Crystal structure and mutational analysis of Ca2+-independent type II antifreeze protein from longsnout poacher, Brachyopsis rostratus

We recently found that longsnout poacher (Brachyosis rostratus) produces a Ca²⁺-independent type II antifreeze protein (lpAFP) and succeeded in expressing recombinant lpAFP using Phichia pastoris. Here, we report, for the first time, the X-ray crystal structure of lpAFP at 1.34 Å resolution. The lpAFP structure displayed a relatively planar surface, which encompasses two loop regions (Cys86-Lys89 and Asn91-Cys97) and a short β-strand (Trp109-Leu112) with three unstructured segments (Gly57-Ile58, Ala103-Ala104, and Pro113-His118). Electrostatic calculation of the protein surface showed that the relatively planar surface was divided roughly into a hydrophobic area (composed of the three unstructured segments lacking secondary structure) and a hydrophilic area (composed of the loops and β-strand). Site-directed mutation of Ile58 with Phe at the center of the hydrophobic area decreased activity significantly, whereas mutation of Leu112 with Phe at an intermediate area between the hydrophobic and hydrophilic areas retained complete activity. In the hydrophilic area, a peptide-swap mutant in the loops retained 60% activity despite simultaneous mutations of eight residues. We conclude that the epicenter of the ice-binding site of lpAFP is the hydrophobic region, which is centered by Ile58, in the relatively planar surface. We built an ice-binding model for lpAFP on the basis of a lattice match of ice and constrained water oxygen atoms surrounding the hydrophobic area in the lpAFP structure. The model in which lpAFP has been docked to a secondary prism (2-1-10) plane, which is different from the one determined for Ca²⁺-independent type II AFP from sea raven (11-21), appears to explain the results of the mutagenesis analysis.     

Multiple sites in αB-crystallin modulate its interactions with desmin filaments assembled in vitro

The β3- and β8-strands and C-terminal residues 155-165 of αB-crystallin were identified by pin arrays as interaction sites for various client proteins including the intermediate filament protein desmin. Here we present data using 5 well-characterised αB-crystallin protein constructs with substituted β3- and β8-strands and with the C-terminal residues 155-165 deleted to demonstrate the importance of these sequences to the interaction of αB-crystallin with desmin filaments. We used electron microscopy of negatively stained samples to visualize increased interactions followed by sedimentation assays to quantify our observations. A low-speed sedimentation assay measured the ability of αB-crystallin to prevent the self-association of desmin filaments. A high-speed sedimentation assay measured αB-crystallin cosedimentation with desmin filaments. Swapping the β8-strand of αB-crystallin or deleting residues 155-165 increased the cosedimentation of αB-crystallin with desmin filaments, but this coincided with increased filament-filament interactions. In contrast, substitution of the β3-strand with the equivalent αA-crystallin sequences improved the ability of αB-crystallin to prevent desmin filament-filament interactions with no significant change in its cosedimentation properties. These data suggest that all three sequences (β3-strand, β8-strand and C-terminal residues 155-165) contribute to the interaction of αB-crystallin with desmin filaments. The data also suggest that the cosedimentation of αB-crystallin with desmin filaments does not necessarily correlate with preventing desmin filament-filament interactions. This important observation is relevant not only to the formation of the protein aggregates that contain both desmin and αB-crystallin and typify desmin related myopathies, but also to the interaction of αB-crystallin with other filamentous protein polymers.     

Denatured-state energy landscapes of a protein structural database reveal the energetic determinants of a framework model for folding

Position-specific denatured-state thermodynamics were determined for a database of human proteins by use of an ensemble-based model of protein structure. The results of modeling denatured protein in this manner reveal important sequence-dependent thermodynamic properties in the denatured ensembles as well as fundamental differences between the denatured and native ensembles in overall thermodynamic character. The generality and robustness of these results were validated by performing fold-recognition experiments, whereby sequences were matched with their respective folds based on amino acid propensities for the different energetic environments in the protein, as determined through cluster analysis. Correlation analysis between structure and energetic information revealed that sequence segments destined for β-sheet in the final native fold are energetically more predisposed to a broader repertoire of states than are sequence segments destined for α-helix. These results suggest that within the subensemble of mostly unstructured states, the energy landscapes are dominated by states in which parts of helices adopt structure, whereas structure formation for sequences destined for β-strand is far less probable. These results support a framework model of folding, which suggests that, in general, the denatured state has evolutionarily evolved to avoid low-energy conformations in sequences that ultimately adopt β-strand. Instead, the denatured state evolved so that sequence segments that ultimately adopt α-helix and coil will have a high intrinsic structure formation capability, thus serving as potential nucleation sites.     

