Well-resolved ion signals of intact large protein assemblies, with molecular masses extending above one million Dalton, have been detected and mass analyzed using electrospray ionization mass spectrometry, with an uncertainty in mass of <0.2%. The mass spectral data seem to reflect known solution-phase behavior of the studied protein assembly and have therefore been directly used to probe the protein assembly topology and stability as a function of ionic strength and pH.

Catalysis by thioredoxin reductase (TrxR) from Escherichia coli requires alternation between two domain arrangements. One of these conformations has been observed by X-ray crystallography (Waksman G, Krishna TSR, Williams CH Jr, Kuriyan J, 1994, J Mol Biol 236:800–816). This form of TrxR, denoted FO, permits the reaction of enzyme-bound reduced FAD with a redox-active disulfide on TrxR. As part of an investigation of conformational changes and intermediates in catalysis by TrxR, an X-ray structure of the FO form of TrxR with both the FAD and active site disulfide reduced has been determined. Reduction after crystallization resulted in significant local conformation changes. The isoalloxazine ring of the FAD cofactor, which is essentially planar in the oxidized enzyme, assumes a 34° “butterfly” bend about the N(5)–N(10) axis in reduced TrxR. Theoretical calculations reported by others predict ring bending of 15–28° for reduced isoalloxazines protonated at N(1). The large bending in reduced TrxR is attributed in part to steric interactions between the isoalloxazine ring and the sulfur of Cys138, formed by reduction of the active site disulfide, and is accompanied by changes in the positions and interactions of several of the ribityl side-chain atoms of FAD. The bending angle in reduced TrxR is larger than that for any flavoprotein in the Protein Data Bank. Distributions of bending angles in published oxidized and reduced flavoenzyme structures are different from those found in studies of free flavins, indicating that the protein environment has a significant effect on bending.

Production of folded and biologically active protein from Escherichia coli derived inclusion bodies can only be accomplished if a scheme exists for in vitro naturation. Motivated by the need for a rapid and statistically meaningful method of determining and evaluating protein folding conditions, we have designed a new fractional factorial protein folding screen. The screen includes 12 factors shown by previous experiments to enhance protein folding and it incorporates the 12 factors into 16 different folding conditions. By examining a 1/256th fraction of the full factorial, multiple folding conditions were determined for the ligand binding domains from glutamate and kainate receptors, and for lysozyme and carbonic anhydrase B. The impact of each factor on the formation of biologically active material was estimated by calculating factor main effects. Factors and corresponding levels such as pH (8.5) and l-arginine (0.5 M) consistently had a positive effect on protein folding, whereas detergent (0.3 mM lauryl maltoside) and nonpolar additive (0.4 M sucrose) were detrimental to the folding of these four proteins. One of the 16 conditions yielded the most folded material for three out of the four proteins. Our results suggest that this protein folding screen will be generally useful in determining whether other proteins will fold in vitro and, if so, what factors are important. Furthermore, fractional factorial folding screens are well suited to the evaluation of previously untested factors on protein folding.

L6, IL-TMP, and TM4SF5 are cell surface proteins predicted to have four transmembrane domains. Previous sequence analysis led to their assignment as members of the tetraspanin superfamily. In this paper, we identify a new sequence (L6D) that is strikingly similar to L6, IL-TMP, and TM4SF5. Analyses of these four sequences indicate that they are not significantly related to genuine tetraspanins, but instead constitute their own L6 superfamily.

Sequential 1H-NMR assignments of mouse [Cd7]-metallothionein-1 (MT1) have been carried out by standard homonuclear NMR methods and the use of an accordion–heteronuclear multiple quantum correlation (HMQC) experiment for establishing the metal, 113Cd2+, to cysteine connectivities. The three-dimensional structure was then calculated using the distance constraints from two-dimensional nuclear Overhauser effect (NOE) spectroscopy spectra and the Cys–Cd connectivities as input for a distance geometry-dynamical simulated annealing protocol in X-PLOR 3.851. Similar to the mammalian MT2 isoforms, the homologous primary structure of MT1 suggested two separate domains, each containing one metal cluster. Because there were no interdomain constraints, the structure calculation for the N-terminal β- and the C-terminal α-domain were carried out separately. The structures are based on 409 NMR constraints, consisting of 381 NOEs and 28 cysteine–metal connectivities. The only elements of regular secondary structure found were two short stretches of 310 helices along with some half-turns in the α-domain. Structural comparison with rat liver MT2 showed high similarity, with the β-domain structure in mouse MT1 showing evidence of increased flexibility compared to the same domain in MT2. The latter was reflected by the presence of fewer interresidue NOEs, no slowly exchanging backbone amide protons, and enhanced cadmium–cadmium exchange rates found in the β-domain of MT1.

