Protein folds and folding
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Protein folds and folding
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A computational method for designing diverse linear epitopes including citrullinated peptides with desired binding affinities to intravenous immunoglobulin


Rob Patro, Raquel Norel, Robert J. Prill, Julio Saez-Rodriguez, Peter Lorenz, Felix Steinbeck, Bjoern Ziems, Mitja Luštrek, Nicola Barbarini, Alessandra Tiengo, Riccardo Bellazzi, Hans-Jürgen Thiesen, Gustavo Stolovitzky and Carl Kingsford


BMC BioinformaticsBMC series – open, inclusive and trusted201617:155
DOI: 10.1186/s12859-016-1008-7©  Patro et al. 2016

Received: 23 April 2015

Accepted: 31 March 2016

Published: 8 April 2016

Abstract

Background
Understanding the interactions between antibodies and the linear epitopes that they recognize is an important task in the study of immunological diseases. We present a novel computational method for the design of linear epitopes of specified binding affinity to Intravenous Immunoglobulin (IVIg).

Results
We show that the method, called Pythia-design can accurately design peptides with both high-binding affinity and low binding affinity to IVIg. To show this, we experimentally constructed and tested the computationally constructed designs. We further show experimentally that these designed peptides are more accurate that those produced by a recent method for the same task. Pythia-design is based on combining random walks with an ensemble of probabilistic support vector machines (SVM) classifiers, and we show that it produces a diverse set of designed peptides, an important property to develop robust sets of candidates for construction. We show that by combining Pythia-design and the method of (PloS ONE 6(8):23616, 2011), we are able to produce an even more accurate collection of designed peptides. Analysis of the experimental validation of Pythia-design peptides indicates that binding of IVIg is favored by epitopes that contain trypthophan and cysteine.

Conclusions
Our method, Pythia-design, is able to generate a diverse set of binding and non-binding peptides, and its designs have been experimentally shown to be accurate.

Keywords

Protein binding Machine learning Antibodies Protein design



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Protein elongation, co-translational folding and targeting

J Mol Biol. 2016 Mar 30. pii: S0022-2836(16)30001-8. doi: 10.1016/j.jmb.2016.03.022. [Epub ahead of print]

Rodnina MV, Wintermeyer W.

Abstract 

The elongation phase of protein synthesis defines the overall speed and fidelity of protein synthesis and affects protein folding and targeting. The mechanisms of reactions taking place during translation elongation remain important questions in understanding ribosome function. The ribosome - guided by signals in the mRNA - can recode the genetic information, resulting in alternative protein products. Co-translational protein folding and interaction of ribosomes and emerging polypeptides with associated protein biogenesis factors determines the quality and localization of proteins. In this review we summarize recent findings on mechanisms of translation elongation in bacteria, including decoding and recoding, peptide bond formation, tRNA-mRNA translocation, co-translational protein folding, interaction with protein biogenesis factors, and targeting of ribosomes synthesizing membrane proteins to the plasma membrane. The data provide insights into how the ribosome shapes composition and quality of the cellular proteome.
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The determinants of bond angle variability in protein/peptide backbones: A comprehensive statistical/quantum mechanics analysis

Roberto Improta, Luigi Vitagliano and Luciana Esposito


Abstract

 

The elucidation of the mutual influence between peptide bond geometry and local conformation has important implications for protein structure refinement, validation, and prediction. To gain insights into the structural determinants and the energetic contributions associated with protein/peptide backbone plasticity, we here report an extensive analysis of the variability of the peptide bond angles by combining statistical analyses of protein structures and quantum mechanics calculations on small model peptide systems. Our analyses demonstrate that all the backbone bond angles strongly depend on the peptide conformation and unveil the existence of regular trends as function of ψ and/or φ. The excellent agreement of the quantum mechanics calculations with the statistical surveys of protein structures validates the computational scheme here employed and demonstrates that the valence geometry of protein/peptide backbone is primarily dictated by local interactions. Notably, for the first time we show that the position of the Hα hydrogen atom, which is an important parameter in NMR structural studies, is also dependent on the local conformation. Most of the trends observed may be satisfactorily explained by invoking steric repulsive interactions; in some specific cases the valence bond variability is also influenced by hydrogen-bond like interactions. Moreover, we can provide a reliable estimate of the energies involved in the interplay between geometry and conformations. 

