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At least 343 records · Page 19Linked to original sources
PubMed2004

Computational, spectroscopic, and resonant mirror biosensor analysis of the interaction of adrenodoxin with native and tryptophan-modified NADPH-adrenodoxin reductase.

In steroid hydroxylation system in adrenal cortex mitochondria, NADPH-adrenodoxin reductase (AR) and adrenodoxin (Adx) form a short electron-transport chain that transfers electrons from NADPH to cytochromes P-450 through FAD in AR and [2Fe-2S] cluster in Adx. The formation of [AR/Adx] complex is essential for the electron transfer mechanism in which previous studies suggested that AR tryptophan (Trp) residue(s) might be implicated. In this study, we modified AR Trps by N-bromosuccinimide (NBS) and studied AR binding to Adx by a resonant mirror biosensor. Chemical modification of tryptophans caused inhibition of electron transport. The modified protein (AR*) retained the native secondary structure but showed a lower affinity towards Adx with respect to AR. Activity measurements and fluorescence data indicated that one Trp residue of AR may be involved in the electron transferring activity of the protein. Computational analysis of AR and [AR/Adx] complex structures suggested that Trp193 and Trp420 are the residues with the highest probability to undergo NBS-modification. In particular, the modification of Trp420 hampers the correct reorientation of AR* molecule necessary to form the native [AR/Adx] complex that is catalytically essential for electron transfer from FAD in AR to [2Fe-2S] cluster in Adx. The data support an incorrect assembly of [AR*/Adx] complex as the cause of electron transport inhibition.

Adrenodoxin↗
PubMed2004

Backbone-backbone geometry of tertiary contacts between alpha-helices.

Knowledge about how secondary-structure elements combine together to form the tertiary structure is crucial for understanding protein folding. We have examined packing solutions for alpha-helices by performing a crystal survey of the underlying backbone-backbone inter-geometry of tertiary contacts. The information content is different from, and complementary to, the results of side-chain to side-chain crystal surveys and studies of helix-helix-crossing angles. Six geometry descriptors were recorded from each tertiary contact in nonredundant data sets of globular and transmembrane proteins. The descriptors included distances, angles, and dihedral angles that together describe completely the underlying geometry of each contact. From the results it is possible to identify differences in the geometry requirements of tertiary contacts between alpha-helices in general and transmembrane alpha-helices. The differences become more apparent when the correlation between the different geometry descriptors is analyzed. The results are compared with those of other types of secondary structure. Finally, an investigation of how the geometry of tertiary contacts changes with the amino-acid types involved in the contact is performed using multivariate techniques. The results of this study provide a well-defined overview of the underlying structural framework of tertiary contacts between alpha-helices, in both globular and TM environments, that will have valuable implications for predicting protein tertiary structure.

Amino Acid Sequence↗
PubMed2005

The impact of protein flexibility on protein-protein docking.

Accounting for protein flexibility in protein-protein docking algorithms is challenging, and most algorithms therefore treat proteins as rigid bodies or permit side-chain motion only. While the consequences are obvious when there are large conformational changes upon binding, the situation is less clear for the modest conformational changes that occur upon formation of most protein-protein complexes. We have therefore studied the impact of local protein flexibility on protein-protein association by means of rigid body and torsion angle dynamics simulation. The binding of barnase and barstar was chosen as a model system for this study, because the complexation of these 2 proteins is well-characterized experimentally, and the conformational changes accompanying binding are modest. On the side-chain level, we show that the orientation of particular residues at the interface (so-called hotspot residues) have a crucial influence on the way contacts are established during docking from short protein separations of approximately 5 A. However, side-chain torsion angle dynamics simulations did not result in satisfactory docking of the proteins when using the unbound protein structures. This can be explained by our observations that, on the backbone level, even small (2 A) local loop deformations affect the dynamics of contact formation upon docking. Complementary shape-based docking calculations confirm this result, which indicates that both side-chain and backbone levels of flexibility influence short-range protein-protein association and should be treated simultaneously for atomic-detail computational docking of proteins.

Computer Simulation↗
PubMed2005

Optimal docking area: a new method for predicting protein-protein interaction sites.

