BMC Structural Biology最新文献

HLA-DPs are class II MHC proteins mediating immune responses to many diseases. Peptides bind MHC class II proteins in the acidic environment within endosomes. Acidic pH markedly elevates association rate constants but dissociation rates are almost unchanged in the pH range 5.0 – 7.0. This pH-driven effect can be explained by the protonation/deprotonation states of Histidine, whose imidazole has a pK_a of 6.0. At pH 5.0, imidazole ring is protonated, making Histidine positively charged and very hydrophilic, while at pH 7.0 imidazole is unprotonated, making Histidine less hydrophilic. We develop here a method to predict peptide binding to the four most frequent HLA-DP proteins: DP1, DP41, DP42 and DP5, using a molecular docking protocol. Dockings to virtual combinatorial peptide libraries were performed at pH 5.0 and pH 7.0.

The X-ray structure of the peptide – HLA-DP2 protein complex was used as a starting template to model by homology the structure of the four DP proteins. The resulting models were used to produce virtual combinatorial peptide libraries constructed using the single amino acid substitution (SAAS) principle. Peptides were docked into the DP binding site using AutoDock at pH 5.0 and pH 7.0. The resulting scores were normalized and used to generate Docking Score-based Quantitative Matrices (DS-QMs). The predictive ability of these QMs was tested using an external test set of 484 known DP binders. They were also compared to existing servers for DP binding prediction. The models derived at pH 5.0 predict better than those derived at pH 7.0 and showed significantly improved predictions for three of the four DP proteins, when compared to the existing servers. They are able to recognize 50% of the known binders in the top 5% of predicted peptides.

The higher predictive ability of DS-QMs derived at pH 5.0 may be rationalised by the additional hydrogen bond formed between the backbone carbonyl oxygen belonging to the peptide position before p1 (p-1) and the protonated ε-nitrogen of His^79β. Additionally, protonated His residues are well accepted at most of the peptide binding core positions which is in a good agreement with the overall negatively charged peptide binding site of most MHC proteins.

Recent technological advances enabled high-throughput collection of Small Angle X-ray Scattering (SAXS) profiles of biological macromolecules. Thus, computational methods for integrating SAXS profiles into structural modeling are needed more than ever. Here, we review specifically the use of SAXS profiles for the structural modeling of proteins, nucleic acids, and their complexes. First, the approaches for computing theoretical SAXS profiles from structures are presented. Second, computational methods for predicting protein structures, dynamics of proteins in solution, and assembly structures are covered. Third, we discuss the use of SAXS profiles in integrative structure modeling approaches that depend simultaneously on several data types.

Dihydroxylation of tandemly linked aromatic carbons in a cis-configuration, catalyzed by multicomponent oxygenase systems known as Rieske nonheme iron oxygenase systems (ROs), often constitute the initial step of aerobic degradation pathways for various aromatic compounds. Because such RO reactions inherently govern whether downstream degradation processes occur, novel oxygenation mechanisms involving oxygenase components of ROs (RO-Os) is of great interest. Despite substantial progress in structural and physicochemical analyses, no consensus exists on the chemical steps in the catalytic cycles of ROs. Thus, determining whether conformational changes at the active site of RO-O occur by substrate and/or oxygen binding is important. Carbazole 1,9a-dioxygenase (CARDO), a RO member consists of catalytic terminal oxygenase (CARDO-O), ferredoxin (CARDO-F), and ferredoxin reductase. We have succeeded in determining the crystal structures of oxidized CARDO-O, oxidized CARDO-F, and both oxidized and reduced forms of the CARDO-O: CARDO-F binary complex.

In the present study, we determined the crystal structures of the reduced carbazole (CAR)-bound, dioxygen-bound, and both CAR- and dioxygen-bound CARDO-O: CARDO-F binary complex structures at 1.95, 1.85, and 2.00?? resolution. These structures revealed the conformational changes that occur in the catalytic cycle. Structural comparison between complex structures in each step of the catalytic mechanism provides several implications, such as the order of substrate and dioxygen bindings, the iron-dioxygen species likely being Fe(III)-(hydro)peroxo, and the creation of room for dioxygen binding and the promotion of dioxygen binding in desirable fashion by preceding substrate binding.

