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Protein folds and folding
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Sequence Determines Degree of Knottedness in a Coarse-Grained Protein Model

Sequence Determines Degree of Knottedness in a Coarse-Grained Protein Model | Protein folds and folding | Scoop.it
The sequence of amino acids in certain biomolecules could be a factor in ensuring that they remain free of knots.

 

ABSTRACT 

Knots are abundant in globular homopolymers but rare in globular proteins. To shed new light on this long-standing conundrum, we study the influence of sequence on the formation of knots in proteins under native conditions within the framework of the hydrophobic-polar lattice protein model. By employing large-scale Wang-Landau simulations combined with suitable Monte Carlo trial moves we show that even though knots are still abundant on average, sequence introduces large variability in the degree of self-entanglements. Moreover, we are able to design sequences which are either almost always or almost never knotted. Our findings serve as proof of concept that the introduction of just one additional degree of freedom per monomer (in our case sequence) facilitates evolution towards a protein universe in which knots are rare.

Bernard Offmann's insight:

Well, there is something that is missing in this model... 

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Reduced alphabet for protein folding prediction

Abstract

What are the key building blocks that would have been needed to construct complex protein folds? This is an important issue for understanding protein folding mechanism and guiding de novo protein design. Twenty naturally occurring amino acids and eight secondary structures consist of a 28-letter alphabet to determine folding kinetics and mechanism. Here we predict folding kinetic rates of proteins from many reduced alphabets. We find that a reduced alphabet of 10 letters achieves good correlation with folding rates, close to the one achieved by full 28-letter alphabet. Many other reduced alphabets are not significantly correlated to folding rates. The finding suggests that not all amino acids and secondary structures are equally important for protein folding. The foldable sequence of a protein could be designed using at least ten folding units, which can either promote or inhibit protein folding. Reducing alphabet cardinality without losing key folding kinetic information opens the door to potentially faster machine learning and data mining applications in protein structure prediction, sequence alignment and protein design. 

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Native fold and docking pose discrimination by the same residue-based scoring function

Abstract

Structure prediction and quality assessment are crucial steps in modeling native protein conformations. Statistical potentials are widely used in related algorithms, with different parametrizations typically developed for different contexts such as folding protein monomers or docking protein complexes. Here, we describe BACH-SixthSense, a single residue-based statistical potential that can be successfully employed in both contexts.

BACH-SixthSense shares the same approach as BACH, a knowledge-based potential originally developed to score monomeric protein structures. A term which penalizes steric clashes as well as the distinction between polar and apolar sidechain-sidechain contacts are crucial novel features of BACH-SixthSense. The performance of BACH-SixthSense in discriminating correctly the native structure among a competing set of decoys is significantly higher than other state-of-the-art scoring functions, that were specifically trained for a single context, for both monomeric proteins (QMEAN, Rosetta, RF_CB_SRS_OD, benchmarked on CASP targets) and protein dimers (IRAD, Rosetta, PIE*PISA, HADDOCK, FireDock, benchmarked on 14 CAPRI targets). The performance of BACH-SixthSense in recognizing near-native docking poses within CAPRI decoy sets is good as well. 

 

By Edoardo Sarti, Daniele Granata, Flavio Seno, Antonio Trovato and Alessandro Laio

Bernard Offmann's insight:

The authors claim to have a scoring function (Bach-6thSense) better than the Rosetta score to identify native folds.

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Folding pathway of a multidomain protein depends on its topology of domain connectivity

Abstract

How do the folding mechanisms of multidomain proteins depend on protein topology? We addressed this question by developing an Ising-like structure-based model and applying it for the analysis of free-energy landscapes and folding kinetics of an example protein, Escherichia coli dihydrofolate reductase (DHFR). DHFR has two domains, one comprising discontinuous N- and C-terminal parts and the other comprising a continuous middle part of the chain. The simulated folding pathway of DHFR is a sequential process during which the continuous domain folds first, followed by the discontinuous domain, thereby avoiding the rapid decrease in conformation entropy caused by the association of the N- and C-terminal parts during the early phase of folding. Our simulated results consistently explain the observed experimental data on folding kinetics and predict an off-pathway structural fluctuation at equilibrium. For a circular permutant for which the topological complexity of wild-type DHFR is resolved, the balance between energy and entropy is modulated, resulting in the coexistence of the two folding pathways. This coexistence of pathways should account for the experimentally observed complex folding behavior of the circular permutant.