Studies on the rules of β-strand alignment in a protein β-sheet structure

To further disclose the underlying mechanisms of protein β-sheet formation, studies were made on the rules of β-strands alignment forming β-sheet structure using statistical and machine learning approaches. Firstly, statistical analysis was performed on the sum of β-strands between each β-strand pairs in protein sequences. The results showed a propensity of near-neighbor pairing (or called “first come first pair”) in the β-strand pairs. Secondly, based on the same dataset, the pairwise cross-combinations of real β-strand pairs and four pseudo-β-strand contained pairs were classified by support vector machine (SVM). A novel feature extracting approach was designed for classification using the average amino acid pairing encoding matrix (APEM). Analytical results of the classification indicated that a segment of β-strand had the ability to distinguish β-strands from segments of α-helix and coil. However, the result also showed that a β-strand was not strongly conserved to choose its real partner from all the alternative β-strand partners, which was corresponding with the ordination results of the statistical analysis each other. Thus, the rules of “first come first pair” propensity and the non-conservative ability to choose real partner, were possible important factors affecting the β-strands alignment forming β-sheet structures.     

Predicted structure for aldolase.

Recent chromatographic and absorbance spectral measurements using the dye Cibacron blue F3GA (Stellwagen et al., 1975) have indicated that the substrate-binding site of fructose diphosphate aldolase is constructed by a supersecondary structural array closely resembling the NAD-domain commonly found in a variety of glycolytic enzymes. Analysis of the amino acid sequence of rabbit muscle aldolase according to the procedure of Chou &; Fasman (1974) predicts the occurrence of alternating β-strand and α-helical forming segments in the sequence region involving residues 147 to 299. Comparison of the sequence of residues 146 to 300 in aldolase with the sequence of residues 22 to 164 in dogfish lactate dehydrogenase which form its NAD-domain, suggests that the two sequence regions are related genetically. It is proposed that the locus of an NAD-domain in the structure of a protein can be predicted by sequence analysis provided that the protein specifically binds Cibacron blue F3GA.     

Backbone 1H, 13C and 15N resonance assignments of an intrinsically unstructured βγ-crystallin from Hahella chejuensis

The sequence specific backbone ¹H, ¹³C and ¹⁵N resonance assignments of an intrinsically unstructured βγ-crystallin from Hahella chejuensis are reported. The secondary structure chracterization of the unstructured protein reveals that large fraction of residues exhibits β-strand propensity, as in the case of the Ca²⁺-bound structured protein.     

Prediction of the structure of the replication initiator protein DnaA

The secondary structure of DnaA protein and its interaction with DNA and ribonucleotides has been predicted using biochemical, biophysical techniques, and prediction methods based on multiple-sequence alignment and neural networks. The core of all proteins from the DnaA family consists of an “open twisted α/β structure,” containing five α-helices alternating with five β-strands. In our proposed structural model the interior of the core is formed by a parallel β-sheet, whereas the α-helices are arranged on the surface of the core. The ATP-binding motif is located within the core, in a loop region following the first β-strand. The N-terminal domain (80 aa) is composed of two α-helices, the first of which contains a potential leucine zipper motif for mediating protein-protein interaction, followed by a β-strand and an additional α-helix. The N-terminal domain and the α/β core region of DnaA are connected by a variable loop (45–70 aa); major parts of the loop region can be deleted without loss of protein activity. The C-terminal DNA-binding domain (94 aa) is mostly α-helical and contains a potential helix-loop-helix motif. DnaA protein does not dimerize in solution; instead, the two longest C-terminal α-helices could interact with each other, forming an internal “coiled coil” and exposing highly basic residues of a small loop region on the surface, probably responsible for DNA backbone contacts. © 1997 Wiley-Liss Inc.     

