Configurational entropy of native proteins

Karplus, Martin; Ichiye, Toshiko; Pettitt, Bernard

doi:10.1016/s0006-3495(87)83303-9

Cited by 200 publications

(230 citation statements)

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“…Accordingly, in discussions of protein stability and related issues, it is commonly assumed that the residual entropy of proteins is negligible. Nevertheless, over the past two decades there has been an accumulation of experimental (vide infra) and computational evidence (e.g., Karplus et al, 1987) that suggests quite a different view-that proteins are quite dynamic on time scales relevant to the question of residual entropy (for a recent review, see Doig and Sternberg, 1995). The magnitude of the residual entropy of proteins is of critical importance to an understanding of protein structure, stability, and ultimately function.…”

mentioning

confidence: 99%

Insights into the local residual entropy of proteins provided by NMR relaxation

Li¹,

Raychaudhuri²,

Wand³

1996

Protein Science

234

267

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A simple model is used to illustrate the relationship between the dynamics measured by NMR relaxation methods and the local residual entropy of proteins. The expected local dynamic behavior of well-packed extended amino acid side chains are described by employing a one-dimensional vibrator that encapsulates both the spatial and temporal character of the motion. This model is then related to entropy and to the generalized order parameter of the popular "model-free" treatment often used in the analysis of NMR relaxation data. Simulations indicate that order parameters observed for the methyl symmetry axes in, for example, human ubiquitin correspond to significant local entropies. These observations have obvious significance for the issue of the physical basis of protein structure, dynamics, and stability.Keywords: protein dynamics; protein stability; protein entropy; NMR relaxationThe physical basis of protein structure, dynamics, and stability has been a subject of intense study and debate for several decades. While the taxonomy of protein structure appears to be well understood, a similar depth of understanding of the existence and character of the dynamics of proteins remains to be developed (for a review, see Frauenfelder et al., 1991). These issues are fundamental to a complete understanding of the origins, temporal behavior, and marginal stability of protein structure. For example, empirical evidence indicates that entropic effects dominate the free energy changes that accompany folding of a solvated "random coil" polypeptide usually to a dominant structure of lower free energy. The observed net increase in system entropy upon folding has been attributed to the dominance of a large increase in solvent entropy upon side-chain dehydration over a putatively smaller decrease in side-chain entropy upon packing in the folded globular state. have extremely high packing densities, which in turn, suggests that proteins are rigid with residual motion being extremely restricted and local. Accordingly, in discussions of protein stability and related issues, it is commonly assumed that the residual entropy of proteins is negligible. Nevertheless, over the past two decades there has been an accumulation of experimental (vide infra) and computational evidence (e.g., Karplus et al., 1987) that suggests quite a different view-that proteins are quite dynamic on time scales relevant to the question of residual entropy (for a recent review, see Doig and Sternberg, 1995). The magnitude of the residual entropy of proteins is of critical importance to an understanding of protein structure, stability, and ultimately function. In principle, nuclear magnetic resonance spectroscopy can be employed to estimate the local dynamics throughout a protein. Though comprehensive studies of the backbone dynamics of proteins based on analysis of I5N relaxation have appeared, it is only recently that general techniques have emerged to probe the fast dynamics of amino acid side chains. Earlier approaches employing 13C relaxation in selec...

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mentioning

confidence: 99%

Insights into the local residual entropy of proteins provided by NMR relaxation

Li¹,

Raychaudhuri²,

Wand³

1996

Protein Science

234

267

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“…[47] It is also been known for a long time that the entropy of the native state can be approximated by contributions from the small number of native conformations in relation to the vast amount of unfolded conformations. [48] This means that the native state must be located at a very deep minimum in the energy hypersurface and thus there is a significant energy gap between a native structure and an average non-native structure.…”

Section: Methodsmentioning

confidence: 99%

Assessment of semiempirical enthalpy of formation in solution as an effective energy function to discriminate native‐like structures in protein decoy sets

2016

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In this work, we tested the PM6, PM6-DH1, PM6-D3, and PM7 enthalpies of formation in aqueous solution as scoring functions across 33 decoy sets to discriminate native structures or good models in a decoy set. In each set these semiempirical quantum chemistry methods were compared according to enthalpic and geometric criteria. Enthalpically, we compared the methods according to how much lower was the enthalpy of each native, when compared with the mean enthalpy of its set. Geometrically, we compared the methods according to the fraction of native contacts (Q), which is a measure of geometric closeness between an arbitrary structure and the native. For each set and method, the Q of the best decoy was compared with the Q 0 , which is the Q of the decoy closest to the native in the set. It was shown that the PM7 method is able to assign larger energy differences between the native structure and the decoys in a set, arguably because of a better description of dispersion interactions, however PM6-DH1 was slightly better than the rest at selecting geometrically good models in the absence of a native structure in the set.