 

 

Bernard Offmann's insight:

Interesting work by Nasaki Sasai & colleagues from Nagoya University, Japan.

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Understanding shape entropy through local dense packing

Significance

Many natural systems are structured by the ordering of repeated, distinct shapes. Understanding how this happens is difficult because shape affects structure in two ways. One is how the shape of a cell or nanoparticle, for example, affects its surface, chemical, or other intrinsic properties. The other is an emergent, entropic effect that arises from the geometry of the shape itself, which we term “shape entropy,” and is not well understood. In this paper, we determine how shape entropy affects structure. We quantify the mechanism and determine when shape entropy competes with intrinsic shape effects. Our results show that in a wide class of systems, shape affects bulk structure because crowded particles optimize their local packing.

 

Abstract

Entropy drives the phase behavior of colloids ranging from dense suspensions of hard spheres or rods to dilute suspensions of hard spheres and depletants. Entropic ordering of anisotropic shapes into complex crystals, liquid crystals, and even quasicrystals was demonstrated recently in computer simulations and experiments. The ordering of shapes appears to arise from the emergence of directional entropic forces (DEFs) that align neighboring particles, but these forces have been neither rigorously defined nor quantified in generic systems. Here, we show quantitatively that shape drives the phase behavior of systems of anisotropic particles upon crowding through DEFs. We define DEFs in generic systems and compute them for several hard particle systems. We show they are on the order of a few times the thermal energy (kBT) at the onset of ordering, placing DEFs on par with traditional depletion, van der Waals, and other intrinsic interactions. In experimental systems with these other interactions, we provide direct quantitative evidence that entropic effects of shape also contribute to self-assembly. We use DEFs to draw a distinction between self-assembly and packing behavior. We show that the mechanism that generates directional entropic forces is the maximization of entropy by optimizing local particle packing. We show that this mechanism occurs in a wide class of systems and we treat, in a unified way, the entropy-driven phase behavior of arbitrary shapes, incorporating the well-known works of Kirkwood, Onsager, and Asakura and Oosawa.

Bernard Offmann's insight:

I think this very inspiring work from Sharon Glotzer @profglotz can be extended to the #proteinfolding problem.

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Cartoon Physics - Protein Folding

Cartoon Physics - Protein Folding | Protein folds and folding | Scoop.it
RT @StangJared: I learned something about protein folding, @cartoon_physics: http://t.co/cVc9EwE0Dy Thank you!
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Use of a structural alphabet to find compatible folds for amino acid sequences

Use of a structural alphabet to find compatible folds for amino acid sequences | Protein folds and folding | Scoop.it

Swapnil Mahajan, Alexandre de Brevern, Yves-Henri Sanejouand, Srinivasan Narayanaswamy and Bernard Offmann

 

Accepted in Protein Science

 

Abstract

 

The structural annotation of proteins with no detectable homologues of known 3D structure identified using sequence-search methods is a major challenge today. We propose an original method that computes the conditional probabilities for the amino-acid sequence of a protein to fit to known protein 3D structures using a structural alphabet, known as “Protein Blocks” (PBs). PBs constitute a library of 16 local structural prototypes that approximate every part of protein backbone structures. It is used to encode 3D protein structures into 1D PB sequences and to capture sequence to structure relationships. Our method relies on amino acid occurrence matrices, one for each PB, to score global and local threading of query amino acid sequences to protein folds encoded into PB sequences. It does not use any information from residue contacts or sequence-search methods or explicit incorporation of hydrophobic effect. The performance of the method was assessed with independent test datasets derived from SCOP 1.75A. With a Z-score cutoff that achieved 95% specificity (i.e less than 5% false positives), global and local threading showed sensitivity of 64.1% and 34.2% respectively. We further tested its performance on 57 difficult CASP10 targets that had no known homologues in PDB: 38 compatible templates were identified by our approach and 66% of these hits yielded correctly predicted structures. This method scales-up well and offers promising perspectives for structural annotations at genomic level. It has been implemented in the form of a web-server that is freely available at http://www.bo-protscience.fr/forsa.

