Atomically precise (catalytic) particles synthesized by a novel cluster deposition instrument.

We report a new high vacuum instrument which is dedicated to the preparation of well-defined clusters supported on model and technologically relevant supports for catalytic and materials investigations. The instrument is based on deposition of size selected metallic cluster ions that are produced by a high flux magnetron cluster source. The throughput of the apparatus is maximized by collecting and focusing ions utilizing a conical octupole ion guide and a linear ion guide. The size selection is achieved by a quadrupole mass filter. The new design of the sample holder provides for the preparation of multiple samples on supports of various sizes and shapes in one session. After cluster deposition onto the support of interest, samples will be taken out of the chamber for a variety of testing and characterization.

Empirical potentials and functions for protein folding and binding.

Simplified models and empirical potentials are being increasingly used for the analysis of proteins, frequently augmenting or replacing molecular mechanics approaches. Recent folding simulations have employed potentials that, in addition to terms assuring proper polypeptide geometry, include only two noncovalent effects-hydrogen bonding and hydrophobicity, with extremely simple approximations to the latter. The potentials that have been used in the free-energy ranking of protein-ligand complexes have generally been more involved. These potentials have more detailed solvation models and account for both local (hydrophobic and polar) solute-solvent phenomena and long range electrostatic solvation effects. The models of solvation that have been used most frequently are surface area related atomic parameters, knowledge-based models extracted from protein-structure data, and continum electrostatics with an additional area-related parameter. The knowledge-based approaches to solvation, although convenient and accurate enough, are suspect of double counting certain free-energy terms.

Streptavidins with intersubunit crosslinks have enhanced stability.

Natural tetrameric streptavidin has two subunit interfaces; one is a strong interface between subunits in a tightly associated dimer, and the other is a weak interface between a pair of such dimers (dimer-dimer interface). To test whether strengthening the weak dimer-dimer interface could provide streptavidin with additional structural stability, covalent crosslinks were introduced between adjacent subunits through the dimer-dimer interface. Specific crosslinking sites were designed by site-directed mutations of His-127 residues that are in close proximity in natural streptavidin. The first and second streptavidin constructs have a disulfide bond and an irreversible covalent bond, respectively, between two Cys-127 residues across the dimer-dimer interface. The third variant is a hybrid tetramer consisting of two different streptavidin species, one having lysine and the other aspartic acid at position 127, which are covalently crosslinked. All streptavidin constructs with intersubunit crosslinks showed higher biotin-binding ability than natural core streptavidin after heat treatment. All of these crosslinked streptavidins retained bound biotin more stably than natural core streptavidin in guanidine hydrochloride at very acidic pH. These results suggest that the introduction of covalent bonds across the dimer-dimer interface enhances the overall stability of streptavidin.

Conformational filtering in polypeptides and proteins.

We present a method for assigning an ensemble of conformational states to each amino acid residue of a sequence. The states are defined as regions in the (phi, psi) map. The procedure is based on the use of conformational filters. In each filter we use a different set of approximations to estimate the probability of conformational states, and retain only the ones whose probability exceeds an acceptance probability. The resulting state assignment is not necessarily unique, but provides information that can be further exploited in searches for the tertiary structure. This conformational filtering approach to the de novo analysis of a sequence has a number of advantages over traditional structure prediction. First, it is possible to select acceptance probabilities such that the true conformational state is retained for up to 87% of residues, while substantially reducing the number of potential conformations. Second, in solution most linear peptides are present as ensembles of rapidly interconverting conformers, and such ensembles can be well predicted by filtering. Third, we can use Markov chains instead of a statistical mechanical (Ising) treatment, and avoid the need for estimating statistical weight matrices valid for the molecule as a whole. Markov models can use local transition matrices that are assumed to be independent of the rest of the chain, and are directly calculated from pairwise data. We show here that the locally identifiable transition matrices are transferable from the crystal structures of proteins to the solution structures of short peptides, and the ensembles of filtered conformations are in good agreement with nuclear magnetic resonance data. When applied to proteins, the filters retain several conformational states for most residues, and provide a measure of conformational variability. Small variability means that the segment is well defined by local interactions alone, and hence is likely to preserve its structure when isolated from the rest of the chain. Conversely, the structure of a segment with above-average conformational variability is likely to be significantly affected by its protein environment.