The RO catalytic mechanism is proposed as follows: When the Rieske cluster is reduced, substrate binding induces several conformational changes (e.g., movements of the nonheme iron and the ligand residue) that create room for oxygen binding. Dioxygen bound in a side-on fashion onto nonheme iron is activated by reduction to the peroxo state [Fe(III)-(hydro)peroxo]. This state may react directly with the bound substrate, or O–O bond cleavage may occur to generate Fe(V)-oxo-hydroxo species prior to the reaction. After producing a cis-dihydrodiol, the product is released by reducing the nonheme iron. This proposed scheme describes the catalytic cycle of ROs and provides important information for a better understanding of the mechanism.

Capping protein (CP), also known as CapZ in muscle cells and Cap32/34 in Dictyostelium discoideum, plays a major role in regulating actin filament dynamics. CP is a ubiquitously expressed heterodimer comprising an α- and β-subunit. It tightly binds to the fast growing end of actin filaments, thereby functioning as a “cap” by blocking the addition and loss of actin subunits. Vertebrates contain two somatic variants of CP, one being primarily found at the cell periphery of non-muscle tissues while the other is mainly localized at the Z-discs of skeletal muscles.

To elucidate structural and functional differences between cytoplasmic and sarcomercic CP variants, we have solved the atomic structure of Cap32/34 (32?=?β- and 34?=?α-subunit) from the cellular slime mold Dictyostelium at 2.2?? resolution and compared it to that of chicken muscle CapZ. The two homologs display a similar overall arrangement including the attached α-subunit C-terminus (α-tentacle) and the flexible β-tentacle. Nevertheless, the structures exhibit marked differences suggesting considerable structural flexibility within the α-subunit. In the α-subunit we observed a bending motion of the β-sheet region located opposite to the position of the C-terminal β-tentacle towards the antiparallel helices that interconnect the heterodimer. Recently, a two domain twisting attributed mainly to the β-subunit has been reported. At the hinge of these two domains Cap32/34 contains an elongated and highly flexible loop, which has been reported to be important for the interaction of cytoplasmic CP with actin and might contribute to the more dynamic actin-binding of cytoplasmic compared to sarcomeric CP (CapZ).

The structure of Cap32/34 from Dictyostelium discoideum allowed a detailed analysis and comparison between the cytoplasmic and sarcomeric variants of CP. Significant structural flexibility could particularly be found within the α-subunit, a loop region in the β-subunit, and the surface of the α-globule where the amino acid differences between the cytoplasmic and sarcomeric mammalian CP are located. Hence, the crystal structure of Cap32/34 raises the possibility of different binding behaviours of the CP variants toward the barbed end of actin filaments, a feature, which might have arisen from adaptation to different environments.

The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions.

We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence-based methods.

Appropriate homologous sequences are selected automatically and objectively by the index. Such sequence selection improved the performance of functional region prediction. As far as we know, this is the first approach in which spatial statistics have been applied to protein analyses. Such integration of structure and sequence information would be useful for other bioinformatics problems.

Modular polyketide synthases are multifunctional megasynthases which biosynthesize a variety of secondary metabolites using various combinations of dehydratase (DH), ketoreductase (KR) and enoyl-reductase (ER) domains. During the catalysis of various reductive steps these domains act on a substrate moiety which is covalently attached to the phosphopantetheine (P-pant) group of the holo-Acyl Carrier Protein (holo-ACP) domain, thus necessitating the formation of holo-ACP:DH and holo-ACP:KR complexes. Even though three dimensional structures are available for DH, KR and ACP domains, no structures are available for DH or KR domains in complex with ACP or substrate moieties. Since Ser of holo-ACP is covalently attached to a large phosphopantetheine group, obtaining complexes involving holo-ACP by standard protein-protein docking has been a difficult task.