Bernard Offmann's insight:

Our new fold recognition method is based on the principle of threading amino acid sequences onto protein structures encoded using a structural alphabet. It uses simple conditional probabilities to find compatible folds for protein sequences.

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Global view of the protein universe

Global view of the protein universe | Protein folds and folding | Scoop.it

Sergey Nepomnyachiy, Nir Ben-Tal, and Rachel Kolodny

 

Abstract

To explore protein space from a global perspective, we consider 9,710 SCOP (Structural Classification of Proteins) domains with up to 70% sequence identity and present all similarities among them as networks: In the “domain network,” nodes represent domains, and edges connect domains that share “motifs,” i.e., significantly sized segments of similar sequence and structure. We explore the dependence of the network on the thresholds that define the evolutionary relatedness of the domains. At excessively strict thresholds the network falls apart completely; for very lax thresholds, there are network paths between virtually all domains. Interestingly, at intermediate thresholds the network constitutes two regions that can be described as “continuous” versus “discrete.” The continuous region comprises a large connected component, dominated by domains with alternating alpha and beta elements, and the discrete region includes the rest of the domains in isolated islands, each generally corresponding to a fold. We also construct the “motif network,” in which nodes represent recurring motifs, and edges connect motifs that appear in the same domain. This network also features a large and highly connected component of motifs that originate from domains with alternating alpha/beta elements (and some all-alpha domains), and smaller isolated islands. Indeed, the motif network suggests that nature reuses such motifs extensively. The networks suggest evolutionary paths between domains and give hints about protein evolution and the underlying biophysics. They provide natural means of organizing protein space, and could be useful for the development of strategies for protein search and design.

 

Significance

To globally explore protein space, we use networks to present similarities among a representative set of all known domains. In the “domain network” edges connect domains that share “motifs,” i.e., significantly sized segments of similar sequence and structure, and in the “motif network” edges connect recurring motifs that appear in the same domain. The networks offer a way to organize protein space, and examine how the organization changes upon changing the definition of “evolutionary relatedness” among domains. For example, we use them to highlight and characterize the uniqueness of a class of domains called alpha/beta, in which the alpha and beta elements alternate. The networks can also suggest evolutionary paths between domains, and be used for protein search and design.

 

Bernard Offmann's insight:

Mapping of the protein fold space, revisited by Rachel Kolodny in PNAS.

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Synthesis and folding of a mirror-image enzyme reveals ambidextrous chaperone activity

Matthew T. Weinstock, Michael T. Jacobsen, and Michael S. Kay

 

Abstract

 

Mirror-image proteins (composed of D-amino acids) are promising therapeutic agents and drug discovery tools, but as synthesis of larger D-proteins becomes feasible, a major anticipated challenge is the folding of these proteins into their active conformations. In vivo, many large and/or complex proteins require chaperones like GroEL/ES to prevent misfolding and produce functional protein. The ability of chaperones to fold D-proteins is unknown. Here we examine the ability of GroEL/ES to fold a synthetic D-protein. We report the total chemical synthesis of a 312-residue GroEL/ES-dependent protein, DapA, in both L- and D-chiralities, the longest fully synthetic proteins yet reported. Impressively, GroEL/ES folds both L- and D-DapA. This work extends the limits of chemical protein synthesis, reveals ambidextrous GroEL/ES folding activity, and provides a valuable tool to fold D-proteins for drug development and mirror-image synthetic biology applications.

 

Significance

 

This paper addresses a fundamental question: Can natural chaperones fold mirror-image proteins? Mirror-image proteins (composed of D-amino acids) are only accessible by chemical synthesis, but are protease resistant and therefore have tremendous potential as long-lived drugs. Many large/complex proteins depend on chaperones for efficient folding. Here we describe the total chemical synthesis of a 312-residue chaperone-dependent protein (DapA) in natural (L-) and mirror-image (D-) forms, the longest fully synthetic proteins yet reported. Using these proteins we show that the natural bacterial GroEL/ES chaperone is “ambidextrous”—i.e., it can fold both natural and mirror-image proteins via nonspecific hydrophobic interactions. Our study also provides proof-of-concept for the use of natural GroEL/ES to fold D-proteins for mirror-image drug discovery and synthetic biology applications.