A neural network has been used to predict both the location and the type of β-turns in a set of 300 nonhomologous protein domains. A substantial improvement in prediction accuracy compared with previous methods has been achieved by incorporating secondary structure information in the input data. The total percentage of residues correctly classified as β-turn or not-β-turn is around 75% with predicted secondary structure information. More significantly, the method gives a Matthews correlation coefficient (MCC) of around 0.35, compared with a typical MCC of around 0.20 using other β-turn prediction methods. Our method also distinguishes the two most numerous and well-defined types of β-turn, types I and II, with a significant level of accuracy (MCCs 0.22 and 0.26, respectively).

Collectins are animal calcium dependent lectins that target the carbohydrate structures on invading pathogens, resulting in the agglutination and enhanced clearance of the microorganism. These proteins form trimers that may assemble into larger oligomers. Each polypeptide chain consists of four regions: a relatively short N-terminal region, a collagen like region, an α-helical coiled-coil, and the lectin domain. Only primary structure data are available for the N-terminal region, while the most important features of the collagen-like region can be derived from its homology with collagen. The structures of the α-helical coiled-coil and the lectin domain are known from crystallographic studies of mannan binding protein (MBP) and lung surfactant protein D (SP-D). Carbohydrate binding has been structurally characterized in several complexes between MBP and carbohydrate; all indicate that the major interaction between carbohydrate and collectin is the binding of two adjacent carbohydrate hydroxyl group to a collectin calcium ion. In addition, these hydroxyl groups hydrogen bond to some of the calcium amino acid ligands. While each collectin trimer contains three such carbohydrate binding sites, deviation from the overall threefold symmetry has been demonstrated for SP-D, which may influence its binding properties. The protein surface between the three binding sites is positively charged in both MBP and SP-D.

We have identified a ∼140 amino acid domain that is shared by a variety of proteins in budding and fission yeast, nematode, rat, mouse, frog, oat, and man. Typically, this domain is located within 20 residues of the N-terminus of the various proteins. The percent identity among the domains in the 12 proteins ranges from 42 to 93%, with 16 absolutely conserved residues: N-x11–13-V-x2-A-T-x34–36-R-x7–8-W-R-x3-K-x12-G-x-E-x15-L-x11–12-D-x-G-R-x11-D-x7-R. Even though these proteins share little beyond their segment of homology, data are emerging that several of the proteins are involved in endocytosis and or regulation of cytoskeletal organization. We have named this protein segment the ENTH domain, for Epsin N-terminal Homology domain, and hypothesize that it is a candidate for binding specific ligands and/or enzymatic activity in the cell.

The topology of a protein structure is a highly simplified description of its fold including only the sequence of secondary structure elements, and their relative spatial positions and approximate orientations. This information can be embodied in a two-dimensional diagram of protein topology, called a TOPS cartoon. These cartoons are useful for the understanding of particular folds and making comparisons between folds. Here we describe a new algorithm for the production of TOPS cartoons, which is more robust than those previously available, and has a much higher success rate. This algorithm has been used to produce a database of protein topology cartoons that covers most of the data bank of known protein structures.

Alanine scanning mutagenesis of the HyHEL-10 paratope of the HyHEL-10/HEWL complex demonstrates that the energetically important side chains (hot spots) of both partners are in contact. A plot of ΔΔGHyHEL-10_mutant vs. ΔΔGHEWL_mutant for the five of six interacting side-chain hydrogen bonds is linear (Slope = 1). Only 3 of the 13 residues in the HEWL epitope contribute >4 kcal/mol to the free energy of formation of the complex when replaced by alanine, but 6 of the 12 HyHEL-10 paratope amino acids do. Double mutant cycle analysis of the single crystallographically identified salt bridge, D32H/K97, shows that there is a significant energetic penalty when either partner is replaced with a neutral side-chain amino acid, but the D32HN/K97M complex is as stable as the WT. The role of the disproportionately high number of Tyr residues in the CDR was evaluated by comparing the ΔΔG values of the Tyr → Phe vs. the corresponding Tyr → Ala mutations. The nonpolar contacts in the light chain contribute only about one-half of the total ΔΔG observed for the Tyr → Ala mutation, while they are significantly more important in the heavy chain. Replacement of the N31L/K96 hydrogen bond with a salt bridge, N31DL/K96, destabilizes the complex by 1.4 kcal/mol. The free energy of interaction, ΔΔGint, obtained from double mutant cycle analysis showed that ΔΔGint for any complex for which the HEWL residue probed is a major immunodeterminant is very close to the loss of free energy observed for the HyHEL-10 single mutant. Error propagation analysis of double mutant cycles shows that data of atypically high precision are required to use this method meaningfully, except where large ΔΔG values are analyzed.