 

 

Bernard Offmann's insight:

"all the backbone bond angles strongly depend on the peptide conformation". I do not understand very much what this means !

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Rapid search for tertiary fragments reveals protein sequence–structure relationships

Rapid search for tertiary fragments reveals protein sequence–structure relationships | Protein folds and folding | Scoop.it

Jianfu Zhou and Gevorg Grigoryan


Abstract


Finding backbone substructures from the Protein Data Bank that match an arbitrary query structural motif, composed of multiple disjoint segments, is a problem of growing relevance in structure prediction and protein design. Although numerous protein structure search approaches have been proposed, methods that address this specific task without additional restrictions and on practical time scales are generally lacking. Here, we propose a solution, dubbed MASTER, that is both rapid, enabling searches over the Protein Data Bank in a matter of seconds, and provably correct, finding all matches below a user-specified root-mean-square deviation cutoff. We show that despite the potentially exponential time complexity of the problem, running times in practice are modest even for queries with many segments. The ability to explore naturally plausible structural and sequence variations around a given motif has the potential to synthesize its design principles in an automated manner; so we go on to illustrate the utility of MASTER to protein structural biology. We demonstrate its capacity to rapidly establish structure–sequence relationships, uncover the native designability landscapes of tertiary structural motifs, identify structural signatures of binding, and automatically rewire protein topologies. Given the broad utility of protein tertiary fragment searches, we hope that providing MASTER in an open-source format will enable novel advances in understanding, predicting, and designing protein structure.

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Eager and impatient to test this tool and evaluate its performance...

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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.

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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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Managing the protein folding demands in the endoplasmic reticulum of plants. - PubMed - NCBI

New Phytol. 2016 Mar 14. doi: 10.1111/nph.13915. [Epub ahead of print] 


Liu JX, Howell SH.


Abstract

Endoplasmic reticulum (ER) stress occurs in plants during certain developmental stages or under adverse environmental conditions, as a result of the accumulation of unfolded or misfolded proteins in the ER. To minimize the accumulation of misfolded proteins in the ER, a protein quality control (PQC) system monitors protein folding and eliminates misfolded proteins through either ER-associated protein degradation (ERAD) or autophagy. ER stress elicits the unfolded protein response (UPR), which enhances the operation in plant cells of the ER protein folding machinery and the PQC system. The UPR also reduces protein folding demands in the ER by degrading mRNAs encoding secretory proteins. In plants subjected to severe or chronic stress, UPR promotes programmed cell death (PCD). Progress in the field in recent years has provided insights into the regulatory networks and signaling mechanisms of the ER stress responses in plants. In addition, novel physiological functions of the ER stress responses in plants for coordinating plant growth and development with changing environment have been recently revealed.



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A structural ensemble of a ribosome-nascent chain complex during cotranslational protein folding

Nature Structural & Molecular Biology 23, 278–285 (1 April 2016) | doi:10.1038/nsmb.3182 

Lisa D Cabrita , Anaïs M E Cassaignau , Hélène M M Launay , Christopher A Waudby , Tomasz Wlodarski , Carlo Camilloni , Maria-Evangelia Karyadi , Amy L Robertson , Xiaolin Wang , Anne S Wentink , Luke S Goodsell , Cheryl A Woolhead , Michele Vendruscolo , Christopher M Dobson & John Christodoulou

