The performance of the physics-based protocol, whose main component is the United Residue (UNRES) physics-based coarse-grained force field, developed in our laboratory for the prediction of protein structure from amino acid sequence, is illustrated. Candidate models are selected, based on probabilities of the conformational families determined by multiplexed replica-exchange simulations, from the 10th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP10). For target T0663, classified as a new fold, which consists of two α + β domains homologous to those of known proteins, UNRES predicted the correct symmetry of packing, in which the domains are rotated with respect to each other by 180°in the experimental structure. By contrast, models obtained by knowledge-based methods, in which each domain is modeled very accurately but not rotated, resulted in incorrect packing. Two UNRES models of this target were featured by the assessors. Correct domain packing was also predicted by UNRES for the homologous target T0644, which has a similar structure to that of T0663, except that the two domains are not rotated. Predictions for two other targets, T0668 and T0684_D2, are among the best ones by global distance test score. These results suggest that our physicsbased method has substantial predictive power. In particular, it has the ability to predict domain-domain orientations, which is a significant advance in the state of the art.protein folding | structure symmetry | multi-domain packing P rediction of protein structures from amino acid sequence still remains an unsolved problem of computational biology. Although, since the famous experiments by Anfinsen (1), it is known that a protein adopts the structure which is the (kinetically reachable) global minimum of the free energy of a system, it is not straightforward to implement this physical principle in practice because of the inaccuracy of existing force fields and because of the enormous difficulty to search the conformational space of the system. Therefore, the most effective methods for protein-structure prediction nowadays are knowledge-based approaches, in which database information is incorporated explicitly into the procedure (2). These methods can be divided into three categories, namely, comparative (homology) modeling (3-5), in which the target sequence is compared with the sequences for which experimental structures are known and those structures are usually selected as candidate models for which the greatest similarity is observed; threading (6-8), in which the target sequence is superposed on structures from a database, and those which give the highest score (lowest pseudoenergy) are selected as candidate predictions; and, finally, the fragment-assembly or minithreading method developed by David Baker and colleagues (9, 10), in which the predicted structure is assembled from nine-residue fragments extracted from a protein-structure database, and knowledge-and physicsbased filters are applied at each asse...

Fibrils formed by the β-amyloid (Aβ) peptide play a central role in the development of Alzheimer’s disease. In this study, the principles governing their growth and stability are investigated by analyzing canonical and replica-exchange molecular dynamics trajectories of Aβ(9–40) fibrils. In particular, an unstructured monomer was allowed to interact freely with an Aβ fibril template. Trajectories were generated with the coarse-grained united-residue force field, and one- and two-dimensional free-energy landscapes (FELs) along the backbone virtual-bond angle θ and backbone virtual-bond-dihedral angle γ of each residue and principal components, respectively, were analyzed. Also, thermal unbinding (unfolding) of an Aβ peptide from the fibril template was investigated. These analyses enable us to illustrate the entire process of Aβ fibril elongation and to elucidate the key residues involved in it. Several different pathways were identified during the search for the fibril conformation by the monomer, which finally follows a dock-lock mechanism with two distinct locking stages. However, it was found that the correct binding, with native hydrogen bonds, of the free monomer to the fibril template at both stages is crucial for fibril elongation. In other words, if the monomer is incorrectly bound (with nonnative hydrogen bonds) to the fibril template during the first “docking” stage, it can remain attached to it for a long time before it dissociates and either attempts a different binding or allows another monomer to bind. This finding is consistent with an experimentally-observed “stop-and-go” mechanism of fibril growth.

The origins of formation of an intermediate state involved in amyloid formation and ways to prevent it are illustrated with the example of the Formin binding protein 28 (FBP28) WW domain, which folds with biphasic kinetics. Molecular dynamics of protein folding trajectories are used to examine local and global motions and the time dependence of formation of contacts between C α s and C β s of selected pairs of residues. Focus is placed on the WT FBP28 WW domain and its six mutants (L26D, L26E, L26W, E27Y, T29D, and T29Y), which have structures that are determined by high-resolution NMR spectroscopy. The origins of formation of an intermediate state are elucidated, viz. as formation of hairpin 1 by a hydrophobic collapse mechanism causing significant delay of formation of both hairpins, especially hairpin 2, which facilitates the emergence of an intermediate state. It seems that three-state folding is a major folding scenario for all six mutants and WT. Additionally, two-state and downhill folding scenarios were identified in ∼15% of the folding trajectories for L26D and L26W, in which both hairpins are formed by the Matheson-Scheraga mechanism much faster than in three-state folding. These results indicate that formation of hairpins connecting two antiparallel β-strands determines overall folding. The correlations between the local and global motions identified for all folding trajectories lead to the identification of the residues making the main contributions in the formation of the intermediate state. The presented findings may provide an understanding of protein folding intermediates in general and lead to a procedure for their prevention.A n intermediate state in protein folding is involved in amyloid fibril formation, which is responsible for a number of neurodegenerative diseases (1-7). Therefore, prevention of the aggregation of folding intermediates is one of the most important problems to surmount. Hence, it is necessary to determine the mechanism by which an intermediate state is formed. For example, one of the members of the WW domain family (8, 9), the triple β-stranded WW domain from the Formin binding protein 28 (FBP28; Protein Data Bank ID code 1E0L) (10) (Fig. 1N), has been shown to fold with biphasic kinetics exhibiting intermediates during folding (3,5,6,(11)(12)(13)(14)(15)(16). We address this problem here with the design of new FBP28 WW domain mutants and by examining their structural properties and folding kinetics.Because of the small size, fast folding kinetics, and biological importance, the formation of intermolecular β-sheets is thought to be a crucial event in the initiation and propagation of amyloid diseases, such as Alzheimer's disease, and spongiform encephalopathy, FBP28, and other WW domain proteins (e.g., Pin1 and FiP35) have been the subjects of extensive experimental (4,11,(17)(18)(19)(20)(21)(22)(23) and theoretical (3,5,6,(12)(13)(14)(15)(16)(24)(25)(26)(27) studies. However, a folding mechanism of the FBP28 was debatable for a long time because of its complexity. There ar...

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...

We recently introduced a physically based approach to sequence comparison, the property factor method (PFM). In the present work, we apply the PFM approach to the study of a challenging set of sequences-the bacterial chemotaxis protein CheY, the N-terminal receiver domain of the nitrogen regulation protein NT-NtrC, and the sporulation response regulator Spo0F. These are all response regulators involved in signal transduction. Despite functional similarity and structural homology, they exhibit low sequence identity. PFM sequence comparison demonstrates a statistically significant qualitative difference between the sequence of CheY and those of the other two proteins that is not found using conventional alignment methods. This difference is shown to be consonant with structural characteristics, using distance matrix comparisons. We also demonstrate that residues participating strongly in native contacts during unfolding are distributed differently in CheY than in the other two proteins. The PFM result is also in accord with dynamic simulation results of several types. Molecular dynamics simulations of all three proteins were carried out at several temperatures, and it is shown that the dynamics of CheY are predicted to differ from those of NT-NtrC and Spo0F. The predicted dynamic properties of the three proteins are in good agreement with experimentally determined B factors and with fluctuations predicted by the Gaussian network model. We pinpoint the differences between the PFM and traditional sequence comparisons and discuss the informatic basis for the ability of the PFM approach to detect physical differences between these sequences that are not apparent from traditional alignment-based comparison.amino acid physical properties | protein fluctuations | all-atom simulations