Computational studies of the structure, dynamics and native content of amyloid-like fibrils of ribonuclease A

It is a common belief that some residues of a protein are more important than others. In some cases, point mutations of some residues make butterfly effect on the protein structure and function, but in other cases they do not. In addition, the residues important for the protein function tend to be not only conserved but also coevolved with other interacting residues in a protein. Motivated by these observations, the authors propose that there is a network composed of the residues, the residue-residue coevolution network (RRCN), where nodes are residues and links are set when the coevolutionary interaction strengths between residues are sufficiently large. The authors build the RRCN for the 44 diverse protein families. The interaction strengths are calculated by using McBASC algorithm. After constructing the RRCN, the authors identify residues that have high degree of connectivity (hub nodes), and residues that play a central role in network flow of information (C(I) nodes). The authors show that these residues are likely to be functionally important residues. Moreover, the C(I) nodes appear to be more relevant to the function than the hub nodes. Unlike other similar methods, the method described in this study is solely based on sequences. Therefore, the method can be applied to the function annotation of a wider range of proteins.     

Using lysozyme amyloid fibrils as a means of scavenging aggregation-inhibiting compounds

The aggregation of amyloidogenic proteins is linked to several amyloidoses, including neurodegenerative disorders, such as Alzheimer's or Parkinson's disease. Currently there are very few effective cures or treatments available, despite countless screenings and clinical trials. One of the most challenging aspects of potential anti-amyloid drug discovery is finding which molecules are the actual inhibitors out of mixtures, which may contain hundreds of distinct compounds. Considering that anti-amyloid compounds would interact with the aggregate, this affinity could be used as a means of separating such compounds from ineffective ones. In this work, we attempt to scavenge potential aggregation-inhibiting molecules out of four, different complexity mixtures, ranging from oxidized gallic acid to tea extract, using lysozyme amyloid fibrils. We show that these compounds bind to aggregates with high affinity and can be later separated from them by different methods.     

Interactions in native binding sites cause a large change in protein dynamics

Cellular functions are regulated by molecules that interact with proteins and alter their activities. To enable such control, protein activity, and therefore protein conformational distributions, must be susceptible to alteration by molecular interactions at functional sites. Here we investigate whether interactions at functional sites cause a large change in the protein conformational distribution. We apply a computational method, called dynamics perturbation analysis (DPA), to identify sites at which interactions have a large allosteric potential D(x), which is the Kullback-Leibler divergence between protein conformational distributions with and without an interaction. In DPA, a protein is decorated with surface points that interact with neighboring protein atoms, and D(x) is calculated for each of the points in a coarse-grained model of protein vibrations. We use DPA to examine hundreds of protein structures from a standard small-molecule docking test set, and find that ligand-binding sites have elevated values of D(x): for 95% of proteins, the probability of randomly obtaining values as high as those in the binding site is 10(-3) or smaller. We then use DPA to develop a computational method to predict functional sites in proteins, and find that the method accurately predicts ligand-binding-site residues for proteins in the test set. The performance of this method compares favorably with that of a cleft analysis method. The results confirm that interactions at small-molecule binding sites cause a large change in the protein conformational distribution, and motivate using DPA for large-scale prediction of functional sites in proteins. They also suggest that natural selection favors proteins whose activities are capable of being regulated by molecular interactions.     

Structure-based identification of binding sites,native ligands and potential inhibitors for G-protein coupled receptors

G-protein coupled receptors (GPCRs) are the largest family of cell-surface receptors involved in signal transmission. Drugs associated with GPCRs represent more than one fourth of the 100 top-selling drugs and are the targets of more than half of the current therapeutic agents on the market. Our methodology based on the internal coordinate mechanics (ICM) program can accurately identify the ligand-binding pocket in the currently available crystal structures of seven transmembrane (7TM) proteins [bacteriorhodopsin (BR) and bovine rhodopsin (bRho)]. The binding geometry of the ligand can be accurately predicted by ICM flexible docking with and without the loop regions, a useful finding for GPCR docking because the transmembrane regions are easier to model. We also demonstrate that the native ligand can be identified by flexible docking and scoring in 1.5% and 0.2% (for bRho and BR, respectively) of the best scoring compounds from two different types of compound database. The same procedure can be applied to the database of available chemicals to identify specific GPCR binders. Finally, we demonstrate that even if the sidechain positions in the bRho binding pocket are entirely wrong, their correct conformation can be fully restored with high accuracy (0.28 A) through the ICM global optimization with and without the ligand present. These binding site adjustments are critical for flexible docking of new ligands to known structures or for docking to GPCR homology models. The ICM docking method has the potential to be used to "de-orphanize" orphan GPCRs (oGPCRs) and to identify antagonists-agonists for GPCRs if an accurate model (experimentally and computationally validated) of the structure has been constructed or when future crystal structures are determined.     

