Importance of hydrophobic cluster formation through long-range contacts in the folding transition state of two-state proteins

Understanding the folding pathways of proteins is a challenging task. The Phi value approach provides a detailed understanding of transition-state structures of folded proteins. In this work, we have computed the hydrophobicity associated with each residue in the folded state of 16 two-state proteins and compared the Phi values of each mutant residue. We found that most of the residues with high Phi value coincide with local maximum in surrounding hydrophobicity, or have nearby residues that show such maximum in hydrophobicity, indicating the importance of hydrophobic interactions in the transition state. We have tested our approach to different structural classes of proteins, such as alpha-helical, SH3 domains of all-beta proteins, beta-sandwich, and alpha/beta proteins, and we observed a good agreement with experimental results. Further, we have proposed a hydrophobic contact network pattern to relate the Phi values with long-range contacts, which will be helpful to understand the transition-state structures of folded proteins. The present approach could be used to identify potential hydrophobic clusters that may form through long-range contacts during the transition state.     

A comparative analysis of the equilibrium dynamics of a designed protein inferred from NMR,X‐ray,and computations

A detailed analysis of high‐resolution structural data and computationally predicted dynamics was carried out for a designed sugar‐binding protein. The mean‐square deviations in the positions of residues derived from nuclear magnetic resonance (NMR) models and those inferred from X‐ray crystallographic B‐factors for two different crystal forms were compared with the predictions based on the Gaussian Network Model (GNM) and the results from molecular dynamics (MD) simulations. GNM systematically yielded a higher correlation than MD, with experimental data, suggesting that the lack of atomistic details in the coarse‐grained GNM is more than compensated for by the mathematically exact evaluation of fluctuations using the native contacts topology. Evidence is provided that particular loop motions are curtailed by intermolecular contacts in the crystal environment causing a discrepancy between theory and experiments. Interestingly, the information conveyed by X‐ray crystallography becomes more consistent with NMR models and computational predictions when ensembles of X‐ray models are considered. Less precise (broadly distributed) ensembles indeed appear to describe the accessible conformational space under native state conditions better than B‐factors. Our results highlight the importance of using multiple conformations obtained by alternative experimental methods, and analyzing results from both coarse‐grained models and atomic simulations, for accurate assessment of motions accessible to proteins under native state conditions. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Structure-wise discrimination of cytosine,thymine, and uracil by proteins in terms of their nonbonded interactions

The molecular recognition and discrimination of very similar ligand moieties by proteins are important subjects in protein–ligand interaction studies. Specificity in the recognition of molecules is determined by the arrangement of protein and ligand atoms in space. The three pyrimidine bases, viz. cytosine, thymine, and uracil, are structurally similar, but the proteins that bind to them are able to discriminate them and form interactions. Since nonbonded interactions are responsible for molecular recognition processes in biological systems, our work attempts to understand some of the underlying principles of such recognition of pyrimidine molecular structures by proteins. The preferences of the amino acid residues to contact the pyrimidine bases in terms of nonbonded interactions; amino acid residue–ligand atom preferences; main chain and side chain atom contributions of amino acid residues; and solvent-accessible surface area of ligand atoms when forming complexes are analyzed. Our analysis shows that the amino acid residues, tyrosine and phenyl alanine, are highly involved in the pyrimidine interactions. Arginine prefers contacts with the cytosine base. The similarities and differences that exist between the interactions of the amino acid residues with each of the three pyrimidine base atoms in our analysis provide insights that can be exploited in designing specific inhibitors competitive to the ligands.     

A simple topological representation of protein structure: implications for new, fast, and robust structural classification

A topological representation of proteins is developed that makes use of two metrics: the Euclidean metric for identifying natural nearest neighboring residues via the Delaunay tessellation in Cartesian space and the distance between residues in sequence space. Using this representation, we introduce a quantitative and computationally inexpensive method for the comparison of protein structural topology. The method ultimately results in a numerical score quantifying the distance between proteins in a heuristically defined topological space. The properties of this scoring scheme are investigated and correlated with the standard Calpha distance root-mean-square deviation measure of protein similarity calculated by rigid body structural alignment. The topological comparison method is shown to have a characteristic dependence on protein conformational differences and secondary structure. This distinctive behavior is also observed in the comparison of proteins within families of structural relatives. The ability of the comparison method to successfully classify proteins into classes, superfamilies, folds, and families that are consistent with standard classification methods, both automated and human-driven, is demonstrated. Furthermore, it is shown that the scoring method allows for a fine-grained classification on the family, protein, and species level that agrees very well with currently established phylogenetic hierarchies. This fine classification is achieved without requiring visual inspection of proteins, sequence analysis, or the use of structural superimposition methods. Implications of the method for a fast, automated, topological hierarchical classification of proteins are discussed.     