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“…The entropic scoring in FoldX [124,27] only takes into account the change in conformational entropy, which depends on the number of accessible conformers in the unfolded state and their probabilities [124]. Although this entropic variation dominates folding [125], large discrepancies in vibrational entropy (the intrinsic entropy of a given protein conformer [124] have been calculated between thermophilic and mesophilic proteins [126].…”

Section: Protein Stability Improvementmentioning

confidence: 99%

“…Although this entropic variation dominates folding [125], large discrepancies in vibrational entropy (the intrinsic entropy of a given protein conformer [124] have been calculated between thermophilic and mesophilic proteins [126]. Therefore, the thoughtful inclusion of a vibrational entropy contribution in protein design free energy functions might pay-off.…”

Section: Protein Stability Improvementmentioning

confidence: 99%

Molecular Modeling in Enzyme Design, Toward In Silico Guided Directed Evolution

Monza

Acebes

Lucas

et al. 2017

Directed Enzyme Evolution: Advances and Applications

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Directed evolution creates diversity in subsequent rounds of mutagenesis in the quest of increased protein stability, substrate binding and catalysis. Although this technique does not require any structural/mechanistic knowledge of the system, the frequency of improved mutations is usually low. For this reason, computational tools are increasingly used to focus the search in sequence space, enhancing the efficiency of laboratory evolution. In particular, molecular modeling methods provide a unique tool to grasp the sequence/structure/function relationship The final publication is available at Springer via https://link.springer.com/chapter/10.1007/978-3-319-50413-1_10/fulltext.html of the protein to evolve, with the only condition that a structural model is provided. With this book chapter, we tried to guide the reader through the state of art of molecular modeling, discussing their strengths, limitations and directions. In addition, we suggest a possible future template for in silico directed evolution where we underline two main points: a hierarchical computational protocol combining several different techniques, and a synergic effort between simulations and experimental validation. IntroductionBiotechnology needs catalysts that can work under harsh conditions, catalyze a broad range of substrates, generate maximum amount of product, and tolerate changes in the environment. Enzymes, which are biodegradable and reusable catalysts [1], in addition to remarkable reaction rates, can work in environmentally friendly pH and temperature ranges, and display control over stereochemistry and regioselectivity which makes them ideal for many applications [2,3]. When thinking about enzymes, people normally associate them to expressions such as "perfect catalysts" or "outstanding reaction rate". In fact, there are examples of enzymes that catalyze reactions at extremely high rates such as triose phosphate isomerase, superoxide dismutase or carbonic anhydrase [4]. These are often limited only by the rate of ligand diffusion into the active site (diffusion-controlled rate). Nevertheless, an extensive analysis by Bar-Even et al., of nearly 2000 enzymes, showed that the median maximal turnover rate value over all measured enzymes is about 10 s −1 nowhere close to the values of 10 5 or 10 6 normally associated with catalysts [5,6].So, it would appear that natural enzymes are "just good enough" for the function they must perform in a given organism [7]. One might conclude that if they had evolved to their optimum performance then trying to improve them (from a kinetic point of view) would be attempting the impossible. On the contrary, as seen by the distribution of reaction rates, k cat , most enzymes function at a lower rate than the diffusion-limit and thus, there is space to further increase their kinetic properties to meet industrial needs. Additionally, we need enzymes capable of catalyzing reactions for which no known enzymes exist, to work with different substrates and for particular conditions that are industrially...

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Configurational entropy of native proteins

Abstract: Simulations of the residual configurational entropy of a protein in the native state suggest that it is nearly an order of magnitude larger than the entropy of denaturation. The implications of this result are discussed.

Cited by 200 publications

References 17 publications

Insights into the local residual entropy of proteins provided by NMR relaxation

Insights into the local residual entropy of proteins provided by NMR relaxation

Assessment of semiempirical enthalpy of formation in solution as an effective energy function to discriminate native‐like structures in protein decoy sets

Molecular Modeling in Enzyme Design, Toward In Silico Guided Directed Evolution

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