We have modeled the holo-ACP:DH and holo-ACP:KR complexes for identifying specific residues on DH and KR domains which are involved in interaction with ACP, phosphopantetheine and substrate moiety. A novel combination of protein-protein and protein-ligand docking has been used to first model complexes involving apo-ACP and then dock the phosphopantetheine and substrate moieties using covalent connectivity between ACP, phosphopantetheine and substrate moiety as constraints. The holo-ACP:DH and holo-ACP:KR complexes obtained from docking have been further refined by restraint free explicit solvent MD simulations to incorporate effects of ligand and receptor flexibilities. The results from 50?ns MD simulations reveal that substrate enters into a deep tunnel in DH domain while in case of KR domain the substrate binds a shallow surface exposed cavity. Interestingly, in case of DH domain the predicted binding site overlapped with the binding site in the inhibitor bound crystal structure of FabZ, the DH domain from E.Coli FAS. In case of KR domain, the substrate binding site identified by our simulations was in proximity of the known stereo-specificity determining residues.

We have modeled the holo-ACP:DH and holo-ACP:KR complexes and identified the specific residues on DH and KR domains which are involved in interaction with ACP, phosphopantetheine and substrate moiety. Analysis of the conservation profile of binding pocket residues in homologous sequences of DH and KR domains indicated that, these results can also be extrapolated to reductive domains of other modular PKS clusters.

Tumor necrosis factors, TNF and lymphotoxin-α (LT), are cytokines that bind to two receptors, TNFR1 and TNFR2 (TNF-receptor 1 and 2) to trigger their signaling cascades. The exact mechanism of ligand-induced receptor activation is still unclear. It is generally assumed that three receptors bind to the homotrimeric ligand to trigger a signaling event. Recent evidence, though, has raised doubts if the ligand:receptor stoichiometry should indeed be 3:3 for ligand-induced cellular response. We used molecular dynamics simulations, elastic network models, as well as MM/PBSA to analyze this question.

Applying MM/PBSA methodology to different stoichiometric complexes of human LT-(TNFR1)_n=1,2,3 the free energy of binding in these complexes has been estimated by single-trajectory and separate-trajectory methods. Simulation studies rationalized the favorable binding energy in the LT-(TNFR1)₁ complex, as evaluated from single-trajectory analysis to be an outcome of the interaction of cysteine-rich domain 4 (CRD4) and the ligand. Elastic network models (ENMs) help to associate the difference in the global fluctuation of the receptors in these complexes. Functionally relevant transformation associated with these complexes reveal the difference in the dynamics of the receptor when free and in complex with LT.

MM/PBSA predicts complexes with a ligand-receptor molar ratio of 3:1 and 3:2 to be energetically favorable. The high affinity associated with LT-(TNFR1)₁ is due to the interaction between the CRD4 domain with LT. The global dynamics ascertained from ENMs have highlighted the differential dynamics of the receptor in different states.

Influenza neuraminidase (NA) is an important target for antiviral inhibitors since its active site is highly conserved such that inhibitors can be cross-reactive against multiple types and subtypes of influenza. Here, we discuss the crystal structure of neuraminidase subtype N9 complexed with a new benzoic acid based inhibitor (2) that was designed to add contacts by overpacking one side of the active site pocket. Inhibitor 2 uses benzoic acid to mimic the pyranose ring, a bis-(hydroxymethyl)-substituted 2-pyrrolidinone ring in place of the N-acetyl group of the sialic acid, and a branched aliphatic structure to fill the sialic acid C6 subsite.

Inhibitor 2 {4-[2,2-bis(hydroxymethyl)-5-oxo-pyrrolidin-1-yl]-3-[(dipropylamino)methyl)]benzoic acid} was soaked into crystals of neuraminidase of A/tern/Australia/G70c/75 (N9), and the structure refined with 1.55?? X-ray data. The benzene ring of the inhibitor tilted 8.9° compared to the previous compound (1), and the number of contacts, including hydrogen bonds, increased. However, the IC₅₀ for compound 2 remained in the low micromolar range, likely because one propyl group was disordered. In this high-resolution structure of NA isolated from virus grown in chicken eggs, we found electron density for additional sugar units on the N-linked glycans compared to previous neuraminidase structures. In particular, seven mannoses and two N-acetylglucosamines are visible in the glycan attached to Asn200. This long, branched high-mannose glycan makes significant contacts with the neighboring subunit.