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Predictive energy landscapes for folding α-helical transmembrane proteins

Authors : Bobby L. Kim, Nicholas P. Schafer, and Peter G. Wolynes

Abstract

We explore the hypothesis that the folding landscapes of membrane proteins are funneled once the proteins’ topology within the membrane is established. We extend a protein folding model, the associative memory, water-mediated, structure, and energy model (AWSEM) by adding an implicit membrane potential and reoptimizing the force field to account for the differing nature of the interactions that stabilize proteins within lipid membranes, yielding a model that we call AWSEM-membrane. Once the protein topology is set in the membrane, hydrophobic attractions play a lesser role in finding the native structure, whereas polar–polar attractions are more important than for globular proteins. We examine both the quality of predictions made with AWSEM-membrane when accurate knowledge of the topology and secondary structure is available and the quality of predictions made without such knowledge, instead using bioinformatically inferred topology and secondary structure based on sequence alone. When no major errors are made by the bioinformatic methods used to assign the topology of the transmembrane helices, these two types of structure predictions yield roughly equivalent quality structures. Although the predictive energy landscape is transferable and not structure based, within the correct topological sector we find the landscape is indeed very funneled: Thermodynamic landscape analysis indicates that both the total potential energy and the contact energy decrease as native contacts are formed. Nevertheless the near symmetry of different helical packings with respect to native contact formation can result in multiple packings with nearly equal thermodynamic occupancy, especially at temperatures just below collapse.

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Understanding the Influence of Codon Translation Rates on Cotranslational Protein Folding

Understanding the Influence of Codon Translation Rates on Cotranslational Protein Folding | Protein folds and folding | Scoop.it

Authors: O'Brien EP, Ciryam P, Vendruscolo M, Dobson CM

 

Conspectus

 

Protein domains can fold into stable tertiary structures while they are synthesized by the ribosome in a process known as cotranslational folding. If a protein does not fold cotranslationally, however, it has the opportunity to do so post-translationally, that is, after the nascent chain has been fully synthesized and released from the ribosome. The rate at which a ribosome adds an amino acid encoded by a particular codon to the elongating nascent chain can vary significantly and is called the codon translation rate. Recent experiments have illustrated the profound impact that codon translation rates can have on the cotranslational folding process and the acquisition of function by nascent proteins. Synonymous codon mutations in an mRNA molecule change the chemical identity of a codon and its translation rate without changing the sequence of the synthesized protein. This change in codon translation rate can, however, cause a nascent protein to malfunction as a result of cotranslational misfolding. In some situations, such dysfunction can have profound implications; for example, it can alter the substrate specificity of an ABC transporter protein, resulting in patients who are nonresponsive to chemotherapy treatment. Thus, codon translation rates are crucial in coordinating protein folding in a cellular environment and can affect downstream cellular processes that depend on the proper functioning of newly synthesized proteins. As the importance of codon translation rates makes clear, a necessary aspect of fully understanding cotranslational folding lies in considering the kinetics of the process in addition to its thermodynamics.

 

In this Account, we examine the contributions that have been made to elucidating the mechanisms of cotranslational folding by using the theoretical and computational tools of chemical kinetics, molecular simulations, and systems biology. These efforts have extended our ability to understand, model, and predict the influence of codon translation rates on cotranslational protein folding and misfolding. The application of such approaches to this important problem is creating a framework for making quantitative predictions of the impact of synonymous codon substitutions on cotranslational folding that has led to a novel hypothesis regarding the role of fast-translating codons in coordinating cotranslational folding. In addition, it is providing new insights into proteome-wide cotranslational folding behavior and making it possible to identify potential molecular mechanisms by which molecular chaperones can influence such behavior during protein synthesis. As we discuss in this Account, bringing together these theoretical developments with experimental approaches is increasingly helping answer fundamental questions about the nature of nascent protein folding on the ribosome.