Understanding energetics and mechanism of protein-protein association remains one of the biggest theoretical problems in structural biology. It is assumed that desolvation must play an essential role during the association process, and indeed protein-protein interfaces in obligate complexes have been found to be highly hydrophobic. However, the identification of protein interaction sites from surface analysis of proteins involved in non-obligate protein-protein complexes is more challenging. Here we present Optimal Docking Area (ODA), a new fast and accurate method of analyzing a protein surface in search of areas with favorable energy change when buried upon protein-protein association. The method identifies continuous surface patches with optimal docking desolvation energy based on atomic solvation parameters adjusted for protein-protein docking. The procedure has been validated on the unbound structures of a total of 66 non-homologous proteins involved in non-obligate protein-protein hetero-complexes of known structure. Optimal docking areas with significant low-docking surface energy were found in around half of the proteins. The 'ODA hot spots' detected in X-ray unbound structures were correctly located in the known protein-protein binding sites in 80% of the cases. The role of these low-surface-energy areas during complex formation is discussed. Burial of these regions during protein-protein association may favor the complexed configurations with near-native interfaces but otherwise arbitrary orientations, thus driving the formation of an encounter complex. The patch prediction procedure is freely accessible at http://www.molsoft.com/oda and can be easily scaled up for predictions in structural proteomics.

Binding Sites↗
PubMed2005

Extent of protein-protein interactions and quasi-equivalence in viral capsids.

Viral capsids are composed of multiple copies of one or a few gene products that self-assemble on their own or in the presence of the viral genome and/or auxiliary proteins into closed shells (capsids). We have analyzed 75 high-resolution virus capsid structures by calculating the average fraction of the solvent-accessible surface area of the coat protein subunits buried in the viral capsids. This fraction ranges from 0 to 1 and represents a normalized protein-protein interaction (PPI) index and is a measure of the extent of protein-protein interactions. The PPI indices were used to compare the extent of association of subunits among different capsids. We further examined the variation of the PPI indices as a function of the molecular weight of the coat protein subunit and the capsid diameter. Our results suggest that the PPI indices in T=1 and pseudo-T=3 capsids vary linearly with the molecular weight of the subunit and capsid size. This is in contrast to quasi-equivalent capsids with T>or=3, where the extent of protein-protein interactions is relatively independent of the subunit and capsid sizes. The striking outcome of this analysis is the distinctive clustering of the "T=2" capsids, which are distinguished by higher subunit molecular weights and a much lower degree of protein-protein interactions. Furthermore, the calculated residual (R(sym)) of the fraction buried surface areas of the structurally unique subunits in capsids with T>1 was used to calculate the quasi-equivalence of different subunit environments.

Binding Sites↗
PubMed2005

Interaction interfaces of protein domains are not topologically equivalent across families within superfamilies: Implications for metabolic and signaling pathways.

Using a data set of aligned protein domain superfamilies of known three-dimensional structure, we compared the location of interdomain interfaces on the tertiary folds between members of distantly related protein domain superfamilies. The data set analyzed is comprised of interdomain interfaces, with domains occurring within a polypeptide chain and those between two polypeptide chains. We observe that, in general, the interfaces between protein domains are formed entirely in different locations on the tertiary folds in such pairs. This variation in the location of interface happens in protein domains involved in a wide range of functions, such as enzymes, adapters, and domains that bind protein ligands, or cofactors. While basic biochemical functionality is preserved at the domain superfamily level, the effect of biochemical function on protein assemblies is different in these protein domains related by superfamily. The divergence between proteins, in most cases, is coupled with domain recruitment, with different modes of interaction with the recruited domain. This is in complete contrast to the observation that in closely related homologous protein domains, almost always the interaction interfaces are topologically equivalent. In a small subset of interacting domains within proteins related by remote homology, we observe that the relative positioning of domains with respect to one another is preserved. Based on the analysis of multidomain proteins of known or unknown structure, we suggest that variation in protein-protein interactions in members within a superfamily could serve as diverging points in otherwise parallel metabolic or signaling pathways. We discuss a few representative cases of diverging pathways involving domains in a superfamily.

Animals↗
PubMed2005

Properties of polyproline II, a secondary structure element implicated in protein-protein interactions.

