Crystal structure of mammalian purple acid phosphatase

Background: Mammalian purple acid phosphatases are highly conserved binuclear metal-containing enzymes produced by osteoclasts, the cells that resorb bone. The enzyme is a target for drug design because there is strong evidence that it is involved in bone resorption. Results: The 1.55 Angstrom resolution structure of pig purple acid phosphatase has been solved by multiple isomorphous replacement. The enzyme comprises two sandwiched beta sheets flanked by or-helical segments. The molecule shows internal symmetry, with the metal ions bound at the interface between the two halves. Conclusions: Despite less than 15% sequence identity, the protein fold resembles that of the catalytic domain of plant purple acid phosphatase and some serine/threonine protein phosphatases. The active-site regions of the mammalian and plant purple acid phosphatases differ significantly, however. The internal symmetry suggests that the binuclear centre evolved as a result of the combination of mononuclear ancestors. The structure of the mammalian enzyme provides a basis for antiosteoporotic drug design.

Protein fold recognition score functions: Unusual construction strategies

We describe two ways of optimizing score functions for protein sequence to structure threading. The first method adjusts parameters to improve sequence to structure alignment. The second adjusts parameters so as to improve a score function's ability to rank alignments calculated in the first score function. Unlike those functions known as knowledge-based force fields, the resulting parameter sets do not rely on Boltzmann statistics, have no claim to representing free energies and are purely constructions for recognizing protein folds. The methods give a small improvement, but suggest that functions can be profitably optimized for very specific aspects of protein fold recognition, Proteins 1999;36:454-461. (C) 1999 Wiley-Liss, Inc.

Protein sequence threading, the alignment problem, and a two-step strategy

Conventionally, protein structure prediction via threading relies on some nonoptimal method to align a protein sequence to each member of a library of known structures. We show how a score function (force field) can be modified so as to allow the direct application of a dynamic programming algorithm to the problem. This involves an approximation whose damage can be minimized by an optimization process during score function parameter determination. The method is compared to sequence to structure alignments using a more conventional pair-wise score function and the frozen approximation. The new method produces results comparable to the frozen approximation, but is faster and has fewer adjustable parameters. It is also free of memory of the template's original amino acid sequence, and does not suffer from a problem of nonconvergence, which can be shown to occur with the frozen approximation. Alignments generated by the simplified score function can then be ranked using a second score function with the approximations removed. (C) 1999 John Wiley & Sons, Inc.

Three-dimensional structure of RK-1: A novel alpha-defensin peptide

NMR spectroscopy and simulated annealing calculations have been used to determine the three-dimensional structure of RK-1, an antimicrobial peptide from rabbit kidney recently discovered from homology screening based on the distinctive physicochemical properties of the corticostatins/defensins. RK-1 consists of 32 residues, including six cysteines arranged into three disulfide bonds. It exhibits antimicrobial activity against Escherichia coli and activates Ca2+ channels in vitro. Through its physicochemical similarity, identical cysteine spacing, and linkage to the corticostatins/defensins, it was presumed to be a member of this family. However, RK-1 lacks both a large number of arginines in the primary sequence and a high overall positive charge, which are characteristic of this family of peptides. The three-dimensional solution structure, determined by NMR, consists of a triple-stranded antiparallel beta -sheet and a series of turns and is similar to the known structures of other alpha -defensins. This has enabled the definitive classification of RK-1 as a member of this family of antimicrobial peptides. Ultracentrifuge measurements confirmed that like rabbit neutrophil defensins, RK-1 is monomeric in solution, in contrast to human neutrophil defensins, which are dimeric.

Crystal structure at 1.1 angstrom resolution of alpha-conotoxin PnIB: Comparison with alpha-conotoxins PnIA and GI

Conotoxins are small, cysteine-rich peptides isolated from the venom of Conus spp. of predatory marine snails, which selectively target specific receptors and ion channels critical to the functioning of the neuromuscular system. alpha-Conotoxins PnIA and PnIB are both 16-residue peptides (differing in sequence at only two positions) isolated from the molluscivorous snail Conus pennaceus. In contrast to the muscle-selective alpha-conotoxin GI from Conus geographus, PnIA and PnIB block the neuronal nicotinic acetylcholine receptor (nAChR). Here, we describe the crystal structure of PnIB, solved at a resolution of 1.1 Angstrom and phased using the Shake-and-Bake direct methods program. PnIB crystals are orthorhombic and belong to the space group P2(1)2(1)2(1) with the following unit cell dimensions: a = 14.6 Angstrom, b = 26.1 Angstrom, and c = 29.2 Angstrom. The final refined structure of alpha-conotoxin PnIB includes all 16 residues plus 23 solvent molecules and has an overall R-factor of 14.7% (R-free of 15.9%). The crystal structures of the alpha-conotoxins PnIB and PnIA are solved from different crystal forms, with different solvent contents. Comparison of the structures reveals them to be very similar, showing that the unique backbone and disulfide architecture is not strongly influenced by crystal lattice constraints or solvent interactions. This finding supports the notion that this structural scaffold is a rigid support for the presentation of important functional groups. The structures of PnIB and PnIA differ in their shape and surface charge distribution from that of GI.