Bernard Offmann's insight:

Everything is said in these two phrases : 

« Synonymous codon mutations in an mRNA molecule change the chemical identity of a codon and its translation rate without changing the sequence of the synthesized protein. This change in codon translation rate can, however, cause a nascent protein to malfunction as a result of cotranslational misfolding. »

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Protein Folding Thermodynamics: A New Computational Approach

Protein Folding Thermodynamics: A New Computational Approach | Protein folds and folding | Scoop.it
Abstract

Folding free energy is the fundamental thermodynamic quantity characterizing the stability of a protein. Yet, its accurate determination based on computational techniques remains a challenge in physical chemistry. A straightforward brute-force approach would be to conduct molecular dynamics simulations and to estimate the folding free energy from the equilibrium population ratio of the unfolded and folded states. However, this approach is not sensible at physiological conditions where the equilibrium population ratio is vanishingly small: it is extremely difficult to reliably obtain such a small equilibrium population ratio due to the low rate of folding/unfolding transitions. It is therefore desirable to have a computational method that solely relies on simulations independently carried out for the folded and unfolded states. Here, we present such an approach that focuses on the probability distributions of the effective energy (solvent-averaged protein potential energy) in the folded and unfolded states. We construct these probability distributions for the protein villin headpiece subdomain by performing extensive molecular dynamics simulations and carrying out solvation free energy calculations. We find that the probability distributions of the effective energy are well-described by the Gaussian distributions for both the folded and unfolded states due to the central limit theorem, which enables us to calculate the protein folding free energy in terms of the mean and the width of the distributions. The computed protein folding free energy (-2.5 kcal/mol) is in accord with the experimental result (ranging from -2.3 to -3.2 kcal/mol depending on the experimental methods).

  
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Tracing Primordial Protein Evolution through Structurally Guided Stepwise Segment Elongation

Authors: Watanabe H, Yamasaki K, Honda S

 

Abstract

 

The understanding of how primordial proteins emerged has been a fundamental and longstanding issue in biology and biochemistry. For a better understanding of primordial protein evolution, we synthesized an artificial protein on the basis of an evolutionary hypothesis, segment-based elongation starting from an autonomously foldable short peptide. A 10-residue protein, chignolin, the smallest foldable polypeptide ever reported, was used as a structural support to facilitate higher structural organization and gain-of-function in the development of an artificial protein. Repetitive cycles of segment elongation and subsequent phage display selection successfully produced a 25-residue protein, termed AF.2A1, with nanomolar affinity against the Fc region of immunoglobulin G. AF.2A1 shows exquisite molecular recognition ability such that it can distinguish conformational differences of the same molecule. The structure determined by NMR measurements demonstrated that AF.2A1 forms a globular protein-like conformation with the chignolin-derived β-hairpin and a tryptophan-mediated hydrophobic core. Using sequence analysis and a mutation study, we discovered that the structural organization and gain-of-function emerged from the vicinity of the chignolin segment, revealing that the structural support served as the core in both structural and functional development. Here, we propose an evolutionary model for primordial proteins in which a foldable segment serves as the evolving core to facilitate structural and functional evolution. This study provides insights into primordial protein evolution and also presents a novel methodology for designing small sized proteins useful for industrial and pharmaceutical applications.

 

J Biol Chem. 2014 Feb 7;289(6):3394-404

 
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Biophysics of protein evolution and evolutionary protein biophysics

Tobias Sikosek, Hue Sun ChanAbstract

The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence–structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by ‘hidden’ conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution.

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Long paper and interesting review. 

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Genome-scale identification and characterization of moonlighting proteins

Background

Moonlighting proteins perform two or more cellular functions, which are selected based on various contexts including the cell type they are expressed, their oligomerization status, and the binding of different ligands at different sites. To understand overall landscape of their functional diversity, it is important to establish methods that can identify moonlighting proteins in a systematic fashion. Here, we have developed a computational framework to find moonlighting proteins on a genome scale and identified multiple proteomic characteristics of these proteins.

Results

First, we analyzed Gene Ontology (GO) annotations of known moonlighting proteins. We found that the GO annotations of moonlighting proteins can be clustered into multiple groups reflecting their diverse functions. Then, by considering the observed GO term separations, we identified 33 novel moonlighting proteins in Escherichia coli and confirmed them by literature review. Next, we analyzed moonlighting proteins in terms of protein-protein interaction, gene expression, phylogenetic profile, and genetic interaction networks. We found that moonlighting proteins physically interact with a higher number of distinct functional classes of proteins than non-moonlighting ones and also found that most of the physically interacting partners of moonlighting proteins share the latter’s primary functions. Interestingly, we also found that moonlighting proteins tend to interact with other moonlighting proteins. In terms of gene expression and phylogenetically related proteins, a weak trend was observed that moonlighting proteins interact with more functionally diverse proteins. Structural characteristics of moonlighting proteins, i.e. intrinsic disordered regions and ligand binding sites were also investigated.

