Protein–Protein Docking: Past,Present, and Future

The Protein Journal - The biological significance of proteins attracted the scientific community in exploring their characteristics. The studies shed light on the interaction patterns and functions...     

A Phage Display Technique for a Fast, Sensitive, and Systematic Investigation of Protein–Protein Interactions

Phage display is a technique in which a foreign protein or peptide is presented at the surface of a (filamentous) bacteriophage. This system, developed by Smith [(1985), Science 228, 1315–1317], was originally used to create large libraries of antibodies for the purpose of selecting those that strongly bound a particular antigen. More recently it was also employed to present peptides, domains of proteins, or intact proteins at the surface of phages, again to identify high-affinity interactions with ligands. Here we want to illustrate the use of phage display, in combination with PCR saturation mutagenesis, for the study of protein–protein interactions. Rather than selecting for mutants having high affinity, we systematically investigate the binding of every variant with its natural ligand. Via a modified ELISA we can calculate a relative affinity. As a model system we chose to display thymosin β4 on the phage surface in order to study its interaction with actin.     

Peptide, Peptidomimetic, and Small-molecule Antagonists of the p53–HDM2 Protein–Protein Interaction

Modulation of intracellular protein–protein interactions has been – and remains – a challenging goal for the discovery and development of small-molecule therapeutic agents. Progress in the pharmacological targeting and understanding at the molecular level of one such interaction that is relevant to cancer drug research, viz. that between the tumour suppressor protein p53 and its negative regulator HDM2, is reviewed here. The first X-ray crystal structure of a complex between a small peptide from the trans-activation domain of p53 and the N-terminal domain of HDM2 was reported almost 10 years ago. The nature of this interaction, which involves just three residue side chains in the p53 peptide ligand and a compact hydrophobic binding pocket in the HDM2 receptor, together with the attractive concept of reactivating the anti-proliferative functions of p53 in tumour cells, has spurned a great deal of effort aimed at finding drug-like antagonists of this interaction. A variety of approaches, including both structure-guided peptidomimetic and de novo design, as well as high through-put screening campaigns, have provided a wealth of leads that might be turned into actual drugs. There is still some way to go as far as optimisation and preclinical development of such leads is concerned, but it is clear already now that antagonists of the p53–HDM2 protein–protein interaction have a good chance of ultimately being successful in providing a new anti-cancer therapy modality, both in monotherapy and to potentiate the effectiveness of existing chemotherapies.     

Isolation of Protein Inhibitors of Papain,Trypsin, and α-Amylase in the Grain of Foxtail Millet

The amino acid sequence of Indian peafowl egg-white lysozyme has been identified. The reduced and carboxymethylated lysozyme was digested with trypsin followed by purification of the resulting peptides by reverse-phase HPLC. The tryptic peptides obtained were sequenced using the DABITC/PITC double coupling manual sequencing method. The alignment of the tryptic peptides were deduced by comparison with corresponding peptides of hen egg-white lysozyme. This protein proved to consist of 129 amino acid residues, and a relative molecular mass of 14423 Da was calculated. Amino acid sequence comparison of peafowl lysozyme and other phasianoid bird lysozymes revealed a maximum homology ratio of 98% with turkey lysozyme.     

The Lengthening of a Giant Protein: When, How, and Why?

Subcommissural organ (SCO)-spondin is a giant glycoprotein of more than 5000 amino acids found in Vertebrata, expressed in the central nervous system and constitutive of Reissner’s fiber. For the first time, in situ hybridization performed on zebrafish (Danio rerio) embryos shows that the gene encoding this protein is expressed transitionally in the floor plate, the ventral midline of the neural tube, and later in the diencephalic third ventricle roof, the SCO. The modular organization of the protein in Echinodermata (Strongylocentrotus purpuratus), Urochordata (Ciona savignyi and C. intestinalis), and Vertebrata (Teleostei, Amphibia, Aves and Mammalia) is also described. As the thrombospondin type 1 repeat motifs represent an increasingly large part of the protein during Deuterostomia evolution, the duplication mechanisms leading to this complex organization are examined. The functional significance of the particularly well-preserved arrangement of the series of SCO-spondin repeat motifs and thombospondin type 1 repeats is discussed. Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Combination of Soy Protein,Amylopectin, and Chromium Stimulates Muscle Protein Synthesis by Regulation of Ubiquitin–Proteasome Proteolysis Pathway after Exercise