Fructose 1,6-bisphosphate aldolase catalyzes the reversible cleavage of fructose 1,6-bisphosphate and fructose 1-phosphate to dihydroxyacetone phosphate and either glyceraldehyde 3-phosphate or glyceraldehyde, respectively. Catalysis involves the formation of a Schiff's base intermediate formed at the ε-amino group of Lys229. The existing apo-enzyme structure was refined using the crystallographic free-R-factor and maximum likelihood methods that have been shown to give improved structural results that are less subject to model bias. Crystals were also soaked with the natural substrate (fructose 1,6-bisphosphate), and the crystal structure of this complex has been determined to 2.8 Å. The apo structure differs from the previous Brookhaven-deposited structure (1ald) in the flexible C-terminal region. This is also the region where the native and complex structures exhibit differences. The conformational changes between native and complex structure are not large, but the observed complex does not involve the full formation of the Schiff's base intermediate, and suggests a preliminary hydrogen-bonded Michaelis complex before the formation of the covalent complex.

Several recent publications illustrated advantages of using sequence profiles in recognizing distant homologies between proteins. At the same time, the practical usefulness of distant homology recognition depends not only on the sensitivity of the algorithm, but also on the quality of the alignment between a prediction target and the template from the database of known proteins. Here, we study this question for several supersensitive protein algorithms that were previously compared in their recognition sensitivity (Rychlewski et al., 2000). A database of protein pairs with similar structures, but low sequence similarity is used to rate the alignments obtained with several different methods, which included sequence–sequence, sequence–profile, and profile–profile alignment methods. We show that incorporation of evolutionary information encoded in sequence profiles into alignment calculation methods significantly increases the alignment accuracy, bringing them closer to the alignments obtained from structure comparison.

In general, alignment quality is correlated with recognition and alignment score significance. For every alignment method, alignments with statistically significant scores correlate with both correct structural templates and good quality alignments. At the same time, average alignment lengths differ in various methods, making the comparison between them difficult. For instance, the alignments obtained by FFAS, the profile–profile alignment algorithm developed in our group are always longer that the alignments obtained with the PSI-BLAST algorithms. To address this problem, we develop methods to truncate or extend alignments to cover a specified percentage of protein lengths. In most cases, the elongation of the alignment by profile–profile methods is reasonable, adding fragments of similar structure. The examples of erroneous alignment are examined and it is shown that they can be identified based on the model quality.

The X-ray structure of chitinase from the fungal pathogen Coccidioides immitis has been solved to 2.2 Å resolution. Like other members of the class 18 hydrolase family, this 427 residue protein is an eight-stranded β/α-barrel. Although lacking an N-terminal chitin anchoring domain, the enzyme closely resembles the chitinase from Serratia marcescens. Among the conserved features are three cis peptide bonds, all involving conserved active site residues. The active site is formed from conserved residues such as tryptophans 47, 131, 315, 378, tyrosines 239 and 293, and arginines 52 and 295. Glu171 is the catalytic acid in the hydrolytic mechanism; it was mutated to a Gln, and activity was abolished. Allosamidin is a substrate analog that strongly inhibits the class 18 enzymes. Its binding to the chitinase hevamine has been observed, and we used conserved structural features of the two enzymes to predict the inhibitors binding to the fungal enzyme.

Conformational free energy calculations have been carried out for proline-containing alanine-based pentadecapeptides with the sequence Ac-(Ala)n-Pro-(Ala)m-NHMe, where n + m = 14, to figure out the positional preference of proline in α-helices. The relative free energy of each peptide was calculated by subtracting the free energy of the extended conformation from that of the α-helical one, which is used here as a measure of preference. The highest propensity is found for the peptide with proline at the N-terminus (i.e., Ncap + 1 position), and the next propensities are found at Ncap, N′ (Ncap − 1), and C′ (Ccap + 1) positions. These computed results are reasonably consistent with the positional propensities estimated from X-ray structures of proteins. The breaking in hydrogen bonds around proline is found to play a role in destabilizing α-helical conformations, which, however, provides the favored hydration of the corresponding N–H and C=O groups. The highest preference of proline at the beginning of α-helix appears to be due to the favored electrostatic and nonbonded energies between two residues preceding proline and the intrinsic stability of α-helical conformation of the proline residue itself as well as no disturbance in hydrogen bonds of α-helix by proline. The average free energy change for the substitution of Ala by Pro in a α-helix is computed to be 4.6 kcal/mol, which is in good agreement with the experimental value of ∼4 kcal/mol estimated for an oligopeptide dimer and proteins of barnase and T4 lysozyme.