Conclusion

Additional functions of moonlighting proteins are difficult to identify by experiments and these proteins also pose a significant challenge for computational function annotation. Our method enables identification of novel moonlighting proteins from current functional annotations in public databases. Moreover, we showed that potential moonlighting proteins without sufficient functional annotations can be identified by analyzing available omics-scale data. Our findings open up new possibilities for investigating the multi-functional nature of proteins at the systems level and for exploring the complex functional interplay of proteins in a cell.

Reviewers

This article was reviewed by Michael Galperin, Eugine Koonin, and Nick Grishin.

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A simple theoretical model goes a long way in explaining complex behavior in protein folding

Extract of commentary from Victor Munoz in PNAS :

 

Understanding how natural proteins fold spontaneously onto their specific, biologically functional 3D structures is both a fascinating fundamental problem in modern biochemistry and a necessary step toward developing technologies for protein engineering and designing protein-based nanodevices...The work of Inanami et al. in PNAS (1) provides a remarkable example of how powerful these simple theoretical models can be in explaining the complexities and nuances of protein folding reactions.

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The nature of protein folding pathways

Abstract

How do proteins fold, and why do they fold in that way? This Perspective integrates earlier and more recent advances over the 50-y history of theprotein folding problem, emphasizing unambiguously clear structural information. Experimental results show that, contrary to prior belief, proteins are multistate rather than two-state objects. They are composed of separately cooperative foldon building blocks that can be seen to repeatedly unfold and refold as units even under native conditions. Similarly, foldons are lost as units when proteins are destabilized to produce partially unfolded equilibrium molten globules. In kinetic folding, the inherently cooperative nature of foldons predisposes the thermally driven amino acid-level search to form an initial foldon and subsequent foldons in later assisted searches. The small size of foldon units, ∼20 residues, resolves the Levinthal time-scale search problem. These microscopic-level search processes can be identified with the disordered multitrack search envisioned in the "new view" model for protein folding. Emergent macroscopic foldon-foldon interactions then collectively provide the structural guidance and free energy bias for the ordered addition of foldons in a stepwise pathway that sequentially builds the native protein. These conclusions reconcile the seemingly opposed new view and defined pathway models; the two models account for different stages of the protein folding process. Additionally, these observations answer the "how" and the "why" questions. The protein folding pathway depends on the same foldon units and foldon-foldon interactions that construct the native structure.

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Protein folding problem revisited by Englander & Mayne.

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Loss of conformational entropy in protein folding calculated using realistic ensembles and its implications for NMR-based calculations

Michael C. Baxa, Esmael J. Haddadian, John M. Jumper, Karl F. Freed, and Tobin R. Sosnick

 

Significance

 

Despite 40 years of study, no consensus has been achieved on the magnitude of the loss of backbone (BB) and side-chain (SC) entropies upon folding, even though these quantities are essential for characterizing the energetics of folding and conformational change. We calculate the loss using experimentally validated denatured and native state ensembles, avoiding the drastic assumptions used in many past analyses. By also accounting for correlated motions, we find that the loss of BB entropy is three- to fourfold larger than the SC contribution. Our values differ with some calculations by up to a factor of 3 and depend strongly on 2° structure. These results have implications upon other thermodynamic properties, the estimation of entropy using NMR methods, and coarse-grained simulations.

 

Abstract

 

The loss of conformational entropy is a major contribution in the thermodynamics of protein folding. However, accurate determination of the quantity has proven challenging. We calculate this loss using molecular dynamic simulations of both the native protein and a realistic denatured state ensemble. For ubiquitin, the total change in entropy is TΔSTotal = 1.4 kcal⋅mol−1 per residue at 300 K with only 20% from the loss of side-chain entropy. Our analysis exhibits mixed agreement with prior studies because of the use of more accurate ensembles and contributions from correlated motions. Buried side chains lose only a factor of 1.4 in the number of conformations available per rotamer upon folding (ΩU/ΩN). The entropy loss for helical and sheet residues differs due to the smaller motions of helical residues (TΔShelix−sheet = 0.5 kcal⋅mol−1), a property not fully reflected in the amide N-H and carbonyl C=O bond NMR order parameters. The results have implications for the thermodynamics of folding and binding, including estimates of solvent ordering and microscopic entropies obtained from NMR.