1D2DSimScore: A novel method for comparing contacts in biomacromolecules and their complexes

The biologically relevant structures of proteins and nucleic acids and their complexes are dynamic. They include a combination of regions ranging from rigid structural segments to structural switches to regions that are almost always disordered, which interact with each other in various ways. Comparing conformational changes and variation in contacts between different conformational states is essential to understand the biological functions of proteins, nucleic acids, and their complexes. Here, we describe a new computational tool, 1D2DSimScore, for comparing contacts and contact interfaces in all kinds of macromolecules and macromolecular complexes, including proteins, nucleic acids, and other molecules. 1D2DSimScore can be used to compare structural features of macromolecular models between alternative structures obtained in a particular experiment or to score various predictions against a defined “ideal” reference structure. Comparisons at the level of contacts are particularly useful for flexible molecules, for which comparisons in 3D that require rigid-body superpositions are difficult, and in biological systems where the formation of specific inter-residue contacts is more relevant for the biological function than the maintenance of a specific global 3D structure. Similarity/dissimilarity scores calculated by 1D2DSimScore can be used to complement scores describing 3D structural similarity measures calculated by the existing tools.     

Atomic contacts in protein structures. A detailed analysis of atomic radii, packing, and overlaps

A rigorous quantitative assessment of atomic contacts and packing in native protein structures is presented. The analysis is based on optimized atomic radii derived from a set of high-resolution protein structures and reveals that the distribution of atomic contacts and overlaps is a structural constraint in proteins, irrespective of structural or functional classification and size. Furthermore, a newly developed method for calculating packing properties is introduced and applied to sets of protein structures at different levels of resolution. The results show that limited resolution yields decreasing packing quality, which underscores the relevance of packing considerations for structure prediction, design, dynamics, and docking.     

DeepFunc: A Deep Learning Framework for Accurate Prediction of Protein Functions from Protein Sequences and Interactions

Annotation of protein functions plays an important role in understanding life at the molecular level. High‐throughput sequencing produces massive numbers of raw proteins sequences and only about 1% of them have been manually annotated with functions. Experimental annotations of functions are expensive, time‐consuming and do not keep up with the rapid growth of the sequence numbers. This motivates the development of computational approaches that predict protein functions. A novel deep learning framework, DeepFunc, is proposed which accurately predicts protein functions from protein sequence‐ and network‐derived information. More precisely, DeepFunc uses a long and sparse binary vector to encode information concerning domains, families, and motifs collected from the InterPro tool that is associated with the input protein sequence. This vector is processed with two neural layers to obtain a low‐dimensional vector which is combined with topological information extracted from protein–protein interactions (PPIs) and functional linkages. The combined information is processed by a deep neural network that predicts protein functions. DeepFunc is empirically and comparatively tested on a benchmark testing dataset and the Critical Assessment of protein Function Annotation algorithms (CAFA) 3 dataset. The experimental results demonstrate that DeepFunc outperforms current methods on the testing dataset and that it secures the highest F_max = 0.54 and AUC = 0.94 on the CAFA3 dataset.     

Energetics of galactose- and glucose-aromatic amino acid interactions: implications for binding in galactose-specific proteins

An aromatic amino acid is present in the binding site of a number of sugar binding proteins. The interaction of the saccharide with the aromatic residue is determined by their relative position as well as orientation. The position-orientation of the saccharide relative to the aromatic residue was found to vary in different sugar-binding proteins. In the present study, interaction energies of the complexes of galactose (Gal) and of glucose (Glc) with aromatic residue analogs have been calculated by ab initio density functional (U-B3LYP/ 6-31G**) theory. The position-orientations of the saccharide with respect to the aromatic residue observed in various Gal-, Glc-, and mannose-protein complexes were chosen for the interaction energy calculations. The results of these calculations show that galactose can interact with the aromatic residue with similar interaction energies in a number of position-orientations. The interaction energy of Gal-aromatic residue analog complex in position-orientations observed for the bound saccharide in Glc/Man-protein complexes is comparable to the Glc-aromatic residue analog complex in the same position-orientation. In contrast, there is a large variation in interaction energies of complexes of Glc- and of Gal- with the aromatic residue analog in position-orientations observed in Gal-protein complexes. Furthermore, the conformation wherein the O6 atom is away from the aromatic residue is preferred for the exocyclic -CH2OH group in Gal-aromatic residue analog complexes. The implications of these results for saccharide binding in Gal-specific proteins and the possible role of the aromatic amino acid to ensure proper positioning and orientation of galactose in the binding site have been discussed.     