This review discusses the development of studies that evaluated the essentiality and requirements of iron from the ancient to the present. The therapeutic effects of iron compounds were recognized by the ancient Greeks and Romans. The earliest recognition of the essentiality of iron was stated by Paracelsus, a distinguished physician alchemist, in the sixteenth century. Iron was included in the earliest nutritional standard prepared for the Royal Army by E. A. Parkes, the first professor of hygiene. The League of Nations Health Organisation determined average iron requirements based on literature review. In the first US Recommended Dietary Allowances (RDA), the RDA of iron was determined from the results of iron balance studies. In the current Dietary Reference Intakes, iron requirements were determined based on the factorial method with the aid of Monte Carlo simulation for combining basal and menstrual iron losses. Population data analysis is a recently developed alternative that does not use the pre-estimated iron absorption rate and requires the prevalence of inadequacy instead. Population data analysis uses the convolution integral for combining basal and menstrual iron losses to ensure the required accuracy. This review also provides new estimates of hair and nail iron losses.

     

Computational Prediction of Protein–Protein Interaction Networks: Algo-rithms and Resources

Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computational methods have attracted tremendous attention among biologists because of the ability to predict protein-protein interactions and validate the obtained experimental results. In this study, we have reviewed several computational methods for protein-protein interaction prediction as well as describing major databases, which store both predicted and detected protein-protein interactions, and the tools used for analyzing protein interaction networks and improving protein-protein interaction reliability.     

Protein Components of Bacteriophages λ and λ Virulent

Parallel studies have been made of the protein coats of the temperate bacteriophage λ and of a deletion mutant, λ virulent. A new method for preparing ghosts of both phages by the action of Cu⁺⁺ is described. Protein ghosts of both phages can be dissolved in citrate at pH values below 3, more rapidly in the presence of 8 m urea. Both phages yielded three apparently identical protein components which can be separated by thin-layer gel filtration and thin-layer gel electrophoresis. The protein of molecular weight 47,000 ± 1,500 represents about 55% of the protein of the ghosts and is therefore likely to be the subunit of the head. The other proteins of molecular weight 30,000 ± 1,500 and 16,000 ± 1,500 represent approximately 25% and 20% of the protein, respectively. Amino acid analyses of the ghosts from the two phages have been carried out and show no significant differences. The buoyant density of phage λ virulent is 0.016 g/ml less than that of λ. Since no differences have been found in the protein components of the two phages, this indicates that the virulent mutant contains approximately 16% less deoxyribonucleic acid than the temperate phage.     

Methodology and Problems of Protein‐Ligand Docking: Case Study of Dihydroorotate Dehydrogenase,Thymidine Kinase,and Phosphodiesterase 4

Abstract

The docking methodology was applied to three different therapeutically interesting enzymes: human dihydroorotate dehydrogenase (DHODH), Herpes simplex virus type I thymidine kinase (HSV1 TK) and human phosphodiesterase 4 (PDE4). Programs FlexX, AutoDock and DOCK where used. The three targets represent three distinct cases. For DHODH and HSV1 TK, the binding modes of substrate and inhibitors within the active site are known, while the binding orientation of cAMP within PDE4 has been solely hypothesized. Active site of DHODH is mainly hydrophobic and the binding mode of the inhibitor brequinar was used as a template for evaluating the docking strategies. The presence of cofactors revealed to be crucial for the definition of the docking site. The HSV1 TK active site is small and polar and contains crystal water molecules and ATP. Docking of thymidine and aciclovir (ACV) within the active site was analyzed by keeping or removing water molecules. It showed the crucial role of water in predicting the binding of pyrimidines and purines. The crystal structure of PDE4 contains magnesium and zinc cations as well as catalytic water molecule but no ligand. Several docking experiments of cAMP and rolipram were performed and the results showed clear‐cut dependence between the ligand orientation and the presence of metals in the active site. All three cases show specific problems of the docking methodology, depending on the character of the active site.     

