Heat capacity effects in protein folding and ligand binding: a re-evaluation of the role of water in biomolecular thermodynamics

Corsaro

Proc. Natl. Acad. Sci. U.S.A.

et al. 2016

102

We use 1 H NMR to probe the energy landscape in the protein folding and unfolding process. Using the scheme ⇄ reversible unfolded (intermediate) → irreversible unfolded (denatured) state, we study the thermal denaturation of hydrated lysozyme that occurs when the temperature is increased. Using thermal cycles in the range 295 < T < 365 K and following different trajectories along the protein energy surface, we observe that the hydrophilic (the amide NH) and hydrophobic (methyl CH 3 and methine CH) peptide groups evolve and exhibit different behaviors. We also discuss the role of water and hydrogen bonding in the protein configurational stability.protein folding | proton NMR | energy landscape | hydration water A n intriguing problem of statistical physics concerns the evolutionary pathways that molecular systems follow as they form mesoscale structures and exhibit new functional behaviors (1). An example of this problem is the self-organization of biosystems that evolve from basic molecules. This challenging subject is studied by using a variety of theoretical methods (2-4). The free-energy landscape model is nowadays the most used to describe such phenomena and especially the aging of the protein folding mechanism (1, 5, 6), i.e., the way in which proteins fold to their native state and then unfold (protein denaturation) (6, 7). The model is based on the idea that in complex materials and systems there are many thermodynamical configurations in which the free-energy surface exhibits a number of local minima separated by barriers, i.e., as the system explores its phase space the trajectory of its evolution is an alternating sequence of local energy minima and saddle points (transition states), which are associated with the positions of all of the system particles. A trajectory thus specifies the path of the system as it evolves by moving across its energy landscape.A peptide is a linear chain of amino acids, and globular proteins are polypeptide chains that fold into their native conformation. During the folding process a polypeptide undergoes many conformational changes and there is a significant decrease in the system configurational entropy as the native state is approached. To understand folding we focus on how proteins search conformational space. The process is accompanied by many microscopic reactions, the nature of which is determined by the specifics of the energy surface. Thus, the characteristics of the energy surface of a polypeptide chain are the key to a quantitative understanding of folding. Although the degrees of freedom of a polypeptide chain allow an enormously large number of possible configurations, "constraints" on the energy decrease these configurations visited in the folding reaction to a limited number (8). Understanding the free-energy surface ("landscape") enables us to understand the folding process. A balance between the potential energy and the configurational entropy leads to a freeenergy barrier that generates the two-state folding behavior usually observed in small proteins. The...

Section: Resultsmentioning

confidence: 96%

Section: Resultsmentioning

confidence: 99%

Energy landscape in protein folding and unfolding

Corsaro

Proc. Natl. Acad. Sci. U.S.A.

et al. 2016

102

Journal of Dairy Science

“…The thermodynamic signatures of β-and κ-casein self-association do not establish that the hydrophobic effect is the only, or even the predominant, driving force, as maintained by Horne in his so-called dual binding model (Horne, 2002(Horne, , 2008, because they could equally well arise from the formation of a network of H-bonds (Cooper, 2000(Cooper, , 2005. Indeed, it would be naïve to assume that main chain H-bonding was not also of importance in casein interactions and in many cases it may be the dominant form of interaction between P,Q-rich sequences.…”

Section: Summary Of Casein Pq-rich Sequence Interactionsmentioning

confidence: 96%

“…As defined by Kautzmann (1959), the hydrophobic interaction in proteins is a property only of the side chains of residues. More recent work on the nature of the free energy changes in protein folding has recognized the difficulty of separating the hydrophobic effect derived from the desolvation of side chains from the H-bonding interactions and desolvation of the main chain, particularly as the latter can display the same thermodynamic signatures as the hydrophobic effect (Cooper 2000(Cooper , 2005Djikaev and Ruckenstein, 2009). For example, molecular dynamics simulations showed that perturbation of the structure of the water shells around the main chain of a poly-Ala sequence, going from its stable PP-II conformation to a β-strand, was reminiscent of the hydrophobic effect (Mezei et al, 2004).…”

Section: Quaternary Structures and The Hydrophobic Effectmentioning

confidence: 99%

Invited review: Caseins and the casein micelle: Their biological functions, structures, and behavior in foods