We designed inhibitor 2 with an extended substituent at C4-corresponding to C6 of sialic acid-to increase the contact surface in the C6-subsite and to force the benzene ring to tilt to maximize these interactions while retaining the interactions of the carboxylate and the pyrolidinone substituents. The crystal structure at 1.55?? showed that we partially succeeded in that the ring in 2 is tilted relative to 1 and the number of contacts increased, but one hydrophobic branch makes no contacts, perhaps explaining why the IC₅₀ did not decrease. Future design efforts will include branches of unequal length so that both branches may be accommodated in the C6-subsite without conformational disorder. The high-mannose glycan attached to Asn200 makes several inter-subunit contacts and appears to stabilize the tetramer.

Most signalling and regulatory proteins participate in transient protein-protein interactions during biological processes. They usually serve as key regulators of various cellular processes and are often stable in both protein-bound and unbound forms. Availability of high-resolution structures of their unbound and bound forms provides an opportunity to understand the molecular mechanisms involved. In this work, we have addressed the question “What is the nature, extent, location and functional significance of structural changes which are associated with formation of protein-protein complexes?”

A database of 76 non-redundant sets of high resolution 3-D structures of protein-protein complexes, representing diverse functions, and corresponding unbound forms, has been used in this analysis. Structural changes associated with protein-protein complexation have been investigated using structural measures and Protein Blocks description. Our study highlights that significant structural rearrangement occurs on binding at the interface as well as at regions away from the interface to form a highly specific, stable and functional complex. Notably, predominantly unaltered interfaces interact mainly with interfaces undergoing substantial structural alterations, revealing the presence of at least one structural regulatory component in every complex.

Interestingly, about one-half of the number of complexes, comprising largely of signalling proteins, show substantial localized structural change at surfaces away from the interface. Normal mode analysis and available information on functions on some of these complexes suggests that many of these changes are allosteric. This change is largely manifest in the proteins whose interfaces are altered upon binding, implicating structural change as the possible trigger of allosteric effect. Although large-scale studies of allostery induced by small-molecule effectors are available in literature, this is, to our knowledge, the first study indicating the prevalence of allostery induced by protein effectors.

The enrichment of allosteric sites in signalling proteins, whose mutations commonly lead to diseases such as cancer, provides support for the usage of allosteric modulators in combating these diseases.

Structural genomics approaches, particularly those solving the 3D structures of many proteins with unknown functions, have increased the desire for structure-based function predictions. However, prediction of enzyme function is difficult because one member of a superfamily may catalyze a different reaction than other members, whereas members of different superfamilies can catalyze the same reaction. In addition, conformational changes, mutations or the absence of a particular catalytic residue can prevent inference of the mechanism by which catalytic residues stabilize and promote the elementary reaction. A major hurdle for alignment-based methods for prediction of function is the absence (despite its importance) of a measure of similarity of the physicochemical properties of catalytic sites. To solve this problem, the physicochemical features radially distributed around catalytic sites should be considered in addition to structural and sequence similarities.

We showed that radial distribution functions (RDFs), which are associated with the local structural and physicochemical properties of catalytic active sites, are capable of clustering oxidoreductases and transferases by function. The catalytic sites of these enzymes were also characterized using the RDFs. The RDFs provided a measure of the similarity among the catalytic sites, detecting conformational changes caused by mutation of catalytic residues. Furthermore, the RDFs reinforced the classification of enzyme functions based on conventional sequence and structural alignments.

Our results demonstrate that the application of RDFs provides advantages in the functional classification of enzymes by providing information about catalytic sites.