Computing the structure of bound peptides. Application to antigen recognition by class I major histocompatibility complex receptors.

The ability to accurately compute the atomic positions of substrate-bound ligands is central to understanding biological recognition. Although substantial progress has been made in docking small, relatively rigid ligands, the problem of docking flexible peptides remains open. In this communication we present a new method that allows configurational flexibility of peptides, and apply it to predict the conformation of peptides bound to two class-I major histocompatibility complex receptors: human HLA-A2, and murine H-2Kb. Using only the approximate locations of the amino and carboxyl-terminal residues of the bound peptide, our calculations yield structures with backbone conformations that are similar to structures reported crystallographically.

Selecting near-native conformations in homology modeling: the role of molecular mechanics and solvation terms.

A free energy function, combining molecular mechanics energy with empirical solvation and entropic terms, is used for ranking near-native conformations that occur in the conformational search steps of homology modeling, i.e., side-chain search and loop closure calculations. Correlations between the free energy and RMS deviation from the X-ray structure are established. It is shown that generally both molecular mechanics and solvation/entropic terms should be included in the potential. The identification of near-native backbone conformations is accomplished primarily by the molecular mechanics term that becomes the dominant contribution to the free energy if the backbone is even slightly strained, as frequently occurs in loop closure calculations. Both terms become equally important if a sufficiently accurate backbone conformation is found. Finally, the selection of the best side-chain positions for a fixed backbone is almost completely governed by the solvation term. The discriminatory power of the combined potential is demonstrated by evaluating the free energies of protein models submitted to the first meeting on Critical Assessment of techniques for protein Structure Prediction (CASP1), and comparing them to the free energies of the native conformations.

Prediction of protein complexes using empirical free energy functions.

A long sought goal in the physical chemistry of macromolecular structure, and one directly relevant to understanding the molecular basis of biological recognition, is predicting the geometry of bimolecular complexes from the geometries of their free monomers. Even when the monomers remain relatively unchanged by complex formation, prediction has been difficult because the free energies of alternative conformations of the complex have been difficult to evaluate quickly and accurately. This has forced the use of incomplete target functions, which typically do no better than to provide tens of possible complexes with no way of choosing between them. Here we present a general framework for empirical free energy evaluation and report calculations, based on a relatively complete and easily executable free energy function, that indicate that the structures of complexes can be predicted accurately from the structures of monomers, including close sequence homologues. The calculations also suggest that the binding free energies themselves may be predicted with reasonable accuracy. The method is compared to an alternative formulation that has also been applied recently to the same data set. Both approaches promise to open new opportunities in macromolecular design and specificity modification.

Free energy mapping of class I MHC molecules and structural determination of bound peptides.

Free energy maps of the binding site are constructed for class I major histocompatibility complex (MHC) proteins, by rotating and translating amino acid probes along the cleft, and performing a side-chain conformational search at each position. The free energy maps are used to determine favorable residue positions that are then combined to form docked peptide conformations. Because the generic backbone structural motif of peptides bound to class I MHC is known, the mapping is restricted to appropriate regions of the site, but allows for the sometimes substantial variations in backbone and side-chain conformations. In a test demonstrating the quality of predictions for a known MHC site using only a rotational and conformational search, we started from the crystal structure of the HIV-1 gp120/HLA-A2 complex, and predicted the HLA-A2 bound structures of peptides from the influenza matrix protein, the HIV-1 reverse transcriptase, and the human T cell leukemia virus. The calculated peptides are at 1.6, 1.3, and 1.4 A all-atom RMSDs from their respective crystal structures (Madden DR, Garboczi DN, Wiley DC, 1993). A further test, which also included a local translational search, predicted structures across MHCs. In particular, we obtained the Kb/SEV-9 complex (Fremont DH et al., 1992, Science 257:919-927) starting with the complex between HLA-B27 and a generic peptide (Madden DR, Gorga JC, Strominger JL, Wiley DC, 1991, Nature (Lond) 353:321-325), with an all-atom RMSD of 1.2 A, indicating that the docking procedure is essentially as effective for predictions across MHCs as it is for determinations within the same MHC, although at substantially greater computational cost. The requirements for further improvement in accuracy are identified and discussed briefly.