The polyproline II (PPII) conformation of protein backbone is an important secondary structure type. It is unusual in that, due to steric constraints, its main-chain hydrogen-bond donors and acceptors cannot easily be satisfied. It is unable to make local hydrogen bonds, in a manner similar to that of alpha-helices, and it cannot easily satisfy the hydrogen-bonding potential of neighboring residues in polyproline conformation in a manner analogous to beta-strands. Here we describe an analysis of polyproline conformations using the HOMSTRAD database of structurally aligned proteins. This allows us not only to determine amino acid propensities from a much larger database than previously but also to investigate conservation of amino acids in polyproline conformations, and the conservation of the conformation itself. Although proline is common in polyproline helices, helices without proline represent 46% of the total. No other amino acid appears to be greatly preferred; glycine and aromatic amino acids have low propensities for PPII. Accordingly, the hydrogen-bonding potential of PPII main-chain is mainly satisfied by water molecules and by other parts of the main-chain. Side-chain to main-chain interactions are mostly nonlocal. Interestingly, the increased number of nonsatisfied H-bond donors and acceptors (as compared with alpha-helices and beta-strands) makes PPII conformers well suited to take part in protein-protein interactions.

Amino Acid Sequence↗
PubMed2005

Analysis of sequence-reactivity space for protein-protein interactions.

Sequence-reactivity space is defined by the relationships between amino acid type choices at some residue positions in a protein and the reactivities of the resulting variants. We are studying Kazal superfamily serine proteinase inhibitors, under substitution of any combination of residue types at 10 binding-region positions. Reactivities are defined by the standard free energy of association for an inhibitor against an enzyme, and we are interested in both the strength (the free energy value) and specificity (relative free energy values for one inhibitor against different enzymes). Characterizing the structure of such a space poses several interesting questions: (1) How many sequences achieve particular strength and specificity characteristics? (2) What is the best such sequence? (3) What are some nearly-as-good alternatives? (4) What are their common residue type characteristics (e.g., conservation and correlation)? Although these problems are all highly combinatorial in nature, this article develops an efficient, integrated mechanism to address them under a data-driven model that predicts reactivity for given sequences. We employ sampling and a novel deterministic distribution propagation algorithm, in order to determine both the reactivity distribution and sequence composition statistics; integer programming and a novel branch-and-bound search algorithm, in order to optimize sequences and enumerate near-optimal sequences; and correlation-based sequence decomposition, in order to identify sequence motifs. We demonstrate the value of our mechanism in analyzing the Kazal superfamily sequence-reactivity space, providing insights into the underlying biochemistry and suggesting hypotheses for further experimental consideration. In general, our mechanism offers a valuable tool for investigating the available degrees of freedom in protein design within a combined computational-experimental framework.

Algorithms↗
PubMed2005

A "solvated rotamer" approach to modeling water-mediated hydrogen bonds at protein-protein interfaces.

Water-mediated hydrogen bonds play critical roles at protein-protein and protein-nucleic acid interfaces, and the interactions formed by discrete water molecules cannot be captured using continuum solvent models. We describe a simple model for the energetics of water-mediated hydrogen bonds, and show that, together with knowledge of the positions of buried water molecules observed in X-ray crystal structures, the model improves the prediction of free-energy changes upon mutation at protein-protein interfaces, and the recovery of native amino acid sequences in protein interface design calculations. We then describe a "solvated rotamer" approach to efficiently predict the positions of water molecules, at protein-protein interfaces and in monomeric proteins, that is compatible with widely used rotamer-based side-chain packing and protein design algorithms. Finally, we examine the extent to which the predicted water molecules can be used to improve prediction of amino acid identities and protein-protein interface stability, and discuss avenues for overcoming current limitations of the approach.

Algorithms↗
PubMed2005

Small-world network approach to identify key residues in protein-protein interaction.

We show that protein complexes can be represented as small-world networks, exhibiting a relatively small number of highly central amino-acid residues occurring frequently at protein-protein interfaces. We further base our analysis on a set of different biological examples of protein-protein interactions with experimentally validated hot spots, and show that 83% of these predicted highly central residues, which are conserved in sequence alignments and nonexposed to the solvent in the protein complex, correspond to or are in direct contact with an experimentally annotated hot spot. The remaining 17% show a general tendency to be close to an annotated hot spot. On the other hand, although there is no available experimental information on their contribution to the binding free energy, detailed analysis of their properties shows that they are good candidates for being hot spots. Thus, highly central residues have a clear tendency to be located in regions that include hot spots. We also show that some of the central residues in the protein complex interfaces are central in the monomeric structures before dimerization and that possible information relating to hot spots of binding free energy could be obtained from the unbound structures.

