the first solvation shell. Dispersion, rather than electrostatic, appear the main energetic contribution to explain the stabilization of the unfolded state. We then simulated the early stages of urea-induced unfolding on a large dataset of folded proteins, which represent the major folds of globular proteins, aiming also to investigate the kinetic role of urea in triggering the protein unfolding. We found that partially unfolded proteins expose the apolar residues buried in the protein interior, mainly via cavitation. Similar to the unfolded state, it is the dispersion interactions that drive urea accumulation in the solvation shell but here urea molecules take advantage of microscopic unfolding events to penetrate the protein interior. Macromolecular crowding instead is a phenomenon that universally affects all the proteins. We simulated a system that included as crowding agents proteins with different conformational landscapes (a globular protein, an intrinsically disordered proteins and a molten globule) arranged to reach cell-like concentrations. We conclude that the universal effect of crowding, valid for all the proteins types, is exerted via the aspecific interactions and favors open and moderately extended conformations with higher secondary structure content. This phenomenon counterbalances the volume-exclusion, which prevails at higher crowding concentrations. The impact of crowding is proportional to the degree of disorder of the protein and for folded protein crowding favors structural rearrangements while unfolded structures experience a stronger stabilization and a higher secondary structures content. The synthetic crowder PEG doesn’t reproduce any of these effects, arising concerns about its employment in study cell-like environments

All-scale structural analysis of biomolecules through dynamical graph partitioning

From femtosecond bond vibrations to millisecond domain motions, the dynamics of biomolecules spans a wide range of time and length scales. This hierarchy of overlapping scales links the molecular and biophysical details to key aspects of their functionality. However, the span of scales combined with their intricate coupling rapidly drives atomic simulation methods to their limits, thereby often resulting in the need for coarse-graining techniques which cannot take full account of the biochemical details. To overcome this tradeoff, a graph-theoretical framework inspired by multiscale community detection methods and stochastic processes is here introduced for the analysis of protein and DNA structures. Using biophysical force fields, we propose a general mapping of the 3D atomic coordinates onto an energy-weighted network that includes the physico-chemical details of interatomic bonds and interactions.Making use of a dynamics-based approach for community detection on networks, optimal partitionings of the structure are identified which are biochemically relevant over different scales. The structural organisation of the biomolecule is shown to be recovered bottom-up over the entire range of chemical, biochemical and biologically meaningful scales, directly from the atomic information of the structure, and without any reparameterisation. This methodology is applied and discussed in five proteins and an ensemble of DNA quadruplexes. In each case, multiple conformations associated with different states of the biomolecule or stages of the underlying catalytic reaction are analysed. Experimental observations are shown to be correctly captured, including the functional domains, regions of the protein with coherent dynamics such as rigid clusters, and the spontaneous closure of some enzymes in the absence of substrate. A computational mutational analysis tool is also derived which identifies both known and new residues with a significant impact on ligand binding. In large multimeric structures, the methodology highlights patterns of long range communication taking place between subunits. In the highly dynamic and polymorphic DNA quadruplexes, key structural features for their physical stability and signatures of their unfolding pathway are identified in the static structure.Open Acces

Folding and Assembly of Multimeric Proteins: Dimeric HIV-1 Protease and a Trimeric Coiled Coil Component of a Complex Hemoglobin Scaffold: A Dissertation

Knowledge of how a polypeptide folds from a space-filling random coil into a biologically-functional, three-dimensional structure has been the essence of the protein folding problem. Though mechanistic details of DNA transcription and RNA translation are well understood, a specific code by which the primary structure dictates the acquisition of secondary, tertiary, and quarternary structure remains unknown. However, the demonstrated reversibility of in vitroprotein folding allows for a thermodynamic analysis of the folding reaction. By probing both the equilibrium and kinetics of protein folding, a protein folding mechanism can be postulated. Over the past 40 years, folding mechanisms have been determined for many proteins; however, a generalized folding code is far from clear. Furthermore, most protein folding studies have focused on monomeric proteins even though a majority of biological processes function via the association of multiple subunits. Consequently, a complete understanding of the acquisition of quarternary protein structure is essential for applying the basic principles of protein folding to biology. The studies presented in this dissertation examined the folding and assembly of two very different multimeric proteins. Underlying both of these investigations is the need for a combined analysis of a repertoire of approaches to dissect the folding mechanism for multimeric proteins. Chapter II elucidates the detailed folding energy landscape of HIV-1 protease, a dimeric protein containing β-barrel subunits. The folding of this viral enzyme exhibited a sequential three-step pathway, involving the rate-limiting formation of a monomeric intermediate. The energetics determined from this analysis and their applications to HIV-1 function are discussed. In contrast, Chapter III illustrates the association of a coiled coil component of L. terrestriserythrocruorin. This extracellular hemoglobin consists of a complex scaffold of linker chains with a central ring of interdigitating coiled coils. Allostery is maintained by twelve dodecameric hemoglobin subunits that dock upon this scaffold. Modest association was observed for this coiled coil, and the implications of this fragment to linker assembly are addressed. These studies depict the complexity of multimeric folding reactions. Chapter II demonstrates that a detailed energy landscape of a dimeric protein can be determined by combining traditional equilibrium and kinetic approaches with information from a global analysis of kinetics and a monomer construct. Chapter III indicates that fragmentation of large complexes can show the contributions of separate domains to hierarchical organization. As a whole, this dissertation highlights the importance of pursuing mulitmeric protein folding studies and the implications of these folding mechanisms to biological function

Network analysis of protein dynamics

The network paradigm is increasingly used to describe the topology and dynamics of complex systems. Here we review the results of the topological analysis of protein structures as molecular networks describing their small-world character, and the role of hubs and central network elements in governing enzyme activity, allosteric regulation, protein motor function, signal transduction and protein stability. We summarize available data how central network elements are enriched in active centers and ligand binding sites directing the dynamics of the entire protein. We assess the feasibility of conformational and energy networks to simplify the vast complexity of rugged energy landscapes and to predict protein folding and dynamics. Finally, we suggest that modular analysis, novel centrality measures, hierarchical representation of networks and the analysis of network dynamics will soon lead to an expansion of this field.Comment: 10 pages, 2 figures, 1 tabl