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A better understanding of protein aggregation is bound to translate into critical advances in several areas, including the treatment of misfolded protein disorders and the development of self-assembling biomaterials for novel commercial applications. Because of its ubiquity and clinical potential, albumin is one of the best-characterized models in protein aggregation research; but its properties in different conditions are not completely understood. Here, we carried out all-atom molecular dynamics simulations of albumin to understand how electrostatics can affect the conformation of a single albumin molecule just prior to self-assembly. We then analyzed the tertiary structure and solvent accessible surface area of albumin after electrostatically triggered partial denaturation. The data obtained from these single protein simulations allowed us to investigate the effect of electrostatic interactions between two proteins. The results of these simulations suggested that hydrophobic attractions and counterion binding may be strong enough to effectively overcome the electrostatic repulsions between the highly charged monomers. This work contributes to our general understanding of protein aggregation mechanisms, the importance of explicit consideration of free ions in protein solutions, provides critical new insights about the equilibrium conformation of albumin in its partially denatured state at low pH, and may spur significant progress in our efforts to develop biocompatible protein hydrogels driven by electrostatic partial denaturation.

A server (CheShift) has been developed to predict 13 C ␣ chemical shifts of protein structures. It is based on the generation of 696,916 conformations as a function of the , , , 1 and 2 torsional angles for all 20 naturally occurring amino acids. Their 13 C ␣ chemical shifts were computed at the DFT level of theory with a small basis set and extrapolated, with an empirically-determined linear regression formula, to reproduce the values obtained with a larger basis set. Analysis of the accuracy and sensitivity of the CheShift predictions, in terms of both the correlation coefficient R and the conformational-averaged rmsd between the observed and predicted 13 C ␣ chemical shifts, was carried out for 3 sets of conformations: (i) 36 x-ray-derived protein structures solved at 2.3 Å or better resolution, for which sets of 13 C ␣ chemical shifts were available; (ii) 15 pairs of x-ray and NMR-derived sets of protein conformations; and (iii) a set of decoys for 3 proteins showing an rmsd with respect to the x-ray structure from which they were derived of up to 3 Å. Comparative analysis carried out with 4 popular servers, namely SHIFTS, SHIFTX, SPARTA, and PROSHIFT, for these 3 sets of conformations demonstrated that CheShift is the most sensitive server with which to detect subtle differences between protein models and, hence, to validate protein structures determined by either x-ray or NMR methods, if the observed 13 C ␣ chemical shifts are available. CheShift is available as a web server. chemical shifts prediction ͉ DFT calculations ͉ validation server A ccurate and fast validation of protein structures constitutes a long-standing problem in NMR spectroscopy (1-3). Investigators have proposed a plethora of methods to determine the accuracy and reliability of protein structures in recent years (4-8). Despite this progress, there is a growing need for more sophisticated, physics-based and fast structure-validation methods (1, 2, 7). With these goals in mind, we recently proposed a new, physics-based solution of this important problem (9), viz., a methodology that makes use of observed and computed 13 C ␣ chemical shifts (at the DFT level of theory) for an accurate validation of protein structures in solution (9) and in a crystal (10). Assessment of the ability of computed 13 C ␣ chemical shifts to reproduce observed values for a single or an ensemble of structures in solution and in a crystal was accomplished by using the conformationally-averaged root-mean-square-deviation (ca-rmsd) as a scoring function (9). While computationally intensive, this methodology has several advantages: (i) it makes use of the 13 C ␣ chemical shifts, not shielding, that are ubiquitous to proteins; (ii) it can be computed accurately from the , , and torsional angles; (iii) there is no need for a priori knowledge of the oligomeric state of the protein; and (iv) no knowledgebased information or additional NMR data are required.However, the primary and the most serious limitation of the method is the computational cost of such calculations, whi...

Summary: The differences between observed and predicted 13Cα chemical shifts can be used as a sensitive probe with which to detect possible local flaws in protein structures. For this reason, we previously introduced CheShift, a Web server for protein structure validation. Now, we present CheShift-2 in which a graphical user interface is implemented to render such local flaws easily visible. A series of applications to 15 ensembles of conformations illustrate the ability of CheShift-2 to locate the main structural flaws rapidly and accurately on a per-residue basis. Since accuracy plays a central role in CheShift predictions, the treatment of histidine (His) is investigated here by exploring which form of His should be used in CheShift-2.Availability: CheShift-2 is free of charge for academic use and can be accessed from www.cheshift.comContact: has5@cornell.edu; jv84@cornell.eduSupplementary information: Supplementary data are available at the Bioinformatics online.

BackgroundProtected areas, regarded today as a cornerstone of nature conservation, result from an array of multiple motivations and opportunities. We explored at global and regional levels the current distribution of protected areas along biophysical, human, and biological gradients, and assessed to what extent protection has pursued (i) a balanced representation of biophysical environments, (ii) a set of preferred conditions (biological, spiritual, economic, or geopolitical), or (iii) existing opportunities for conservation regardless of any representation or preference criteria.MethodsWe used histograms to describe the distribution of terrestrial protected areas along biophysical, human, and biological independent gradients and linear and non-linear regression and correlation analyses to describe the sign, shape, and strength of the relationships. We used a random forest analysis to rank the importance of different variables related to conservation preferences and opportunity drivers, and an evenness metric to quantify representativeness.ResultsWe find that protection at a global level is primarily driven by the opportunities provided by isolation and a low population density (variable importance = 34.6 and 19.9, respectively). Preferences play a secondary role, with a bias towards tourism attractiveness and proximity to international borders (variable importance = 12.7 and 3.4, respectively). Opportunities shape protection strongly in “North America & Australia–NZ” and “Latin America & Caribbean,” while the importance of the representativeness of biophysical environments is higher in “Sub-Saharan Africa” (1.3 times the average of other regions).DiscussionEnvironmental representativeness and biodiversity protection are top priorities in land conservation agendas. However, our results suggest that they have been minor players driving current protection at both global and regional levels. Attempts to increase their relevance will necessarily have to recognize the predominant opportunistic nature that the establishment of protected areas has had until present times.