Characterization of Protein–Protein Interfaces

We analyze the characteristics of protein–protein interfaces using the largest datasets available from the Protein Data Bank (PDB). We start with a comparison of interfaces with protein cores and non-interface surfaces. The results show that interfaces differ from protein cores and non-interface surfaces in residue composition, sequence entropy, and secondary structure. Since interfaces, protein cores, and non-interface surfaces have different solvent accessibilities, it is important to investigate whether the observed differences are due to the differences in solvent accessibility or differences in functionality. We separate out the effect of solvent accessibility by comparing interfaces with a set of residues having the same solvent accessibility as the interfaces. This strategy reveals residue distribution propensities that are not observable by comparing interfaces with protein cores and non-interface surfaces. Our conclusions are that there are larger numbers of hydrophobic residues, particularly aromatic residues, in interfaces, and the interactions apparently favored in interfaces include the opposite charge pairs and hydrophobic pairs. Surprisingly, Pro-Trp pairs are over represented in interfaces, presumably because of favorable geometries. The analysis is repeated using three datasets having different constraints on sequence similarity and structure quality. Consistent results are obtained across these datasets. We have also investigated separately the characteristics of heteromeric interfaces and homomeric interfaces.     

Protein and carbohydrate moieties of a preparation of β-lactamase II

1. A crystalline preparation of beta-lactamase II has been separated into two moieties by gel filtration on a column of Sephadex G-100. 2. The first moiety consisted mainly of carbohydrate and showed virtually no beta-lactamase activity. 3. The second moiety was a protein of molecular weight 22500, which was enzymically active. 4. The protein moiety, like the original protein-carbohydrate complex, required Zn(2+) for beta-lactamase activity. It did not differ significantly from the complex in its behaviour to a number of cephalosporin substrates, but was less stable to heat than the complex. 5. About 30% of the total beta-lactamase activity was lost when the protein-carbohydrate complex was separated into the two moieties. This activity was regained when the protein and carbohydrate moieties were mixed, but the mixture did not show the heat stability of the original complex.     

Direct Binding and Regulation of RhoA Protein by Cyclic GMP-dependent Protein Kinase Iα

Vascular smooth muscle cell (VSMC) tone is regulated by the state of myosin light chain (MLC) phosphorylation, which is in turn regulated by the balance between MLC kinase and MLC phosphatase (MLCP) activities. RhoA activates Rho kinase, which phosphorylates the regulatory subunit of MLC phosphatase, thereby inhibiting MLC phosphatase activity and increasing contraction and vascular tone. Nitric oxide is an important mediator of VSMC relaxation and vasodilation, which acts by increasing cyclic GMP (cGMP) levels in VSMC, thereby activating cGMP-dependent protein kinase Iα (PKGIα). PKGI is known to phosphorylate Rho kinase, preventing Rho-mediated inhibition of MLC phosphatase, promoting vasorelaxation, although the molecular mechanisms that mediate this are unclear. Here we identify RhoA as a target of activated PKGIα and show further that PKGIα binds directly to RhoA, inhibiting its activation and translocation. In protein pulldown and immunoprecipitation experiments, binding of RhoA and PKGIα was demonstrated via a direct interaction between the amino terminus of RhoA (residues 1–44), containing the switch I domain of RhoA, and the amino terminus of PKGIα (residues 1–59), which includes a leucine zipper heptad repeat motif. Affinity assays using cGMP-immobilized agarose showed that only activated PKGIα binds RhoA, and a leucine zipper mutant PKGIα was unable to bind RhoA even if activated. Furthermore, a catalytically inactive mutant of PKGIα bound RhoA but did not prevent RhoA activation and translocation. Collectively, these results support that RhoA is a PKGIα target and that direct binding of activated PKGIα to RhoA is central to cGMP-mediated inhibition of the VSMC Rho kinase contractile pathway.     