Automated identification of binding sites for phosphorylated ligands in protein structures

Phosphorylation is a crucial step in many cellular processes, ranging from metabolic reactions involved in energy transformation to signaling cascades. In many instances, protein domains specifically recognize the phosphogroup. Knowledge of the binding site provides insights into the interaction, and it can also be exploited for therapeutic purposes. Previous studies have shown that proteins interacting with phosphogroups are highly heterogeneous, and no single property can be used to reliably identify the binding site. Here we present an energy‐based computational procedure that exploits the protein three‐dimensional structure to identify binding sites involved in the recognition of phosphogroups. The procedure is validated on three datasets containing more than 200 proteins binding to ATP, phosphopeptides, and phosphosugars. A comparison against other three generic binding site identification approaches shows higher accuracy values for our method, with a correct identification rate in the 80–90% range for the top three predicted sites. Addition of conservation information further improves the performance. The method presented here can be used as a first step in functional annotation or to guide mutagenesis experiments and further studies such as molecular docking. Proteins 2012;. © 2012 Wiley Periodicals, Inc.     

Multiple diverse ligands binding at a single protein site: A matter of pre-existing populations

Here, we comment on the steadily increasing body of data showing that proteins with specificity actually bind ligands of diverse shapes, sizes, and composition. Such a phenomenon is not surprising when one considers that binding is a dynamic process with populations in equilibrium and that the shape of the binding site is strongly influenced by the molecular partner. It derives implicitly from the concept of populations. All proteins, specific and nonspecific, exist in ensembles of substates. If the library of ligands in solution is large enough, favorably matching ligands with altered shapes and sizes can be expected to bind, with a redistribution of the protein populations. Point mutations at spatially distant sites may exert large conformational rearrangements and hinge effects, consistent with mutations away from the binding site leading to population shifts and (cross-)drug resistance. A similar effect is observed in protein superfamilies, in which different sequences with similar topologies display similar large-scale dynamic motions. The hinges are frequently at analogous sites, yet with different substrate specificity. Similar topologies yield similar conformational isomers, although with different distributions of population times, owing to the change in the conditions, that is, the change in the sequences. In turn, different distributions relate to binding of different sizes and shapes. Hence, the binding site shape and size are defined by the ligand. They are not independent entities of fixed proportions and cannot be analyzed independently of the binding partner. Such a proposition derives from viewing proteins as dynamic distributions, presenting to the incoming ligands a range of binding site shapes. It illustrates how presumably specific binding molecules can bind multiple ligands. In terms of drug design, the ability of a single receptor to recognize many dissimilar ligands shows the need to consider more diverse molecules. It provides a rationale for higher affinity inhibitors that are not derived from substrates at their transition states and indicates flexible docking schemes.     

Usage of a dataset of NMR resolved protein structures to test aggregation versus solubility prediction algorithms

There has been an increased interest in computational methods for amyloid and (or) aggregate prediction, due to the prevalence of these aggregates in numerous diseases and their recently discovered functional importance. To evaluate these methods, several datasets have been compiled. Typically, aggregation‐prone regions of proteins, which form aggregates or amyloids in vivo, are more than 15 residues long and intrinsically disordered. However, the number of such experimentally established amyloid forming and non‐forming sequences are limited, not exceeding one hundred entries in existing databases. In this work, we parsed all available NMR‐resolved protein structures from the PDB and assembled a new, sevenfold larger, dataset of unfolded sequences, soluble at high concentrations. We proposed to use these sequences as a negative set for evaluating methods for predicting aggregation in vivo. We also present the results of benchmarking cutting edge tools for the prediction of aggregation versus solubility propensity.     