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Use of a structural alphabet to find compatible folds for amino acid sequences

Use of a structural alphabet to find compatible folds for amino acid sequences | Protein folds and folding | Scoop.it

Swapnil Mahajan, Alexandre de Brevern, Yves-Henri Sanejouand, Srinivasan Narayanaswamy and Bernard Offmann

 

Accepted in Protein Science

 

Abstract

 

The structural annotation of proteins with no detectable homologues of known 3D structure identified using sequence-search methods is a major challenge today. We propose an original method that computes the conditional probabilities for the amino-acid sequence of a protein to fit to known protein 3D structures using a structural alphabet, known as “Protein Blocks” (PBs). PBs constitute a library of 16 local structural prototypes that approximate every part of protein backbone structures. It is used to encode 3D protein structures into 1D PB sequences and to capture sequence to structure relationships. Our method relies on amino acid occurrence matrices, one for each PB, to score global and local threading of query amino acid sequences to protein folds encoded into PB sequences. It does not use any information from residue contacts or sequence-search methods or explicit incorporation of hydrophobic effect. The performance of the method was assessed with independent test datasets derived from SCOP 1.75A. With a Z-score cutoff that achieved 95% specificity (i.e less than 5% false positives), global and local threading showed sensitivity of 64.1% and 34.2% respectively. We further tested its performance on 57 difficult CASP10 targets that had no known homologues in PDB: 38 compatible templates were identified by our approach and 66% of these hits yielded correctly predicted structures. This method scales-up well and offers promising perspectives for structural annotations at genomic level. It has been implemented in the form of a web-server that is freely available at http://www.bo-protscience.fr/forsa.

Bernard Offmann's insight:

Our new, fast and quite efficient method for protein fold recognition was published in Protein Science. It is now online.

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From eons to seconds, proteins exploit the same forces

From eons to seconds, proteins exploit the same forces | Protein folds and folding | Scoop.it
(Phys.org) —Nature's artistic and engineering skills are evident in proteins, life's robust molecular machines. Scientists at Rice University have now employed their unique theories to show how the interplay between evolution and physics developed these skills.

Via Arjen ten Have
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Arjen ten Have's curator insight, August 14, 2014 3:29 PM

How proteins evolve depends on many aspects but according to this the energy landscape is extremely important. Nice combination of physics and evolution, at the heart of where biocomputation should be!

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Spin-dependent electron transport in protein-like single-helical molecules

Ai-Min Guo and Qing-Feng Sun

 

Significance

The control of electron spin transport in molecular systems has been receiving lots of attention among different scientific communities because of possible applications in spintronics and understanding of the spin effects in biological systems. Recent experiments have demonstrated that α-helical protein acts as an efficient spin filter and the chiral-induced spin selectivity may be a general phenomenon. However, no spin selectivity was measured in single-stranded DNA above the experimental noise. In the present study, we propose a physical model to rationalize the above phenomena, and provide an unambiguous physical mechanism for spin-selective phenomenon observed in α-helical protein and for the contradictory behaviors between protein and single-stranded DNA. These results may facilitate engineering of chiral-based spintronic devices.

 

Abstract

We report on a theoretical study of spin-dependent electron transport through single-helical molecules connected by two nonmagnetic electrodes, and explain the experiment of significant spin-selective phenomenon observed in α-helical protein and the contradictory results between the protein and single-stranded DNA. Our results reveal that the α-helical protein is an efficient spin filter and the spin polarization is robust against the disorder. These results are in excellent agreement with recent experiments [Mishra D, et al. (2013) Proc Natl Acad Sci USA 110(37):14872–14876; Göhler B, et al. (2011) Science 331(6019):894–897] and may facilitate engineering of chiral-based spintronic devices.