Evolution of the Integrin α and β Protein Families

A phylogenetic analysis of vertebrate and invertebrate α integrins supported the hypothesis that two major families of vertebrate α integrins originated prior to the divergence of deuterostomes and protostomes. These two families include, respectively, the αPS1 and αPS2 integrins of Drosophila melanogaster, and each family has duplicated repeatedly in vertebrates but not in Drosophila. In contrast, a third family (including αPS3) has duplicated in Drosophila but is absent from vertebrates. Vertebrate αPS1 and αPS2 family members are found on human chromosomes 2, 12, and 17. Linkage of these family members may have been conserved since prior to the origin of vertebrates, and the two genes duplicated simultaneously. A phylogenetic analysis of β integrins did not clearly resolve whether vertebrate β integrin genes duplicated prior to the origin of vertebrates, although it suggested that at least the gene encoding vertebrate β4 may have done so. In general, the phylogeny of neither α nor β integrins showed a close correspondence with patterns of α–β heterodimer formation or other functional characteristics. One major exception to this trend involved αL, αM, αX, and αD, a monophyletic group of immune cell-expressed α integrins, which share a number of common functional characteristics and have evolved in coordinated fashion with their β integrin partners. Received: 22 June 2000 / Accepted: 11 September 2000     

Computational Prediction of Protein–Protein Interactions

Recently a number of computational approaches have been developed for the prediction of protein–protein interactions. Complete genome sequencing projects have provided the vast amount of information needed for these analyses. These methods utilize the structural, genomic, and biological context of proteins and genes in complete genomes to predict protein interaction networks and functional linkages between proteins. Given that experimental techniques remain expensive, time-consuming, and labor-intensive, these methods represent an important advance in proteomics. Some of these approaches utilize sequence data alone to predict interactions, while others combine multiple computational and experimental datasets to accurately build protein interaction maps for complete genomes. These methods represent a complementary approach to current high-throughput projects whose aim is to delineate protein interaction maps in complete genomes. We will describe a number of computational protocols for protein interaction prediction based on the structural, genomic, and biological context of proteins in complete genomes, and detail methods for protein interaction network visualization and analysis.     

Protein Homeostasis, Aging and Alzheimer’s Disease

Alzheimer's disease (AD) is one key medical challenge of the aging society and despite a great amount of effort and a huge collection of acquired data on molecular mechanisms that are associated with the onset and progression of this devastating disorder, no causal therapy is in sight. The two main hypotheses of AD, the amyloid cascade hypothesis and the Tau hypothesis, are still in the focus of AD research. With aging as the accepted main risk factor of the most important non familial and late onset sporadic forms of AD, it is now mandatory to discuss more intensively aspects of cellular aging and aging biochemistry and its impact on neurodegeneration. Since aging is accompanied by changes in cellular protein homeostasis and an increasing demand for protein degradation, aspects of protein folding, misfolding, refolding and, importantly, protein degradation need to be linked to AD pathogenesis. This is the purpose of this short review.     

MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein–Protein Network Mapping

Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO, to deduce Gene Ontology attributes of proteins by combining sequence homology-based annotation with low-resolution structure prediction and comparison, and partner's homology-based protein–protein network mapping. The pipeline was tested on a large-scale set of 1000 non-redundant proteins from the CAFA3 experiment. Under the stringent benchmark conditions where templates with > 30% sequence identity to the query are excluded, MetaGO achieves average F-measures of 0.487, 0.408, and 0.598, for Molecular Function, Biological Process, and Cellular Component, respectively, which are significantly higher than those achieved by other state-of-the-art function annotations methods. Detailed data analysis shows that the major advantage of the MetaGO lies in the new functional homolog detections from partner's homology-based network mapping and structure-based local and global structure alignments, the confidence scores of which can be optimally combined through logistic regression. These data demonstrate the power of using a hybrid model incorporating protein structure and interaction networks to deduce new functional insights beyond traditional sequence homology-based referrals, especially for proteins that lack homologous function templates. The MetaGO pipeline is available at http://zhanglab.ccmb.med.umich.edu/MetaGO/.     