Amino Acids↗
PubMed2005

Protein conformational transitions coupled to binding in molecular recognition of unstructured proteins: deciphering the effect of intermolecular interactions on computational structure prediction of the p27Kip1 protein bound to the cyclin A-cyclin-dependent kinase 2 complex.

The relationship between folding mechanism coupled to binding and structure prediction of the tertiary complexes is studied for the p27(Kip) (1) protein which has an intrinsically disordered unbound form and undergoes a functional folding transition during complex formation with the phosphorylated cyclin A-cyclin-dependent kinase 2 (Cdk2) binary complex. Hierarchy of p27(Kip1) structural loss determined in our earlier studies from temperature-induced Monte Carlo simulations and subsequent characterization of the transition state ensemble (TSE) for the folding reaction have shown that simultaneous ordering of the p27(Kip1) native intermolecular interface for the beta-hairpin and beta-strand secondary structure elements is critical for nucleating a rapid kinetic transition to the native tertiary complex. In the present study, we investigate the effect of forming specific intermolecular interactions on structure prediction of the p27(Kip1) tertiary complex. By constraining different secondary structure elements of p27(Kip1) in their native bound conformations and conducting multiple simulated annealing simulations, we analyze differences in the success rate of predicting the native structure of p27(Kip1) in the tertiary complex. In accordance with the nucleation-condensation mechanism, we have found that further stabilization of the native intermolecular interface for the beta-hairpin and beta-strand elements of p27(Kip1), that become ordered in the TSE, but are hardly populated in the unbound state, results in a consistent acquisition of the native bound structure. Conversely, the excessive stablization of the local secondary structure elements, which are rarely detected in the TSE, has a detrimental effect on convergence to the native bound structure.

Cell Cycle↗
PubMed2005

Candidate nsSNPs that can affect the functions and interactions of cell cycle proteins.

Nonsynonymous single nucleotide polymorphisms (nsSNPs) alter the encoded amino acid sequence, and are thus likely to affect the function of the proteins, and represent potential disease-modifiers. There is an enormous number of nsSNPs in the human population, and the major challenge lies in distinguishing the functionally significant and potentially disease-related ones from the rest. In this study, we analyzed the genetic variations that can alter the functions and the interactions of a group of cell cycle proteins (n = 60) and the proteins interacting with them (n = 26) using computational tools. As a result, we extracted 249 nsSNPs from 77 cell cycle proteins and their interaction partners from public SNP databases. Only 31 (12.4%) of the nsSNPs were validated. The majority (64.5%) of the validated SNPs were rare (minor allele frequencies < 5%). Evolutionary conservation analysis using the SIFT tool suggested that 16.1% of the validated nsSNPs may disrupt the protein function. In addition, 58% of the validated nsSNPs were located in functional protein domains/motifs, which together with the evolutionary conservation analysis enabled us to infer possible biological consequences of the nsSNPs in our set. Our study strongly suggests the presence of naturally occurring genetic variations in the cell cycle proteins that may affect their interactions and functions with possible roles in complex human diseases, such as cancer.

Alleles↗
PubMed2005

Statistical analysis and prediction of protein-protein interfaces.

Predicting protein-protein interfaces from a three-dimensional structure is a key task of computational structural proteomics. In contrast to geometrically distinct small molecule binding sites, protein-protein interface are notoriously difficult to predict. We generated a large nonredundant data set of 1494 true protein-protein interfaces using biological symmetry annotation where necessary. The data set was carefully analyzed and a Support Vector Machine was trained on a combination of a new robust evolutionary conservation signal with the local surface properties to predict protein-protein interfaces. Fivefold cross validation verifies the high sensitivity and selectivity of the model. As much as 97% of the predicted patches had an overlap with the true interface patch while only 22% of the surface residues were included in an average predicted patch. The model allowed the identification of potential new interfaces and the correction of mislabeled oligomeric states.

Animals↗
PubMed2005

Exploring the charge space of protein-protein association: a proteomic study.