FT-Raman spectroscopy as diagnostic tool of Congo red binding to amyloids

Chorion is the major component of silkmoth eggshell. More than 95% of its dry mass consists of the A and B families of low molecular weight structural proteins, which have remarkable mechanical and chemical properties protecting the oocyte and developing embryo from environmental hazards. We present data from FT-Raman spectroscopy of silkmoth chorion and amyloid-like fibrils formed from peptide analogues of chorion proteins, both unstained and stained by Congo red. The results show that FT-Raman spectroscopy is not a straightforward diagnostic tool for the specific interactions of Congo red with amyloids: a dilute aqueous solution of the Congo red dye at pH 5.5 and a thin solid film of the dye cast from this solution exhibit the same "diagnostic" Raman shifts relative to the neat Congo red dry powder as do amyloid fibrils formed from peptide analogues of chorion proteins stained by Congo red. An important consequence of this finding is that these shifts of the Raman active modes of Congo red are probably due to the formation of supramolecular dye aggregates in the presence of water. Therefore, this is not an appropriate diagnostic test for Congo red binding to amyloids.     

Ligand binding to a high‐energy partially unfolded protein

The conformational energy landscape of a protein determines populations of all possible conformations of the protein and also determines the kinetics of the conversion between the conformations. Interaction with ligands influences the conformational energy landscapes of proteins and shifts populations of proteins in different conformational states. To investigate the effect of ligand binding on partial unfolding of a protein, we use Escherichia coli dihydrofolate reductase (DHFR) and its functional ligand NADP⁺ as a model system. We previously identified a partially unfolded form of DHFR that is populated under native conditions. In this report, we determined the free energy for partial unfolding of DHFR at varying concentrations of NADP⁺ and found that NADP⁺ binds to the partially unfolded form as well as the native form. DHFR unfolds partially without releasing the ligand, though the binding affinity for NADP⁺ is diminished upon partial unfolding. Based on known crystallographic structures of NADP⁺‐bound DHFR and the model of the partially unfolded protein we previously determined, we propose that the adenosine‐binding domain of DHFR remains folded in the partially unfolded form and interacts with the adenosine moiety of NADP⁺. Our result demonstrates that ligand binding may affect the conformational free energy of not only native forms but also high‐energy non‐native forms.     

Ligand binding specificity of the Escherichia coli periplasmic histidine binding protein,HisJ

The HisJ protein from Escherichia coli and related Gram negative bacteria is the periplasmic component of a bacterial ATP‐cassette (ABC) transporter system. Together these proteins form a transmembrane complex that can take up L‐histidine from the environment and translocate it into the cytosol. We have studied the specificity of HisJ for binding L‐His and many related naturally occurring compounds. Our data confirm that L‐His is the preferred ligand, but that 1‐methyl‐L‐His and 3‐methyl‐L‐His can also bind, while the dipeptide carnosine binds weakly and D‐histidine and the histidine degradation products, histamine, urocanic acid and imidazole do not bind. L‐Arg, homo‐L‐Arg, and post‐translationally modified methylated Arg‐analogs also bind with reasonable avidity, with the exception of symmetric dimethylated‐L‐Arg. In contrast, L‐Lys and L‐Orn have considerably weaker interactions with HisJ and methylated and acetylated Lys variants show relatively poor binding. It was also observed that the carboxylate group of these amino acids and their variants was very important for proper recognition of the ligand. Taken together our results are a key step towards designing HisJ as a specific protein‐based reagentless biosensor.     

Structural Characterization of Polyglutamine Fibrils by Solid-State NMR Spectroscopy

Protein aggregation via polyglutamine stretches occurs in a number of severe neurodegenerative diseases such as Huntington's disease. We have investigated fibrillar aggregates of polyglutamine peptides below, at, and above the toxicity limit of around 37 glutamine residues using solid-state NMR and electron microscopy. Experimental data are consistent with a dry fibril core of at least 70-80 Å in width for all constructs. Solid-state NMR dipolar correlation experiments reveal a largely β-strand character of all samples and point to tight interdigitation of hydrogen-bonded glutamine side chains from different sheets. Two approximately equally frequent populations of glutamine residues with distinct sets of chemical shifts are found, consistent with local backbone dihedral angles compensating for β-strand twist or with two distinct sets of side-chain conformations. Peptides comprising 15 glutamine residues are present as single extended β-strands. Data obtained for longer constructs are most compatible with a superpleated arrangement with individual molecules contributing β-strands to more than one sheet and an antiparallel assembly of strands within β-sheets.     