The Cancer Mutation D83V Induces an α-Helix to β-Strand Conformation Switch in MEF2B

MEF2B is a major target of somatic mutations in non-Hodgkin lymphoma. Most of these mutations are non-synonymous substitutions of surface residues in the MADS-box/MEF2 domain. Among them, D83V is the most frequent mutation found in tumor cells. The link between this hotspot mutation and cancer is not well understood. Here we show that the D83V mutation induces a dramatic α-helix to β-strand switch in the MEF2 domain. Located in an α-helix region rich in β-branched residues, the D83V mutation not only removes the extensive helix stabilization interactions but also introduces an additional β-branched residue that further shifts the conformation equilibrium from α-helix to β-strand. Cross-database analyses of cancer mutations and chameleon sequences revealed a number of well-known cancer targets harboring β-strand favoring mutations in chameleon α-helices, suggesting a commonality of such conformational switch in certain cancers and a new factor to consider when stratifying the rapidly expanding cancer mutation data.     

Solid state NMR chemical shift assignment and conformational analysis of a cellulose binding protein facilitated by optimized glycerol enrichment

Magic-angle spinning solid-state NMR has been applied to study CBM3b–Cbh9A (CBM3b), a cellulose binding module protein belonging to family 3b. It is a 146-residue protein having a unique nine-stranded β-sandwich fold, in which 35 % of the structure is in a β-sheet conformation and the remainder of the protein is composed of loops and unstructured regions. Yet, the protein can be crystalized and it forms elongated needles. Close to complete chemical shift assignment of the protein was obtained by combining two- and three-dimensional experiments using a fully labeled sample and a glycerol-labeled sample. The use of an optimized protocol for glycerol-based sparse labeling reduces sample preparation costs and facilitates the assignment of the large number of aromatic signals in this protein. Conformational analysis shows good correlation between the NMR-predicted secondary structure and the reported X-ray crystal structure, in particular in the structured regions. Residues which show high B-factor values are situated mainly in unstructured regions, and are missing in our spectra indicating conformational flexibility rather than heterogeneity. Interestingly, long-range contacts, which could be clearly detected for tyrosine residues, could not be observed for aromatic phenylalanine residues pointing into the hydrophobic core, suggesting possible high ring mobility. These studies will allow us to further investigate the cellulose-bound form of CBM proteins.     

Sequence Determinants for Amyloid Fibrillogenesis of Human alpha-Synuclein

Parkinson's disease (PD) and dementia with Lewy bodies (DLB) are characterized by the presence of filamentous inclusions in nerve cells. These filaments are amyloid fibrils that are made of the protein α-synuclein, which is genetically linked to rare cases of PD and DLB. β-Synuclein, which shares 60% identity with α-synuclein, is not found in the inclusions. Furthermore, while recombinant α-synuclein readily assembles into amyloid fibrils, β-synuclein fails to do so. It has been suggested that this may be due to the lack in β-synuclein of a hydrophobic region that spans residues 73-83 of α-synuclein. Here, fibril assembly of recombinant human α-synuclein, α-synuclein deletion mutants, β-synuclein and β/α-synuclein chimeras was assayed quantitatively by thioflavin T fluorescence and semi-quantitatively by transmission electron microscopy. Deletion of residues 73-83 from α-synuclein did not abolish filament formation. Furthermore, a chimera of β-synuclein with α-synuclein(73-83) inserted was significantly less fibrillogenic than wild-type α-synuclein. These findings, together with results obtained using a number of recombinant synucleins, showed a correlation between fibrillogenesis and mean β-strand propensity, hydrophilicity and charge of the amino acid sequences. The combination of these simple physicochemical properties with a previously described calculation of β-strand contiguity allowed us to design mutations that changed the fibrillogenic propensity of α-synuclein in predictable ways.     