Abstract 

Although detailed pictures of ribosome structures are emerging, little is known about the structural and cotranslational folding properties of nascent polypeptide chains at the atomic level. Here we used solution-state NMR spectroscopy to define a structural ensemble of a ribosome–nascent chain complex (RNC) formed during protein biosynthesis in Escherichia coli, in which a pair of immunoglobulin-like domains adopts a folded N-terminal domain (FLN5) and a disordered but compact C-terminal domain (FLN6). To study how FLN5 acquires its native structure cotranslationally, we progressively shortened the RNC constructs. We found that the ribosome modulates the folding process, because the complete sequence of FLN5 emerged well beyond the tunnel before acquiring native structure, whereas FLN5 in isolation folded spontaneously, even when truncated. This finding suggests that regulating structure acquisition during biosynthesis can reduce the probability of misfolding, particularly of homologous domains.
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Prediction of protein folding rates from simplified secondary structure alphabet.

J Theor Biol. 2015 Aug 4. pii: S0022-5193(15)00369-0. doi: 10.1016/j.jtbi.2015.07.024. [Epub ahead of print] Huang JT, Wang T, Huang SR, Li X. AbstractProtein folding is a very complicated and highly cooperative dynamic process. However, the folding kinetics is likely to depend more on a few key structural features. Here we find that secondary structures can determine folding rates of only large, multi-state folding proteins and fails to predict those for small, two-state proteins. The importance of secondary structures for protein folding is ordered as: extended β strand>α helix>bend>turn>undefined secondary structure>310 helix>isolated β strand>π helix. Only the first three secondary structures, extended β strand, α helix and bend, can achieve a good correlation with folding rates. This suggests that the rate-limiting step of protein folding would depend upon the formation of regular secondary structures and the buckling of chain. The reduced secondary structure alphabet provides a simplified description for the machine learning applications in protein design.

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Bernard Offmann's curator insight, August 14, 2015 5:56 AM

Interesting theoretical insight.

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Directing peptide conformation with centrally positioned pre-organized dipeptide segments: studies of a 12-residue helix and β-hairpin

Chandrappa S, Madhusudana Reddy MB, Sonti R, Basuroy K, Raghothama S, Balaram P.Abstract

Secondary structure formation in oligopeptides can be induced by short nucleating segments with a high propensity to form hydrogen bonded turn conformations. Type I/III turns facilitate helical folding while type II'/I' turns favour hairpin formation. This principle is experimentally verified by studies of two designed dodecapeptides, Boc-Val-Phe-Leu-Phe-Val-Aib-Aib-Val-Phe-Leu-Phe-Val-OMe 1 and Boc-Val-Phe-Leu-Phe-Val-(D)Pro-(L)Pro-Val-Phe-Leu-Phe-Val-OMe 2. The N- and C-terminal flanking pentapeptide sequences in both cases are identical. Peptide 1 adopts a largely α-helical conformation in crystals, with a small 310 helical segment at the N-terminus. The overall helical fold is maintained in methanol solution as evidenced by NMR studies. Peptide 2 adopts an antiparallel β-hairpin conformation stabilized by 6 interstrand hydrogen bonds. Key nuclear Overhauser effects (NOEs) provide evidence for the antiparallel β-hairpin structure. Aromatic proton chemical shifts provide a clear distinction between the conformation of peptides 1 (helical) and 2 (β-hairpin). The proximity of facing aromatic residues positioned at non-hydrogen bonding positions in the hairpin results in extensively ring current shifted proton resonances in peptide 2.

Bernard Offmann's insight:

Very nice paper from P. Balaram's team (Molecular Biophysics Unit, Indian Institute of Science), on how to induce peptide to fold in desired way. The use of two consecutive 2-aminoisobutyric acids in central part of peptide nucleate a 3-10 helix while a D-Pro-L-Pro motif induced an antiparallel β-hairpin.

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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.

Bernard Offmann's insight:

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.

Bernard Offmann's insight:

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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Rescooped by Bernard Offmann from Bioinformatics, Comparative Genomics and Molecular Evolution
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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!

Scooped by Bernard Offmann
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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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