Characterizing the structural variability of HIV-2 protease upon the binding of diverse ligands using a structural alphabet approach

Abstract

The HIV-2 protease (PR2) is an important target for designing new drugs against the HIV-2 infection. In this study, we explored the structural backbone variability of all available PR2 structures complexed with various inhibitors using a structural alphabet approach. 77% of PR2 positions are structurally variable, meaning they exhibit different local conformations in PR2 structures. This variability was observed all along the structure, particularly in the elbow and flap regions. A part of these backbone changes observed between the 18 PR2 is induced by intrinsic flexibility, and ligand binding putatively induces others occurring in the binding pocket. These latter changes could be important for PR2 adaptation to diverse ligands and are accompanied by changes outside the binding pocket. In addition, the study of the link between structural variability of the pocket and PR2–ligand interactions allowed us to localize pocket regions important for ligand binding and catalytic function, regions important for ligand recognition that adjust their backbone in response to ligand binding and regions important for the pocket opening and closing that have large intrinsic flexibility. Finally, we suggested that differences in ligand effectiveness for PR2 could be partially explained by different backbone deformations induced by these ligands. To conclude, this study is the first characterization of the PR2 structural variability considering ligand diversity. It provides information about the recognition of PR2 to various ligands and its mechanisms to adapt its local conformation to bound ligands that could help understand the resistance of PR2 to its inhibitors, a major antiretroviral class.

Communicated by Ramaswamy H. Sarma     

Understanding the contribution of disulfide bridges to the folding and misfolding of an anti‐Aβ scFv

ScFv‐h3D6 is a single chain variable fragment that precludes Aβ peptide‐induced cytotoxicity by withdrawing Aβ oligomers from the amyloid pathway to the worm‐like pathway. Production of scFv molecules is not a straightforward procedure because of the occurrence of disulfide scrambled conformations generated in the refolding process. Here, we separately removed the disulfide bond of each domain and solved the scrambling problem; and then, we intended to compensate the loss of thermodynamic stability by adding three C‐terminal elongation mutations, previously described to stabilize the native fold of scFv‐h3D6. Such stabilization occurred through stabilization of the intermediate state in the folding pathway and destabilization of a different, β‐rich, intermediate state driving to worm‐like fibrils. Elimination of the disulfide bridge of the less stable domain, V_L, deeply compromised the yield and increased the aggregation tendency, but elimination of the disulfide bridge of the more stable domain, V_H, solved the scrambling problem and doubled the production yield. Notably, it also changed the aggregation pathway from the protective worm‐like morphology to an amyloid one. This was so because a partially unfolded intermediate driving to amyloid aggregation was present, instead of the β‐rich intermediate driving to worm‐like fibrils. When combining with the elongation mutants, stabilization of the partially unfolded intermediate driving to amyloid fibrils was the only effect observed. Therefore, the same mutations drove to completely different scenarios depending on the presence of disulfide bridges and this illustrates the relevance of such linkages in the stability of different intermediate states for folding and misfolding.     

Fine-tuning spermidine binding modes in the putrescine binding protein PotF

A profound understanding of the molecular interactions between receptors and ligands is important throughout diverse research, such as protein design, drug discovery, or neuroscience. What determines specificity and how do proteins discriminate against similar ligands? In this study, we analyzed factors that determine binding in two homologs belonging to the well-known superfamily of periplasmic binding proteins, PotF and PotD. Building on a previously designed construct, modes of polyamine binding were swapped. This change of specificity was approached by analyzing local differences in the binding pocket as well as overall conformational changes in the protein. Throughout the study, protein variants were generated and characterized structurally and thermodynamically, leading to a specificity swap and improvement in affinity. This dataset not only enriches our knowledge applicable to rational protein design but also our results can further lay groundwork for engineering of specific biosensors as well as help to explain the adaptability of pathogenic bacteria.     

Effect of the concentration of protein and nanoparticles on the structure of biohybrid nanocomposites

We present colloidal nanocomposites formed by incorporating magnetite Fe₃O₄ nanoparticles (MNPs) with lysozyme amyloid fibrils (LAFs). Preparation of two types of solutions, with and without addition of salt, was carried out to elucidate the structure of MNPs-incorporated fibrillary nanocomposites and to study the effect of the presence of salt on the stability of the nanocomposites. The structural morphology of the LAFs and their interaction with MNPs were analyzed by atomic force microscopy and small-angle x-ray scattering measurements. The results indicate that conformational properties of the fibrils are dependent on the concentration of protein, and the precise ratio of the concentration of the protein and MNPs is crucially important for the stability of the fibrillary nanocomposites. Our results confirm that despite the change in fibrillary morphology induced by the varying concentration of the protein, the adsorption of MNPs on the surface of LAF is morphologically independent. Moreover, most importantly, the samples containing salt have excellent stability for up to 1 year of shelf-life.     