A new wavelet-based adaptive method for solving population balance equations

A new wavelet-based adaptive framework for solving population balance equations (PBEs) is proposed in this work. The technique is general, powerful and efficient without the need for prior assumptions about the characteristics of the processes. Because there are steeply varying number densities across a size range, a new strategy is developed to select the optimal order of resolution and the collocation points based on an interpolating wavelet transform (IWT). The proposed technique has been tested for size-independent agglomeration, agglomeration with a linear summation kernel and agglomeration with a nonlinear kernel. In all cases, the predicted and analytical particle size distributions (PSDs) are in excellent agreement. Further work on the solution of the general population balance equations with nucleation, growth and agglomeration and the solution of steady-state population balance equations will be presented in this framework. (C) 2002 Elsevier Science B.V. All rights reserved.

Protein contact prediction using patterns of correlation

We describe a new method for using neural networks to predict residue contact pairs in a protein. The main inputs to the neural network are a set of 25 measures of correlated mutation between all pairs of residues in two windows of size 5 centered on the residues of interest. While the individual pair-wise correlations are a relatively weak predictor of contact, by training the network on windows of correlation the accuracy of prediction is significantly improved. The neural network is trained on a set of 100 proteins and then tested on a disjoint set of 1033 proteins of known structure. An average predictive accuracy of 21.7% is obtained taking the best L/2 predictions for each protein, where L is the sequence length. Taking the best L/10 predictions gives an average accuracy of 30.7%. The predictor is also tested on a set of 59 proteins from the CASP5 experiment. The accuracy is found to be relatively consistent across different sequence lengths, but to vary widely according to the secondary structure. Predictive accuracy is also found to improve by using multiple sequence alignments containing many sequences to calculate the correlations. (C) 2004 Wiley-Liss, Inc.

Countering cooperative effects in protease inhibitors using constrained b-strand-mimicking templates in focused combinatorial libraries

A major problem in de novo design of enzyme inhibitors is the unpredictability of the induced fit, with the shape of both ligand and enzyme changing cooperatively and unpredictably in response to subtle structural changes within a ligand. We have investigated the possibility of dampening the induced fit by using a constrained template as a replacement for adjoining segments of a ligand. The template preorganizes the ligand structure, thereby organizing the local enzyme environment. To test this approach, we used templates consisting of constrained cyclic tripeptides, formed through side chain to main chain linkages, as structural mimics of the protease-bound extended beta-strand conformation of three adjoining amino acid residues at the N- or C-terminal sides of the scissile bond of substrates. The macrocyclic templates were derivatized to a range of 30 structurally diverse molecules via focused combinatorial variation of nonpeptidic appendages incorporating a hydroxyethylamine transition-state isostere. Most compounds in the library were potent inhibitors of the test protease (HIV-1 protease). Comparison of crystal structures for five protease-inhibitor complexes containing an N-terminal macrocycle and three protease-inhibitor complexes containing a C-terminal macrocycle establishes that the macrocycles fix their surrounding enzyme environment, thereby permitting independent variation of acyclic inhibitor components with only local disturbances to the protease. In this way, the location in the protease of various acyclic fragments on either side of the macrocyclic template can be accurately predicted. This type of templating strategy minimizes the problem of induced fit, reducing unpredictable cooperative effects in one inhibitor region caused by changes to adjacent enzyme-inhibitor interactions. This idea might be exploited in template-based approaches to inhibitors of other proteases, where a beta-strand mimetic is also required for recognition, and also other protein-binding ligands where different templates may be more appropriate.

Structure and folding of potato type II proteinase inhibitors: Circular permutation and intramolecular domain swapping

Potato type II serine proteinase inhibitors are proteins that consist of multiple sequence repeats, and exhibit a multidomain structure. The structural domains are circular permutations of the repeat sequence.. as a result or intramolecular domain swapping. Structural studies give indications for the origins of this folding behaviour, and the evolution of the inhibitor family.