A Continuum theory for the prediction of lateral and rotational positioning of α-helices in membrane proteins: Bacteriorhodopsin

We have developed a new method for the prediction of the lateral and the rotational positioning of transmembrane helices, based upon the present status of knowledge about the dominant interaction of the tertiary structure formation. The basic assumption about the interaction is that the interhelix binding is due to the polar interactions and that very short extramembrane loop segments restrict the relative position of the helices. Another assumption is made for the simplification of the prediction that a helix may be regarded as a continuum rod having polar interaction fields around it. The polar interaction field is calculated by a probe helix method, using a copolymer of serine and alanine as probe helices. The lateral position of helices is determined by the strength of the interhelix binding estimated from the polar interaction field together with the length of linking loop segments. The rotational positioning is determined by the polar interaction field, assuming the optimum lateral configuration. The structural change due to the binding of a prosthetic group is calculated, fixing the rotational freedom of a helix that is connected to the prosthetic group. Applying this method to bacteriorhodopsin, the optimum lateral and rotational positioning of transmembrane helices that are very similar to the experimental configuration was obtained. This method was implemented by a software system, which was developed for this work, and automatic calculation became possible for membrane proteins comprised of several transmembrane helices. © 1995 Wiley-Liss, Inc.     

Conformational and helicoidal analysis of the molecular dynamics of proteins: "curves," dials and windows for a 50 psec dynamic trajectory of BPTI

A new procedure for the graphic analysis of molecular dynamics (MD) simulations on proteins is introduced, in which comprehensive visualization of results and pattern recognition is greatly facilitated. The method involves determining the conformational and helicoidal parameters for each structure entering the analysis via the method "Curves," developed for proteins by Sklenar, Etchebest, and Lavery (Proteins: Structure, Function Genet. 6:46-60, 1989) followed by a novel computer graphic display of the results. The graphic display is organized systematically using conformation wheels ("dials") for each torsional parameter and "windows" on the range values assumed by the linear and angular helicoidal parameters, and is present in a form isomorphous with the primary structure per se. The complete time evolution of dynamic structure can then be depicted in a set of four composite figures. Dynamic aspects of secondary and tertiary structure are also provided. The procedure is illustrated with an analysis of a 50 psec in vacuo simulation on the 58 residue protein, bovine pancreatic trypsin inhibitor (BPTI), in the vicinity of the local minimum on the energy surface corresponding to a high resolution crystal structure. The time evolution of 272 conformational and 788 helicoidal parameters for BPTI is analyzed. A number of interesting features can be discerned in the analysis, including the dynamic range of conformational and helicoidal motions, the dynamic extent of 2 degrees structure motifs, and the calculated fluctuations in the helix axis. This approach is expected to be useful for a critical analysis of the effects of various assumptions about force field parameters, truncation of potentials, solvation, and electrostatic effects, and can thus contribute to the development of more reliable simulation protocols for proteins. Extensions of the analysis to present differential changes in conformational and helicoidal parameters is expected to be valuable in MD studies of protein complexes with substrates, inhibitors, and effectors and in determining the nature of structural changes in protein-protein interactions.     

Toward a systems level view of the ECM and related proteins: a framework for the systematic definition and analysis of biological systems

Advances in high throughput 'omic technologies are starting to provide unprecedented insights into how components of biological systems are organized and interact. Key to exploiting these datasets is the definition of the components that comprise the system of interest. Although a variety of knowledge bases exist that capture such information, a major challenge is determining how these resources may be best utilized. Here we present a systematic curation strategy to define a systems-level view of the human extracellular matrix (ECM)--a three-dimensional meshwork of proteins and polysaccharides that impart structure and mechanical stability to tissues. Employing our curation strategy we define a set of 357 proteins that represent core components of the ECM, together with an additional 524 genes that mediate related functional roles, and construct a map of their physical interactions. Topological properties help identify modules of functionally related proteins, including those involved in cell adhesion, bone formation and blood clotting. Because of its major role in cell adhesion, proliferation and morphogenesis, defects in the ECM have been implicated in cancer, atherosclerosis, asthma, fibrosis, and arthritis. We use MeSH annotations to identify modules enriched for specific disease terms that aid to strengthen existing as well as predict novel gene-disease associations. Mapping expression and conservation data onto the network reveal modules evolved in parallel to convey tissue-specific functionality on otherwise broadly expressed units. In addition to demonstrating an effective workflow for defining biological systems, this study crystallizes our current knowledge surrounding the organization of the ECM.     