Empirical free energy calculation: comparison to calorimetric data.

An effective free energy potential, developed originally for binding free energy calculation, is compared to calorimetric data on protein unfolding, described by a linear combination of changes in polar and nonpolar surface areas. The potential consists of a molecular mechanics energy term calculated for a reference medium (vapor or nonpolar liquid), and empirical terms representing solvation and entropic effects. It is shown that, under suitable conditions, the free energy function agrees well with the calorimetric expression. An additional result of the comparison is an independent estimate of the side-chain entropy loss, which is shown to agree with a structure-based entropy scale. These findings confirm that simple functions can be used to estimate the free energy change in complex systems, and that a binding free energy evaluation model can describe the thermodynamics of protein unfolding correctly. Furthermore, it is shown that folding and binding leave the sum of solute-solute and solute-solvent van der Waals interactions nearly invariant and, due to this invariance, it may be advantageous to use a nonpolar liquid rather than vacuum as the reference medium.

Determining protein loop conformation using scaling-relaxation techniques.

We recently developed a rapid loop closure algorithm in which bond lengths are scaled to constrain the ends of a segment to match a known distance and then gradually relaxed to their standard values, with boundary constraints maintained. Although the algorithm predicted the Zif286 zinc-finger loop to within approximately 2 A, it had a serious limitation that made its more general use tentative: it omitted the atomic environment of the loop. Here we report an extension of the algorithm to take into account the protein environment surrounding a given loop from the outset of the conformational search and show that it predicts structure with an efficiency and accuracy that could not be achieved without continuous environmental inclusion. The algorithm should be widely applicable to structure determination when complete experimental information is unavailable.

Toward computational determination of peptide-receptor structure.

We introduce a method for docking small flexible ligands of the size of dipeptides and phosphocholine and test it against crystallographic complexes. We then show how the method can be used as the basis for a strategy for solving the much more difficult problem of docking fully flexible peptides in the 8-10-residue size range. After developing the method we apply it to peptide-MHC class I systems and find that the predictions are in accord with biological and crystallographic data.

The binding domain structure of retinoblastoma-binding proteins.

The retinoblastoma gene product (Rb), a cellular growth suppressor, complexes with viral and cellular proteins that contain a specific binding domain incorporating three invariant residues: Leu-X-Cys-X-Glu, where X denotes a nonconserved residue. Hydrophobic and electrostatic properties are strongly conserved in this segment even though the nonconserved amino acids vary considerably from one Rb-binding protein to another. In this report, we present a diagnostic computer pattern for a high-affinity Rb-binding domain featuring the three conserved residues as well as the conserved physico-chemical properties. Although the pattern encompasses only 10 residues (with only 4 of these explicitly defined), it exhibits 100% sensitivity and 99.95% specificity in database searches. This implies that a certain pattern of structural and physico-chemical properties encoded by this short sequence is sufficient to govern specific Rb binding. We also present evidence that the secondary structural conformation through this region is important for effective Rb binding.

Empirical free energy as a target function in docking and design: application to HIV-1 protease inhibitors.