Structure of circulin B and implications for antimicrobial activity of the cyclotides

The solution structure of one of the first members of the cyclotide family of macrocyclic peptides to be discovered, circulin B has been determined and compared with that of circulin A and related cyclotides. Cyclotides are mini-proteins derived from plants that have the characteristic features of a head-to-tail cyclised peptide backbone and a knotted arrangement of their three disulfide bonds. First discovered because of their uterotonic or anti-HIV activity, they have also been reported to have activity against a range of Gram positive and Gram negative bacteria as well as fungi. The aim of the current study was to develop structure-activity relationships to rationalise this antimicrobial activity. Comparison of cyclotide structures and activities suggests that the presence and location of cationic residues may be a requirement for activity against Gram negative bacteria. Understanding the topological differences associated with the antimicrobial activity of the cyclotides is of significant interest and potentially may be harnessed for pharmaceutical applications.

Substrate specifity of protein kinases and computational prediction of substrates

To ensure signalling fidelity, kinases must act only on a defined subset of cellular targets. Appreciating the basis for this substrate specificity is essential for understanding the role of an individual protein kinase in a particular cellular process. The specificity in the cell is determined by a combination of peptide specificity of the kinase (the molecular recognition of the sequence surrounding the phosphorylation site), substrate recruitment and phosphatase activity. Peptide specificity plays a crucial role and depends on the complementarity between the kinase and the substrate and therefore on their three-dimensional structures. Methods for experimental identification of kinase substrates and characterization of specificity are expensive and laborious, therefore, computational approaches are being developed to reduce the amount of experimental work required in substrate identification. We discuss the structural basis of substrate specificity of protein kinases and review the experimental and computational methods used to obtain specificity information. (c) 2005 Elsevier B.V. All rights reserved.

Mimicking the action of GroEL in molecular dynamics simulations: Application to the refinement of protein structures

Bacterial chaperonin, GroEL, together with its co-chaperonin, GroES, facilitates the folding of a variety of polypeptides. Experiments suggest that GroEL stimulates protein folding by multiple cycles of binding and release. Misfolded proteins first bind to an exposed hydrophobic surface on GroEL. GroES then encapsulates the substrate and triggers its release into the central cavity of the GroEL/ES complex for folding. In this work, we investigate the possibility to facilitate protein folding in molecular dynamics simulations by mimicking the effects of GroEL/ES namely, repeated binding and release, together with spatial confinement. During the binding stage, the (metastable) partially folded proteins are allowed to attach spontaneously to a hydrophobic surface within the simulation box. This destabilizes the structures, which are then transferred into a spatially confined cavity for folding. The approach has been tested by attempting to refine protein structural models generated using the ROSETTA procedure for ab initio structure prediction. Dramatic improvements in regard to the deviation of protein models from the corresponding experimental structures were observed. The results suggest that the primary effects of the GroEL/ES system can be mimicked in a simple coarse-grained manner and be used to facilitate protein folding in molecular dynamics simulations. Furthermore, the results Sur port the assumption that the spatial confinement in GroEL/ES assists the folding of encapsulated proteins.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Crystal structures of reduced and oxidized DsbA: investigation of domain motion and thiolate stabilization

Background: The redox proteins that incorporate a thioredoxin fold have diverse properties and functions. The bacterial protein-folding factor DsbA is the most oxidizing of the thioredoxin family. DsbA catalyzes disulfide-bond formation during the folding of secreted proteins, The extremely oxidizing nature of DsbA has been proposed to result from either domain motion or stabilizing active-site interactions in the reduced form. In the domain motion model, hinge bending between the two domains of DsbA occurs as a result of redox-related conformational changes. Results: We have determined the crystal structures of reduced and oxidized DsbA in the same crystal form and at the same pH (5.6). The crystal structure of a lower pH form of oxidized DsbA has also been determined (pH 5.0). These new crystal structures of DsbA, and the previously determined structure of oxidized DsbA at pH 6.5, provide the foundation for analysis of structural changes that occur upon reduction of the active-site disulfide bond. Conclusions: The structures of reduced and oxidized DsbA reveal that hinge bending motions do occur between the two domains. These motions are independent of redox state, however, and therefore do not contribute to the energetic differences between the two redox states, instead, the observed domain motion is proposed to be a consequence of substrate binding. Furthermore, DsbA's highly oxidizing nature is a result of hydrogen bond, electrostatic and helix-dipole interactions that favour the thiolate over the disulfide at the active site.