Anti-apoptotic Bcl-XL protein in complex with BH3 peptides of pro-apoptotic Bak, Bad, and Bim proteins: comparative molecular dynamics simulations

The Bcl-2 family of proteins plays a central role in the regulation of mitochondrial outer-membrane permeabilization, a critical step in apoptosis. Heterodimerization between the pro- and anti-apoptotic members of Bcl-2 family is a key event in this process. Anti-apoptotic proteins have high levels of expression in many cancers and they have different affinities for different pro-apoptotic proteins. Experimentally determined structures of all members of Bcl-2 proteins have remarkably similar helical fold despite poor amino acid sequence identity. Peptides representing BH3 region of pro-apoptotic proteins have been shown to bind the hydrophobic cleft of anti-apoptotic proteins and this segment is responsible in modulating the apoptotic pathways in living cells. Understanding the molecular basis of protein-protein recognition is required to develop inhibitors specific to a particular anti-apoptotic protein. We have carried out molecular dynamics simulations on the anti-apoptotic Bcl-X(L) protein in complex with three different BH3 peptides derived from pro-apoptotic Bak, Bad and Bim proteins. Each complex structure was simulated for a period of 50 ns after 2.5 ns equilibration. Analysis of the simulation results showed that in the Bcl-X(L) protein, the helix containing the BH3 region is more flexible than other helices in all three simulations. A network of strong hydrophobic interactions exists between four of the six helices and they contribute significantly to the stability of this helix bundle protein. Analysis of Bcl-X(L)-BH3 peptide interactions reveals the role of loop residues in the protein-peptide interactions in all three simulations. Bad and Bim peptides maintain strong hydrophobic and hydrophilic interactions with the helix preceding the central hydrophobic helix. Residues from this helix interact with an Arg residue in Bad and Bim peptides. This Arg residue is next to the conserved Leu residue and is replaced by Ala in Bak. Absence of these interactions and the helix propensity are likely to be the cause for Bak peptide's weaker binding affinity with the Bcl-X(L) protein. The results of this study have implications in the design of Bcl-X(L)-specific inhibitors.     

ComplexBrowser: A Tool for Identification and Quantification of Protein Complexes in Large-scale Proteomics Datasets

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Highlights

• •Automated analysis of protein complexes in proteomic experiments.
• •Quantitative measurement of the coordinated changes in protein complex components.
• •Interactive visualizations for exploratory analysis of proteomic results.

     

Bcl-2-like和Bax-like蛋白在白蚁生殖蚁和工蚁精子发生过程中的表达比较分析

为探讨凋亡调节因子Bcl-2和Bax蛋白对白蚁生殖蚁和工蚁性腺发育的影响, 揭示白蚁生殖品级与非生殖品级性腺发育的调节机理, 以尖唇散白蚁Reticulitermes aculabialis为研究对象, 运用免疫细胞化学定位方法对生殖蚁和工蚁精子发生过程中的Bcl-2和Bax蛋白表达进行了研究。结果显示： 生殖蚁和工蚁精子发生过程中从精原细胞至精子时期均有Bcl-2-like和Bax-like的阳性表达。生殖蚁的次级精母细胞、 精子细胞和精子中Bcl-2-like阳性表达率较高, 而在精原细胞和初级精母细胞中阳性率较低; 工蚁在次级精母细胞中最高, 在精原细胞和初级精母细胞中较低。除初级精母细胞期外, 工蚁生殖细胞其他发育阶段Bax-like阳性表达率均显著高于生殖蚁同一阶段生殖细胞。生殖蚁的生殖细胞在精原细胞、 初级精母细胞和次级精母细胞时期Bax-like阳性表达率较高, 发育至精子时期阳性率最低; 工蚁在次级精母细胞、 精子细胞和精子时期Bax-like表达率较高, 在初级精母细胞中表达率最低。在精子发生过程中, 生殖蚁生殖细胞Bax/Bcl表达量比值逐步下降; 而工蚁生殖细胞发育过程中Bax/Bcl表达量比值仅在次级精母细胞期下降, 其他发育时期均升高; 根据Bax/Bcl判断, 精原细胞和初级精母细胞是生殖蚁精子发生过程中主要的凋亡点, 而工蚁除了精原细胞和初级精母细胞外, 精子细胞和精子也是主要的凋亡目标。研究结果表明, 白蚁生殖细胞凋亡与其他动物一样受Bcl-2家族的调节, 在精子发生过程中Bcl-2-like和Bax-like表达具有动态变化规律, 正是这种变化调控生殖细胞在不同发育阶段的生或死; Bcl-2-like和Bax-like对生殖细胞凋亡调节不仅在精子发生中有非常重要的作用, 而且可能与工蚁品级的形成有关。     