Structure-based drug design requires the development of efficient computer programs for exploring the structural compatibility of various flexible ligands with a given receptor. While various algorithms are available for finding docked conformations, selecting a target function that can reliably score the conformations remains a serious problem. We show that the use of an empirical free energy evaluation method, originally developed to characterize protein-protein interactions, can substantially improve the efficacy of search algorithms. In addition to the molecular mechanics interaction energy, the function takes account of solvation and side chain conformational entropy, while remaining simple enough to replace the incomplete target functions used in many drug docking and design procedures. The free energy function is used here in conjunction with a simple site mapping-fragment assembly algorithm, for docking the MVT-101 non-peptide inhibitor to HIV-1 protease. In particular, we predict the bound structure with an all atom RMSD of 1.21 A, compared to 1.69 A using an energy target function, and also accurately predict the free energy shifts obtained with a series of five trimeric hydroxyethylene isostere analogs.

Indistinguishability for a class of nonlinear compartmental models.

Indistinguishability, as applied to nonlinear compartmental models, is analyzed by means of the local state isomorphism theorem. The method of analysis involves the determination of all local, diffeomorphic transformations connecting the state variables of two models. This is then applied to two two-compartment models, in the first instance with linear eliminations, and then with the addition of eliminations with Michaelis-Menten kinetics. In the nonlinear example, the state transformation turns out to be linear or possibly affine. It is found that the nonlinear analysis could be eased by splitting the state isomorphism equations into those of the initial linear models together with extra equations due to the nonlinearities.

Global identifiability of the parameters of nonlinear systems with specified inputs: a comparison of methods.

The two methods available for analyzing the global structural identifiability of the parameters of a nonlinear system with a specified input function, the Taylor series approach and the similarity transformation approach, are compared and contrasted through application to three examples. It is shown that, as for linear systems, it is very difficult to predict which of the available methods will result in the least effort for a particular example. The role of modern symbolic manipulation packages in the analysis is assessed. The third example proves intractable using the similarity transformation approach as originally formulated, but the analysis is completed using a reformulation that exploits the polynominal form of the system equations in the example.

Similarity transformation approach to identifiability analysis of nonlinear compartmental models.

Through use of the local state isomorphism theorem instead of the algebraic equivalence theorem of linear systems theory, the similarity transformation approach is extended to nonlinear models, resulting in finitely verifiable sufficient and necessary conditions for global and local identifiability. The approach requires testing of certain controllability and observability conditions, but in many practical examples these conditions prove very easy to verify. In principle the method also involves nonlinear state variable transformations, but in all of the examples presented in the paper the transformations turn out to be linear. The method is applied to an unidentifiable nonlinear model and a locally identifiable nonlinear model, and these are the first nonlinear models other than bilinear models where the reason for lack of global identifiability is nontrivial. The method is also applied to two models with Michaelis-Menten elimination kinetics, both of considerable importance in pharmacokinetics, and for both of which the complicated nature of the algebraic equations arising from the Taylor series approach has hitherto defeated attempts to establish identifiability results for specific input functions.

Parameter space boundaries for unidentifiable compartmental models.

Methods for dealing with unidentifiable compartmental models are first reviewed, emphasizing the parameter interval analysis and exhaustive modeling approaches. More general methods are presented for generating the set of all nonnegative parameter solutions that localize the parameters within bounded regions of parameter space and extend previously published parameter bounding strategies. Each point of these regions is an equivalent solution of the parameter identification problem. If a point on the boundary is selected, at least one of the parameters vanishes and an equivalent submodel is obtained. This property shows the close relationship between the exhaustive modeling and parameter interval analysis approaches.

Beta-turn new classification and its some features in proteins.