Raman signatures of ligand binding and allosteric conformation change in hexameric insulin.

Hexameric insulin is an allosteric protein that undergoes transitions between three conformational states (T(6), T(3)R(3), and R(6)). These allosteric states are stabilized by the binding of ligands to the phenolic pockets and by the coordination of anions to the His B10 metal sites. Raman difference (RD) spectroscopy is utilized to examine the binding of phenolic ligands and the binding of thiocyanate, p-aminobenzoic acid (PABA), or 4-hydroxy-3-nitrobenzoic acid (4H3N) to the allosteric sites of T(3)R(3) and R(6). The RD spectroscopic studies show changes in the amide I and III bands for the transition of residues B1-B8 from a meandering coil to an alpha helix in the T-R transitions and identify the Raman signatures of the structural differences among the T(6), T(3)R(3), and R(6) states. Evidence of the altered environment caused by the approximately 30 A displacement of phenylalanine (Phe) B1 is clearly seen from changes in the Raman bands of the Phe ring. Raman signatures arising from the coordination of PABA or 4H3N to the histidine (His) B10 Zn(II) sites show these carboxylates give distorted, asymmetric coordination to Zn(II). The RD spectra also reveal the importance of the position and the type of substituents for designing aromatic carboxylates with high affinity for the His B10 metal site.     

Effects of heterogeneity and cooperativity on the forms of binding curves for multivalent ligands

An exploratory investigation is made of the binding behavior that is likely to be encountered with multivalent ligands under circumstances where a single intrinsic binding constant does not suffice to describe all acceptor-ligand interactions. Numerical simulations of theoretical binding behavior have established that current criteria for recognizing heterogeneity and cooperativity of acceptor sites on the basis of the deviation of the binding curve from rectangular hyperbolic form for univalent ligands also apply to the interpretation of the corresponding binding curves for multivalent ligands. However, for systems in which the source of the departure from equivalence and independence of binding sites resides in the ligand, these criteria are reversed. On the basis of these observations a case is then made for attributing results of an experimental binding study of the interaction between pyruvate kinase and muscle myofibrils to positive cooperativity of enzyme sites rather than to heterogeneity or negative cooperativity of the myofibrillar sites.     

A metal binding in the polypeptide chain improves the folding efficiency of a denatured and reduced protein

In order to examine the effect of a metal binding to the polypeptide chain on the aggregation of a protein in the refolding process, we prepared a mutant hen lysozyme possessing the same Ca(2+) binding site as in human alpha-lactalbumin by Escherichia coli expression system (Ser(-1) CaB lysozyme). In the presence of 2 mM CaCl(2), the refolding yield of Ser(-1) CaB lysozyme at a low protein concentration (25 microg/mL) was similar to that of the wild-type lysozyme (80%), but that at high protein concentration (200 microg/mL) decreased (15%) due to aggregation comparing to that of the wild-type lysozyme (45%). However, the refolding yield of Ser(-1) CaB lysozyme in the presence of 100 mM CaCl(2) even at a protein concentration of 200 microg/mL was 80% and was higher than that of the wild-type lysozyme. From analysis of chemical shift changes of the cross peaks in the backbone region of total correlated spectroscopy (TOCSY) spectra of a decapeptide possessing the same calcium binding site as in Ser(-1) CaB lysozyme in the presence of various concentrations of Ca(2+), it was suggested that the dissociation constant of Ca(2+)-peptide complex was estimated to be 20-36 mM. Moreover, the solubility of the denatured Ser(-1) CaB lysozyme in the presence of 100 mM CaCl(2) was higher than that in the presence of 2 mM CaCl(2) whereas the solubility of the denatured Ser(-1) lysozyme in the presence of 100 mM CaCl(2) was not higher than that in the presence of 2 mM CaCl(2). Therefore, it was concluded that the reduced lysozyme possessing the Ca(2+) binding site was efficiently folded in the presence of high concentration of Ca(2+) (100 mM) even at high protein concentration due to depression of aggregation by the binding of Ca(2+) to the polypeptide chain in Ser(-1) CaB lysozyme.