 
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General Mechanism of Two-State Protein Folding Kinetics - Journal of the American Chemical Society (ACS Publications)

Geoffrey C. Rollins and Ken A. DillJournal of the American Chemical Society 2014 136 (32), 11420-11427

 

 

We describe here a general model of the kinetic mechanism of protein folding. In the Foldon Funnel Model, proteins fold in units of secondary structures, which form sequentially along the folding pathway, stabilized by tertiary interactions. The model predicts that the free energy landscape has a volcano shape, rather than a simple funnel, that folding is two-state (single-exponential) when secondary structures are intrinsically unstable, and that each structure along the folding path is a transition state for the previous structure. It shows how sequential pathways are consistent with multiple stochastic routes on funnel landscapes, and it gives good agreement with the 9 order of magnitude dependence of folding rates on protein size for a set of 93 proteins, at the same time it is consistent with the near independence of folding equilibrium constant on size. This model gives estimates of folding rates of proteomes, leading to a median folding time in Escherichia coli of about 5 s.

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Codon-by-Codon Modulation of Translational Speed and Accuracy Via mRNA Folding

Codon-by-Codon Modulation of Translational Speed and Accuracy Via mRNA Folding | Protein folds and folding | Scoop.it

Authors : Jian-Rong Yang, Xiaoshu Chen, Jianzhi Zhang


Protein synthesis by ribosomal translation is a vital cellular process, but our understanding of its regulation has been poor. Because the number of ribosomes in the cell is limited, rapid growth relies on fast translational elongation. The accuracy of translation must also be maintained, and in an ideal scenario, both speed and accuracy should be maximized to sustain rapid and productive growth. However, existing data suggest a tradeoff between speed and accuracy, making it impossible to simultaneously maximize both. A potential solution is slowing the elongation at functionally or structurally important sites to ensure their translational accuracies, while sacrificing accuracy for speed at other sites. Here, we show that budding yeast and mouse embryonic stem cells indeed use this strategy. We discover that a codon-by-codon adaptive modulation of translational elongation is accomplished by mRNA secondary structures, which serve as brakes to control the elongation speed and hence translational fidelity. Our findings explain why highly expressed genes tend to have strong mRNA folding, slow translational elongation, and conserved protein sequences. The exquisite translational modulation reflects the power of natural selection in mitigating efficiency–accuracy conflicts, and our study offers a general framework for analyzing similar conflicts, which are widespread in biology.

Bernard Offmann's insight:

Simply brillant analysis, fully computational but yet such important insights in protein synthesis #compbio #bioinformatics #plosbiology

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Fast protein folding kinetics

Fast protein folding kinetics | Protein folds and folding | Scoop.it
Fast-folding proteins have been a major focus of computational and experimental study because they are accessible to both techniques: they are small and fast enough to be reasonably simulated with current computational power, but have dynamics slow enough to be observed with specially developed experimental techniques. This coupled study of fast-folding proteins has provided insight into the mechanisms, which allow some proteins to find their native conformation well <1 ms and has uncovered examples of theoretically predicted phenomena such as downhill folding. The study of fast folders also informs our understanding of even folding processes: fast folders are small; relatively simple protein domains and the principles that govern their folding also govern the folding of more complex systems. This review summarizes the major theoretical and experimental techniques used to study fast-folding proteins and provides an overview of the major findings of fast-folding research. Finally, we examine the themes that have emerged from studying fast folders and briefly summarize their application to protein folding in general, as well as some work that is left to do.
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How the folding rates of two- and multi-state proteins depend on the amino acid properties - Huang - Proteins: Structure, Function, and Bioinformatics - Wiley Online Library

Jitao T. Huang, Wei Huang, Shanran R. Huang and Xin Li Abstract Proteins fold by either two-state or multi-state kinetic mechanism. We observe that amino acids play different roles in different mechanism. Many residues that are easy to form regular secondary structures (α helices, β sheets and turns) can promote the two-state folding reactions of small proteins. Most of hydrophilic residues can speed up the multi-state folding reactions of large proteins. Folding rates of large proteins are equally responsive to the flexibility of partial amino acids. Other properties of amino acids (including volume, polarity, accessible surface, exposure degree, isoelectric point, and phase transfer energy) have contributed little to folding kinetics of the proteins. Cysteine is a special residue, it triggers two-state folding reaction and but inhibits multi-state folding reaction. These findings not only provide a new insight into protein structure prediction, but also could be used to direct the point mutations that can change folding rate.
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