A Molecular Dynamics Study of Human Defensins HBD-1 and HNP-3 in Water

Abstract

Mammalian defensins are crucial components of the innate immune system. They are characterized by three disulfide bridges and exhibit broad spectrum antibacterial activity. The spacing between the cysteines and disulfide connectivities in the two classes of defensins, the α- and β-forms, are different. The structural motif of 3 β-strands appears to be conserved in α and β-defensins despite differences in disulfide connectivities and spacing between cysteines. In this study, Molecular Dynamics Simulations (MDS) have been carried out to study the conformational behavior of α- and β-defensins with and without disulfide bridges. Our results indicate that β-strands in the C-terminal region of HBD-1 and HNP-3 do not unfold during the course of MDS. The segment adopting α-helix in HBD-1 unfolds early during the simulations. The backbone hydrogen bonds in HBD-1 and HNP-3 are broken during MDS. When the disulfide bonds are absent, the N-terminal β-strand unfolds by 20 ns but β-strands are observed in the C-terminal region of HNP-3. HBD-1, without disulfide bridges, unfolds to a greater extent during the course of the MDS. Examination of distances between sulfur atoms of cysteines without disulfide bridges during the simulations indicate that there is no specific preference for native disulfide bridges, which could be the reason for the experimental observation of non-native disulfide bridge formation during chemical synthesis of human α- and β-defensins. Since defensins with non-native disulfide bridges are biologically active, the exact three dimensional structures observed for native HBD-1 and HNP-3 does not appear to be essential for exhibiting antibacterial activity.     

Nonfunctional Missense Mutants in Two Well Characterized Cytosolic Enzymes Reveal Important Information About Protein Structure and Function

The isolation and characterization of 42 unique nonfunctional missense mutants in the bacterial cytosolic β-galactosidase and catechol 2,3-dioxygenase enzymes allowed us to examine some of the basic general trends regarding protein structure and function. A total of 6 out of the 42, or 14.29% of the missense mutants were in α-helices, 17 out of the 42, or 40.48%, of the missense mutants were in β-sheets and 19 out of the 42, or 45.24% of the missense mutants were in unstructured coil, turn or loop regions. While α-helices and β-sheets are undeniably important in protein structure, our results clearly indicate that the unstructured regions are just as important. A total of 21 out of the 42, or 50.00% of the missense mutants caused either amino acids located on the surface of the protein to shift from hydrophilic to hydrophobic or buried amino acids to shift from hydrophobic to hydrophilic and resulted in drastic changes in hydropathy that would not be preferable. There was generally good consensus amongst the widely used algorithms, Chou–Fasman, GOR, Qian–Sejnowski, JPred, PSIPRED, Porter and SPIDER, in their ability to predict the presence of the secondary structures that were affected by the missense mutants and most of the algorithms predicted that the majority of the 42 inactive missense mutants would impact the α-helical and β-sheet secondary structures or the unstructured coil, turn or loop regions that they altered.     

Conformational preferences of non-polar amino acid residues: an additional factor in amyloid formation

Amyloid consists of β-sheet polymers and is associated with disease and with functional assemblies. Amyloid-forming proteins differ widely in native structures and sequences. We describe here how conformational preferences of non-polar amino acid residues can affect amyloid formation. The most non-polar residues promote either β-strands (Val, Ile, Phe, and Cys, VIFC) or α-helices (Leu, Ala, and Met, LAM), while the most polar residues promote only α-helices. For 12 proteins associated with disease, the localizations of the amyloid core regions are known. Eleven of these contain segments that are biased for VIFC, but essentially lack segments that are biased for LAM. For the amyloid β-peptide associated with Alzheimer’s disease and an amyloidogenic fragment of the prion protein, observed effects of mutations support that VIFC bias favors formation of β-sheet aggregates and amyloid, while LAM bias prevents it. VIFC and LAM profiles combine information on secondary structure propensities and polarity, and add a simple criterion to the prediction of amyloidogenic regions.     