The rate of association of a protein complex is a function of an intrinsic basal rate and of the magnitude of electrostatic steering. In the present study we analyze the contribution of electrostatics towards the association rate of proteins in a database of 68 transient hetero-protein-protein complexes. Our calculations are based on an upgraded version of the computer algorithm PARE, which was shown to successfully predict the impact of mutations on k(on) by calculating the difference in Columbic energy of interaction of a pair of proteins. HyPare (http://bip.weizmann.ac.il/HyPare), automatically calculates the impact of mutations on a per-residue basis for all residues of a protein-protein interaction, achieving a precision similar to that of PARE. Our calculations show that electrostatics play a marginal role (<10 fold) in determining the rate of association for about half of the complexes in the database. Strong electrostatic steering, which results in an increase of over 100-fold in k(on), was calculated for about 25% of the complexes. Applying HyPare to all 68 complexes in the database shows that a small number of residues are hotspots for association. About 40% of the hotspots are calculated to increase the rate of association upon mutation, and thus increase binding affinity. This is a much higher ratio than found for hotspots for dissociation, where the large majority cause weaker binding. About 40% of the hotspots are located outside the physical boundary of the binding site, making them ideal candidates for protein engineering. Our data shows that a majority of protein-protein complexes are not optimized for fast association. Hotspots are not evenly distributed between all types of amino acids. About 75% of all hotspots are of charged residues. This is understandable, as a charge-reverse mutant changes the total charge by 2. The small number of hydrophobic residues that are hotspots upon mutation probably relates to their location and surrounding. For 18 out of the 68 complexes in the database, experimental values of k(on) are available. For these, a basal rate of association was calculated to be in the range of 10(4)M(-1)s(-1) to 10(7)M(-1)s(-1). Some of these rates were verified independently from experimental mutant data. The basal rates were correlated with the size of the proteins and the shape of the interface.

Algorithms↗
PubMed2005

Classification of protein complexes based on docking difficulty.

Based on the results of several groups using different docking methods, the key properties that determine the expected success rate in protein-protein docking calculations are measures of conformational change, interface area, and hydrophobicity. A classification of protein complexes in terms of these measures provides a prediction of docking difficulty. This classification is used to study the targets of the CAPRI docking experiment. Results show that targets with a moderate expected difficulty were indeed predicted well by a number of groups, whereas the use of additional a priori information was necessary to obtain good results for some very difficult targets. The analysis indicates that CAPRI and other relatively large-scale docking studies represent very important steps toward understanding the capabilities and limitations of current protein-protein docking methods.

Algorithms↗
PubMed2005

Docking to single-domain and multiple-domain proteins: old and new challenges.

The diverse selection of targets in the CAPRI experiments provides grounds for determining the limits of our rigid-body docking program MolFit, and for extending it. We find that the sensitivity of MolFit is high, enabling it to produce reasonably accurate docking solutions when the structures undergo moderate local conformation changes upon complex formation or when the docked molecules are modeled. Yet the ranks of these solutions are sometimes too low to meet the requirements of CAPRI assessment. This indicates that the selectivity of MolFit, which was optimized for docking of unbound X-ray structures, and which relies on the availability of external data from biochemical and bioinformatic sources, needs readjustment in order to meet the challenges presented by NMR or modeled structures. A different challenge is presented by large global conformation changes such as movements of domains. We show that such changes can be accommodated within the rigid-body approximation by employing rigid multibody multistage docking procedures. We also address the difficulty of ranking results from 2-body and multibody docking scans in cases in which there are no external data favoring one option over the other.

Algorithms↗
PubMed2005

Modeling oligomers with Cn or Dn symmetry: application to CAPRI target 10.

The abundance of oligomeric proteins makes them a frequent target for structure prediction. However, homologous proteins sometimes adopt different oligomerization states, rendering the prediction of structures of whole oligomers beyond the scope of comparative modeling. This obstacle can be overcome by combining comparative modeling of the single subunit of an oligomer with docking techniques, designed for predicting subunit-subunit interfaces. We present here algorithms for predicting the structures of homo-oligomers with C(n) or D(n) (n > 2) symmetry. The prediction procedure includes a symmetry-restricted docking step followed by a C(n) or D(n) oligomer-forming step, in which the dimers from the docking step are assembled to oligomers. The procedure is applied to each of the crystallographically independent subunits in 8 C(n) and 3 D(n) oligomers, producing very accurate predictions. It is further applied to a single monomer of the tick-borne encephalitis virus coat protein E (Target 10 of the CAPRI experiment). The predicted trimer ranked 30, obtained via rigid-body geometric-hydrophobic docking followed by C(n) oligomer formation, is very similar to the experimentally observed trimer formed by domain II of this protein. Furthermore, the predicted trimer formed from the separated domain I is also close to the experimental structure.

Algorithms↗