Identification of metastasis candidate proteins among HCC cell lines by comparative proteome and biological function analysis of S100A4 in metastasis in vitro

Widespread metastasis of hepatocellular carcinoma (HCC) was a complex cascade of events, which is still beyond full appreciation. Screening key proteins, which play a critical role in metastasis, using high-throughput proteomics approach help discover valuable biomarkers and elucidate the mechanism of metastasis. This study was to find out some metastasis candidate proteins among HCC cell lines with various metastatic potential by comparative proteomics, and then further validate the biological function of these proteins in metastasis in vitro. The protein profiles of metastatic HCC cell lines (MHCC97H and MHCC97L) displayed obvious differences compared with nonmetastatic ones (Hep3B). Twenty-six metastasis candidate proteins, which were identified by on-line LC-ESI-MS/MS, such as S100 calcium-binding protein A4 (S100A4), annexin 1, etc., might have much application in diagnostic procedures and prognosis evaluation. S100A4, as a leading different metastasis candidate protein, which overexpressed only in the metastatic cells, was selected for further investigation. A series of assays related to invasion and metastasis in vitro, including cell motility, invasion, and matrix metalloproteinases (MMPs) secretion, were performed in MHCC97H/antisense recombinant plasmid to S100A4 (pcDNA3.1(+) AS S100A4) and the mock controls. All the data in the present study suggested that S100A4 might contribute to HCC invasion and metastasis through two paths of matrix metalloproteinase (MMP9) secretion regulation and strengthened motility and invasion properties.     

A general method for the quantitative analysis of functional chimeras: applications from site-directed mutagenesis and macromolecular association

Two new parameters, I: and C:, are introduced for the quantitative evaluation of functional chimeras: I: (impact) and C: (context dependence) are the free energy difference and sum, respectively, of the effects on a given property measured in forward and retro chimeras. The forward chimera is made by substitution of a part "a" from ensemble A into the analogous position of homologous ensemble B (S:(B --> A)). The C: value is a measure of the interaction of the interrogated position with its surroundings, whereas I: is an expression of the quantitative importance of the probed position. Both I: and C: vary with the evaluated property, for example, kinetics, binding, thermostability, and so forth. The retro chimera is the reverse substitution of the analogous part "b" from B into A, S:(A --> B). The I: and C: values derived from original data for forward and retro mutations in aspartate and tyrosine aminotransferase, from literature data for quasi domain exchange in oncomodulin and for the interaction of Tat with bovine and human TAR are evaluated. The most salient derived conclusions are, first, that Thr 109 (AATase) or Ser 109 (TATase) is an important discriminator for dicarboxylic acid selectivity by these two enzymes (I: < -2.9 kcal/mol). The T109S mutation in AATase produces a nearly equal and opposite effect to S109T in TATase (C: < 0.4 kcal/mol). Second, an I: value of 5.5 kcal/mol describes the effects of mirror mutations D94S (site 1) and S55D (site 2) in the Ca(2+) binding sites of oncomodulin on Ca(2+) affinity. The second mirror set, G98D (site 1) and D59G (site 2), yields a smaller impact (I: = -3.4 kcal/mol) on Ca(2+) binding; however, the effect is significantly more nearly context independent (C: = -0.6 versus C: = -2.7 kcal/mol). Third, the stem and loop regions of HIV and BIV TAR are predominantly responsible for the species specific interaction with BIV Tat(65-81) (I: = -1.5 to -1.6 kcal/mol), whereas I: = 0.1 kcal/mol for bulge TAR chimeras. The C: values are from -0.3 to -1.2 kcal/mol. The analysis described should have important applications to protein design.