A new approach to secondary structure evaluation: Secondary structure prediction of porcine adenylate kinase and yeast guanylate kinase by CD spectroscopy of overlapping synthetic peptide segments

A new approach for evaluating the secondary structure of proteins by CD spectroscopy of overlapping peptide segments is applied to porcine adenylate kinase (AK1) and yeast guanylate kinase (GK3). One hundred seventy-six peptide segments of a length of 15 residues, overlapping by 13 residues and covering the complete sequences of AK1 and GK3, were synthesized in order to evaluate their secondary structure composition by CD spectroscopy. The peptides were prepared by solid phase multiple peptide synthesis method using the 9-fluorenylmethoxycarbonyl/tert-butyl strategy. The individual peptide secondary structures were studied with CD spectroscopy in a mixture of 30% trifluoroethanol in phosphate buffer (pH 7) and subsequently compared with x-ray data of AK1 and GK3. Peptide segments that cover α-helical regions of the AK1 or GK3 sequence mainly showed CD spectra with increasing and decreasing Cotton effects that were typical for appearing and disappearing α-helical structures. For segments with dominating β-sheet conformation, however, the application of this method is limited due to the stability and clustering of β-sheet segments in solution and due to the difficult interpretation of random-coiled superimposed β-sheet CD signals. Nevertheless, the results of this method especially for α-helical segments are very impressive. All α-helical and 71% of the β-sheet containing regions of the AK1 and GK3 could be identified. Moreover, it was shown that CD spectra of consecutive peptide content reveal the appearance and disappearance of α-helical secondary structure elements and help localizing them on the sequence string. © 1997 John Wiley & Sons, Inc. Biopoly 41: 213–231, 1997     

Cooperativity among short amyloid stretches in long amyloidogenic sequences

Amyloid fibrillar aggregates of polypeptides are associated with many neurodegenerative diseases. Short peptide segments in protein sequences may trigger aggregation. Identifying these stretches and examining their behavior in longer protein segments is critical for understanding these diseases and obtaining potential therapies. In this study, we combined machine learning and structure-based energy evaluation to examine and predict amyloidogenic segments. Our feature selection method discovered that windows consisting of long amino acid segments of ~30 residues, instead of the commonly used short hexapeptides, provided the highest accuracy. Weighted contributions of an amino acid at each position in a 27 residue window revealed three cooperative regions of short stretch, resemble the β-strand-turn-β-strand motif in A-βpeptide amyloid and β-solenoid structure of HET-s(218-289) prion (C). Using an in-house energy evaluation algorithm, the interaction energy between two short stretches in long segment is computed and incorporated as an additional feature. The algorithm successfully predicted and classified amyloid segments with an overall accuracy of 75%. Our study revealed that genome-wide amyloid segments are not only dependent on short high propensity stretches, but also on nearby residues.     

Structure–Critical Distribution of Aromatic Residues in the Fibronectin Type III Protein Family

Over a thousand individual Fibronectin type III (FnIII) domain sequences, extracted from more than 60 different FnIII-dependent protein super-structures, were downloaded from curated database resources. Three regions of extreme sequence conservation within the well-characterized FnIII β-sandwich structure were respectively defined by near absolute conservation of a tryptophan (Trp) in β-strand-B, tyrosines (Tyr) in both β-strand-C and β-strand-F, and a leucine (Leu) residue in the unstructured region immediately preceding β-strand-F. Employing these four conserved landmarks, the entire FnIII sequence dataset was vertically registered to align the three conserved regions, and the cumulative distribution of all other amino acid functionality was determined and plotted relative to these landmark residues. Conserved aromatic sites were each found to be flanked by aliphatic residues that assure localization of these sites to the inaccessible hydrophobic interface between major sheet structures. Mapping the location of conserved aromatic sites in numerous PDB structures demonstrated the consistent pair-wise co-localization of the indole side-chain of the conserved strand-B Trp site to within 0.35 nm of the phenolic side-chain of the strand-C Tyr site located 8–14 amino acids distal. Likewise, the side-chain of the strand-F Tyr site co-localized to within 0.45 nm of the aliphatic side-chain of the conserved Leu that uniformly precedes it by six residues. While classic hydropathy-based theories would deem the “burying” of Tyr and Trp side-chains and/or their association with hydrophobic FnIII core residues thermodynamically unnecessary, alternative contributions of conserved Trp and Tyr residues, and particularly the role of the absolutely conserved tyrosine phenolic –OH in native FnIII structure–function are considered. A more global role for conserved FnIII aromaticity is also discussed in light of the aromatic conservation observed in other well-established protein families.     