Holt

Carver

Ecroyd

et al. 2013

385

240

A typical casein micelle contains thousands of casein molecules, most of which form thermodynamically stable complexes with nanoclusters of amorphous calcium phosphate. Like many other unfolded proteins, caseins have an actual or potential tendency to assemble into toxic amyloid fibrils, particularly at the high concentrations found in milk. Fibrils do not form in milk because an alternative aggregation pathway is followed that results in formation of the casein micelle. As a result of forming micelles, nutritious milk can be secreted and stored without causing either pathological calcification or amyloidosis of the mother's mammary tissue. The ability to sequester nanoclusters of amorphous calcium phosphate in a stable complex is not unique to caseins. It has been demonstrated using a number of noncasein secreted phosphoproteins and may be of general physiological importance in preventing calcification of other biofluids and soft tissues. Thus, competent noncasein phosphoproteins have similar patterns of phosphorylation and the same type of flexible, unfolded conformation as caseins. The ability to suppress amyloid fibril formation by forming an alternative amorphous aggregate is also not unique to caseins and underlies the action of molecular chaperones such as the small heat-shock proteins. The open structure of the protein matrix of casein micelles is fragile and easily perturbed by changes in its environment. Perturbations can cause the polypeptide chains to segregate into regions of greater and lesser density. As a result, the reliable determination of the native structure of casein micelles continues to be extremely challenging. The biological functions of caseins, such as their chaperone activity, are determined by their composition and flexible conformation and by how the casein polypeptide chains interact with each other. These same properties determine how caseins behave in the manufacture of many dairy products and how they can be used as functional ingredients in other foods. aBStraCtA typical casein micelle contains thousands of casein molecules, most of which form thermodynamically stable complexes with nanoclusters of amorphous calcium phosphate. Like many other unfolded proteins, caseins have an actual or potential tendency to assemble into toxic amyloid fibrils, particularly at the high concentrations found in milk. Fibrils do not form in milk because an alternative aggregation pathway is followed that results in formation of the casein micelle. As a result of forming micelles, nutritious milk can be secreted and stored without causing either pathological calcification or amyloidosis of the mother's mammary tissue. The ability to sequester nanoclusters of amorphous calcium phosphate in a stable complex is not unique to caseins. It has been demonstrated using a number of noncasein secreted phosphoproteins and may be of general physiological importance in preventing calcification of other biofluids and soft tissues. Thus, competent noncasein phosphoproteins have similar patterns of phosp...

“…One of the central assumptions of transition state theory is that ΔG ‡ , the activation barrier, is independent of temperature and for reactions involving small molecules in common solvents such as water, this is generally true. However, biological reactions are almost always mediated by macromolecules such as enzymes and these very large molecules are peculiar insofar as they have large heat capacities (C P ) (Cooper, 2005). Heat capacity (C P ) is an easily measured property of a system and is simply defined as the temperature dependence of the enthalpy (H) and entropy (S) for the system (and therefore, the Gibbs Free Energy, G, for the system).…”

Section: Theorymentioning

confidence: 99%

Thermodynamic theory explains the temperature optima of soil microbial processes and high Q₁₀ values at low temperatures

Schipper

Hobbs

Rutledge

et al. 2014

Global Change Biology

182

163

Our current understanding of the temperature response of biological processes in soil is based on the Arrhenius equation. This predicts an exponential increase in rate as temperature rises, whereas in the laboratory and in the field, there is always a clearly identifiable temperature optimum for all microbial processes. In the laboratory, this has been explained by denaturation of enzymes at higher temperatures, and in the field, the availability of substrates and water is often cited as critical factors. Recently, we have shown that temperature optima for enzymes and microbial growth occur in the absence of denaturation and that this is a consequence of the unusual heat capacity changes associated with enzymes. We have called this macromolecular rate theory -MMRT (Hobbs et al., 2013, ACS Chem. Biol. 8:2388). Here, we apply MMRT to a wide range of literature data on the response of soil microbial processes to temperature with a focus on respiration but also including different soil enzyme activities, nitrogen and methane cycling. Our theory agrees closely with a wide range of experimental data and predicts temperature optima for these microbial processes. MMRT also predicted high relative temperature sensitivity (as assessed by Q 10 calculations) at low temperatures and that Q 10 declined as temperature increases in agreement with data synthesis from the literature. Declining Q 10 and temperature optima in soils are coherently explained by MMRT which is based on thermodynamics and heat capacity changes for enzyme-catalysed rates. MMRT also provides a new perspective, and makes new predictions, regarding the absolute temperature sensitivity of ecosystems -a fundamental component of models for climate change.