An inspection of the phi-psi angle distribution strongly suggests that protein folding is highly constrained. A number of researchers have even suggested that a relatively small set of discrete phi-psi regions might be sufficient to describe most protein conformation. The total of 541 tight turns from 101 non-identical proteins were extracted form Brookhaven DataBank. The dihedral values of tight turns were scattered into the seven regions on the Ramachandran plot. These seven regions were called A1, A2, B1, B2, B22, T1 and T2. A1 and A2 are the traditional alpha-helix regions, B1, B2 and B22 the beta-strand regions, T1 and T2 the beta-turn regions. The A2 and T2 regions were not defined as "discrete" or single points but rather as one dimensional extended states. Based on the geometry of the two central residues of the tight turns, the new classification of beta-turn was defined. This classification of the majority of beta-turns fell into only six of the possible forty nine region combinations and were identifiable with the traditional nomenclature of Venkatachalam(1), but much simpler. The function of beta-turn in the conformation of proteins was studied. The hydrophobicity for different type turns was discussed. It shows that beta-turns have very strong hydrophilic property, so they are usually situated at the folding protein surface. The features of beta-turn and its amino acid distribution in this 541 beta-turn group and different type beta-turn were given.

Evolutionary origins of the estrogen signaling system: insights from amphioxus.

Classically, the estrogen signaling system has two core components: cytochrome P450 aromatase (CYP19), the enzyme complex that catalyzes the rate limiting step in estrogen biosynthesis; and estrogen receptors (ERs), ligand activated transcription factors that interact with the regulatory region of target genes to mediate the biological effects of estrogen. While the importance of estrogens for regulation of reproduction, development and physiology has been well-documented in gnathostome vertebrates, the evolutionary origins of estrogen as a hormone are still unclear. As invertebrates within the phylum Chordata, cephalochordates (e.g., the amphioxus of the genus Branchiostoma) are among the closest invertebrate relatives of the vertebrates and can provide critical insight into the evolution of vertebrate-specific molecules and pathways. To address this question, this paper briefly reviews relevant earlier studies that help to illuminate the history of the aromatase and ER genes, with a particular emphasis on insights from amphioxus and other invertebrates. We then present new analyses of amphioxus aromatase and ER sequence and function, including an in silico model of the amphioxus aromatase protein, and CYP19 gene analysis. CYP19 shares a conserved gene structure with vertebrates (9 coding exons) and moderate sequence conservation (40% amino acid identity with human CYP19). Modeling of the amphioxus aromatase substrate binding site and simulated docking of androstenedione in comparison to the human aromatase shows that the substrate binding site is conserved and predicts that androstenedione could be a substrate for amphioxus CYP19. The amphioxus ER is structurally similar to vertebrate ERs, but differs in sequence and key residues of the ligand binding domain. Consistent with results from other laboratories, amphioxus ER did not bind radiolabeled estradiol, nor did it modulate gene expression on an estrogen-responsive element (ERE) in the presence of estradiol, 4-hydroxytamoxifen, diethylstilbestrol, bisphenol A or genistein. Interestingly, it has been shown that a related gene, the amphioxus "steroid receptor" (SR), can be activated by estrogens and that amphioxus ER can repress this activation. CYP19, ER and SR are all primarily expressed in gonadal tissue, suggesting an ancient paracrine/autocrine signaling role, but it is not yet known how their expression is regulated and, if estrogen is actually synthesized in amphioxus, whether it has a role in mediating any biological effects. Functional studies are clearly needed to link emerging bioinformatics and in vitro molecular biology results with organismal physiology to develop an understanding of the evolution of estrogen signaling. This article is part of a Special Issue entitled 'Marine organisms'.

Increased silver activity for direct propylene epoxidation via subnanometer size effects.

Production of the industrial chemical propylene oxide is energy-intensive and environmentally unfriendly. Catalysts based on bulk silver surfaces with direct propylene epoxidation by molecular oxygen have not resolved these problems because of substantial formation of carbon dioxide. We found that unpromoted, size-selected Ag3 clusters and approximately 3.5-nanometer Ag nanoparticles on alumina supports can catalyze this reaction with only a negligible amount of carbon dioxide formation and with high activity at low temperatures. Density functional calculations show that, relative to extended silver surfaces, oxidized silver trimers are more active and selective for epoxidation because of the open-shell nature of their electronic structure. The results suggest that new architectures based on ultrasmall silver particles may provide highly efficient catalysts for propylene epoxidation.