Intrinsic secondary structure propensities of the amino acids,using statistical ϕ–ψ matrices: Comparison with experimental scales

Today there are several different experimental scales for the intrinsic α-helix as well as β-strand, propensities of the 20 amino acids obtained from the thermodynamic analysis of various model systems. These scales do not compare well with those extracted from statistical analysis of three-dimensional structure databases. Possible explanations for this could be the limited size of the databases used, the definitions of intrinsic propensities, or the theoretical approach. Here we report a statistical determination of α-helix and β-strand propensities derived from the analysis of a database of 279 three-dimensional structures. Contrary to what has been generally done, we have considered a particular residue as in α-helix or β-strand conformation by looking only at its dihedral angles (?–ψ matrices). Neither the identity nor the conformation of the surrounding residues in the amino acid sequence has been taken into consideration. Pseudoenergy empirical scales have been calculated from the statistical propensities. These scales agree very well with the experimental ones in relative and absolute terms. Moreover, its correlation with the average of the experimental scales for α-helix or β-strand is as good as the correlations of the individual experimental scales with the average. These results show that by using a large enough database and a proper definition for the secondary structure propensities, it is possible to obtain a scale as good as any of experimental origin. Interestingly the ?–ψ analysis of the Ramachandran plot suggests that the amino acids could have different β-strand propensities in different subregions of the β-strand area. © 1994 Wiley-Liss, Inc.     

Conformation and Trimer Association of the Transmembrane Domain of the Parainfluenza Virus Fusion Protein in Lipid Bilayers from Solid-State NMR: Insights into the Sequence Determinants of Trimer Structure and Fusion Activity

Enveloped viruses enter cells by using their fusion proteins to merge the virus lipid envelope and the cell membrane. While crystal structures of the water-soluble ectodomains of many viral fusion proteins have been determined, the structure and assembly of the C-terminal transmembrane domain (TMD) remains poorly understood. Here we use solid-state NMR to determine the backbone conformation and oligomeric structure of the TMD of the parainfluenza virus 5 fusion protein. ¹³C chemical shifts indicate that the central leucine-rich segment of the TMD is α-helical in POPC/cholesterol membranes and POPE membranes, while the Ile- and Val-rich termini shift to the β-strand conformation in the POPE membrane. Importantly, lipid mixing assays indicate that the TMD is more fusogenic in the POPE membrane than in the POPC/cholesterol membrane, indicating that the β-strand conformation is important for fusion by inducing membrane curvature. Incorporation of para-fluorinated Phe at three positions of the α-helical core allowed us to measure interhelical distances using ¹⁹F spin diffusion NMR. The data indicate that, at peptide:lipid molar ratios of ~ 1:15, the TMD forms a trimeric helical bundle with inter-helical distances of 8.2–8.4 Å for L493F and L504F and 10.5 Å for L500F. These data provide high-resolution evidence of trimer formation of a viral fusion protein TMD in phospholipid bilayers, and indicate that the parainfluenza virus 5 fusion protein TMD harbors two functions: the central α-helical core is the trimerization unit of the protein, while the two termini are responsible for inducing membrane curvature by transitioning to a β-sheet conformation.     

Models of noncoupled dinuclear copper centers in azurin

The successful modeling of metalloproteins is an important step in understanding their structure and function. Toward this goal, models of the noncoupled copper centers found in the enzymes peptidyl α-hydroxylating monooxygenase (PHM), dopamine β-monooxygenase (DBM), and nitrite reductase (NiR) were designed into the small soluble protein azurin. The models are significant because they maintain the existing type 1 (T1) copper, electron transfer site of azurin while including the second designed type 2 (T2) copper center that mimics the T2 catalytic sites in the target enzymes. UV–vis absorption and EPR spectroscopy data of the model sites are consistent with T2 centers and establish copper binding at the sites, thus modeling those found in PHM/DBM and NiR. Importantly the models’ approximate 11–13 Å separation between the T1 and T2 copper sites is comparable with the separations in the native systems. This, along with the power to tune the T1 site redox potential in azurin, allows for the future evaluation of relevant activity assays in these models.