Because of the simplicity and regularity of the α-helical coiled coil relative to other structural motifs, it can be conveniently used to clarify the molecular interactions responsible for protein folding and stability. Here we describe the de novo design and characterization of a two heptad-repeat peptide stabilized by a complex network of inter- and intrahelical salt bridges. Circular dichroism spectroscopy and analytical ultracentrifugation show that this peptide is highly α-helical and 100% dimeric under physiological buffer conditions. Interestingly, the peptide was shown to switch its oligomerization state from a dimer to a trimer upon increasing ionic strength. The correctness of the rational design principles used here is supported by details of the atomic structure of the peptide deduced from X-ray crystallography. The structure of the peptide shows that it is not a molten globule but assumes a unique, native-like conformation. This de novo peptide thus represents an attractive model system for the design of a molecular recognition system.

Analysis of thermal melting curves represents one important approach for evaluating protein stability and the consequences of amino acid substitution on protein structure. By use of the van't Hoff relationship, the differential melting curve can be robustly fit to only three parameters, two of which are the underlying physical constants of melting temperature (Tm) and van't Hoff enthalpy (ΔHvH). Calculated Tm and ΔHvH values are insensitive to the choice of pre- and post-transition baselines. Consequently, the method accurately computes Tm and ΔHvH for extremely truncated data sets, in the complete absence of baseline information, and for proteins with low melting temperatures, where the traditional direct approach routinely fails. Moreover, agreement between ΔHvH values obtained using points derived from pre- vs. post-transition data provide an independent method for detecting some classes of non-two-state transitions. Finally, fitting of the differential denaturation curve should prove useful for analysis of abbreviated data sets obtained from high throughput array analysis of protein stability.

We develop a protocol for estimating the free energy difference between different conformations of the same polypeptide chain. The conformational free energy evaluation combines the CHARMM force field with a continuum treatment of the solvent. In almost all cases studied, experimentally determined structures are predicted to be more stable than misfolded “decoys.” This is due in part to the fact that the Coulomb energy of the native protein is consistently lower than that of the decoys. The solvation free energy generally favors the decoys, although the total electrostatic free energy (sum of Coulomb and solvation terms) favors the native structure. The behavior of the solvation free energy is somewhat counterintuitive and, surprisingly, is not correlated with differences in the burial of polar area between native structures and decoys. Rather, the effect is due to a more favorable charge distribution in the native protein, which, as is discussed, will tend to decrease its interaction with the solvent. Our results thus suggest, in keeping with a number of recent studies, that electrostatic interactions may play an important role in determining the native topology of a folded protein. On this basis, a simplified scoring function is derived that combines a Coulomb term with a hydrophobic contact term. This function performs as well as the more complete free energy evaluation in distinguishing the native structure from misfolded decoys. Its computational efficiency suggests that it can be used in protein structure prediction applications, and that it provides a physically well-defined alternative to statistically derived scoring functions.

Structural genomics projects aim to provide an experimental structure or a good model for every protein in all completed genomes. Most of the experimental work for these projects will be directed toward proteins whose fold cannot be readily recognized by simple sequence comparison with proteins of known structure. Based on the history of proteins classified in the SCOP structure database, we expect that only about a quarter of the early structural genomics targets will have a new fold. Among the remaining ones, about half are likely to be evolutionarily related to proteins of known structure, even though the homology could not be readily detected by sequence analysis.

We have identified a similarity between the apical domain of the human transferrin receptor and several other protein families. This domain is found associated with two different families of peptidases. Therefore, we term it the PA domain for protease-associated domain. The PA domain is found inserted within a loop of the peptidase domain of family M8/M33 zinc peptidases. The PA domain is also found in a vacuolar sorting receptor and a ring finger protein of unknown function that may be a cell surface receptor. The PA domain may mediate substrate determination of peptidases or form protein–protein interactions.

To investigate the cooperativity of hydrophobic interactions, the potential of mean force of two- and three-molecule methane clusters in water was determined by molecular dynamics simulations using two methods: umbrella-sampling with the weighted histogram analysis method and thermodynamic integration. Two water models, TIP3P and TIP4P, were used, while each methane molecule was modeled as a united atom. It was found that the three-body potential of mean force is not additive, i.e., it cannot be calculated as a sum of two-body contributions, but requires an additional three-body cooperative term. The cooperative term, which amounts to only about 10% of the total hydrophobic association free energy, was found to increase the strength of hydrophobic association; this finding differs from the results of earlier Monte Carlo studies with the free energy perturbation method of Rank and Baker (1997). As in the work of Rank and Baker, the solvent contribution to the potential of mean force was found to be well approximated by the molecular surface of two methane molecules. Moreover, we also found that the cooperative term is well represented by the difference between the molecular surface of the three-methane cluster and those of all three pairs of methane molecules. In addition, it was found that, while there is a cooperative contribution to the hydrophobic association free energy albeit a small one, the errors associated with the use of pairwise potentials are comparable to or larger than this contribution.