The room-temperature X-ray structures of ubiquitin (PDB code 1ubq) and of the RNA-binding domain of nonstructural protein 1 of influenza A virus (PDB code 1ail) solved at 1.8 and 1.9 Å resolution, respectively, were used to investigate whether a set of conformations rather than a single X-ray structure provides better agreement with both the X-ray data and the observed 13 C chemical shifts in solution. For this purpose, a set of new conformations for each of these proteins was generated by fitting them to the experimental X-ray data deposited in the PDB. For each of the generated structures, which show R and R free factors similar to those of the deposited X-ray structure, the 13 C chemical shifts of all residues in the sequence were computed at the DFT level of theory. The sets of conformations were then evaluated by their ability to reproduce the observed 13 C chemical shifts by using the conformational average root-mean-square-deviation (car.m.s.d.). For ubiquitin, the computed set of conformations is a better representation of the observed 13 C chemical shifts in terms of the ca-r.m.s.d. than a single X-ray-derived structure. However, for the RNA-binding domain of nonstructural protein 1 of influenza A virus, consideration of an ensemble of conformations does not improve the agreement with the observed 13 C chemical shifts. Whether an ensemble of conformations rather than any single structure is a more accurate representation of a protein structure in the crystal as well as of the observed 13 C chemical shifts is determined by the dispersion of coordinates, in terms of the all-atom r.m.s.d. among the generated models; these generated models satisfy the experimental X-ray data with accuracy as good as the PDB structure. Therefore, generation of an ensemble is a necessary step to determine whether or not a single structure is sufficient for an accurate representation of both experimental X-ray data and observed 13 C chemical shifts in solution.

Here we propose that the upper bound marginal stability of proteins ( ∼ 7.4 kcal/mol) is a universal property that includes macro-molecular complexes and is not affected by molecular changes such as mutations and Post-Translational Modifications (PTMs). Its existence is, essentially, a consequence of the Anfinsen's thermodynamics hypothesis rather than a result of an evolutive process. This result enables us to conjecture that neutral evolution should also be, with respect to protein stability, a universal phenomenon. DiscussionExperimental evidence indicates that proteins and complexes as ribosomes are marginally stable 1-4 . In this regards, and following Hormoz 5 , we define stability in terms of thermodynamics stability, namely as "… equivalent to the energy gap size between the native state and the first excited (misfolded) state…" That is, we are interested in biologically active proteins and complexes following a dynamic exchange with slightly higher-energy conformations retaining biological activity.

By using local (free-energy profiles along the amino acid sequence and 13 C α chemical shifts) and global (principal component) analyses to examine the molecular dynamics of protein-folding trajectories, generated with the coarse-grained united-residue force field, for the B domain of staphylococcal protein A, we are able to (i) provide the main reason for formation of the mirror-image conformation of this protein, namely, a slow formation of the second loop and part of the third helix (Asp29-Asn35), caused by the presence of multiple local conformational states in this portion of the protein; (ii) show that formation of the mirror-image topology is a subtle effect resulting from local interactions; (iii) provide a mechanism for how protein A overcomes the barrier between the metastable mirror-image state and the native state; and (iv) offer a plausible reason to explain why protein A does not remain in the metastable mirror-image state even though the mirror-image and native conformations are at least energetically compatible.misfolding | symmetrical proteins T o perform their functions in living organisms, most proteins must fold from unfolded polypeptides into their functional, unique 3D structures. Understanding protein-folding mechanisms is crucial because misfolded proteins can cause many diseases, including neurodegenerative diseases (1) such as Alzheimer's, Parkinson, and Huntington diseases. From theoretical and conceptual points of view, it has been suggested that a native protein exists in a thermodynamically stable state with its surroundings (2) and that a study of free-energy landscapes (FELs) holds the key to understanding how proteins fold and function (3, 4).The native structures of some proteins contain a high degree of symmetry that, in addition to the native structure, allows the existence of another, energetically very close to the native conformation, a native-like "mirror-image" structure. One of the representatives of such symmetrical proteins is the 10-to 55-residue fragment of the B domain of staphylococcal protein A [Protein Data Bank (PDB) ID: 1BDD, a three-α-helix bundle] (5). Protein A has been the subject of extensive theoretical (6-18) and experimental (19-23) studies because of its small size, fast folding kinetics, and biological importance. However, the mirror-image topology has never been a subject for discussion except for the earlier work by Olszewski et al. (7) and recent work by Noel et al. (24). The reason for this might be that it has never been detected experimentally and it was observed only in some theoretical studies (7-9, 12, 13, 15, 17, 18, 24) with different force fields. It is of interest to determine how realistic the mirror-image conformation is. Is it an artifact of the simulations or is it a conformation difficult to observe experimentally? Noel et al. (24) showed that the native and mirror-image structures have a similar enthalpic stability and are thermodynamically competitive and that the mirror image can be considered not just a computational annoyance...