Characterization of Group A Streptococcal M23 Protein and Comparison of the M3 and M23 Protein’s Ligand-Binding Domains

The present study concerns the properties for binding of human plasma and extracellular matrix proteins and the relationship between M3 and M23 molecules. Here, it is demonstrated that M23 protein shows a multiple binding to fibrinogen (FG), fibronectin (FN), human serum albumin (HSA), immunoglobulin G (IgG), kininogen, and collagen type I (CI) in Western blot analysis. Some sets of truncated-recombinant M3 or M23 protein fragments were assayed for their capacity to bind FN, FG, IgG, HSA, and CI. The HSA binding activity resided in the C-repeat region of M3 protein, whereas fibrinogen-binding activity resided in the A-repeat region. The FG, FN, and IgG binding sites were mapped to the N-terminal portion of M23 protein, whereas HSA binding was localized in the B-repeat domain, which has homology with C-repeat domain in M3 molecule. Therefore, it is concluded that the FN, FG, and IgG binding regions in the M3 and M23 proteins are quite dissimilar at the amino acid sequence level, whereas HSA binding is localized to the conserved C-repeat domain in the M3 and M23 proteins.     

Role of Molecular Chaperones in G Protein ��5/Regulator of G Protein Signaling Dimer Assembly and G Protein �¦� Dimer Specificity

The G protein βγ subunit dimer (Gβγ) and the Gβ5/regulator of G protein signaling (RGS) dimer play fundamental roles in propagating and regulating G protein pathways, respectively. How these complexes form dimers when the individual subunits are unstable is a question that has remained unaddressed for many years. In the case of Gβγ, recent studies have shown that phosducin-like protein 1 (PhLP1) works as a co-chaperone with the cytosolic chaperonin complex (CCT) to fold Gβ and mediate its interaction with Gγ. However, it is not known what fraction of the many Gβγ combinations is assembled this way or whether chaperones influence the specificity of Gβγ dimer formation. Moreover, the mechanism of Gβ5-RGS assembly has yet to be assessed experimentally. The current study was undertaken to directly address these issues. The data show that PhLP1 plays a vital role in the assembly of Gγ2 with all four Gβ1–4 subunits and in the assembly of Gβ2 with all twelve Gγ subunits, without affecting the specificity of the Gβγ interactions. The results also show that Gβ5-RGS7 assembly is dependent on CCT and PhLP1, but the apparent mechanism is different from that of Gβγ. PhLP1 seems to stabilize the interaction of Gβ5 with CCT until Gβ5 is folded, after which it is released to allow Gβ5 to interact with RGS7. These findings point to a general role for PhLP1 in the assembly of all Gβγ combinations and suggest a CCT-dependent mechanism for Gβ5-RGS7 assembly that utilizes the co-chaperone activity of PhLP1 in a unique way.Eukaryotic cells utilize receptors coupled to heterotrimeric GTP-binding proteins (G proteins)³ to mediate a vast array of responses ranging from nutrient-induced migration of single-celled organisms to neurotransmitter-regulated neuronal activity in the human brain (1). Ligand binding to a G protein-coupled receptor (GPCR) initiates GTP exchange on the G protein heterotrimer (composed of Gα, Gβ, and Gγ subunits), which in turn causes the release of Gα-GTP from the Gβγ dimer (2–4). Both Gα-GTP and Gβγ propagate and amplify the signal by interacting with effector enzymes and ion channels (1, 5). The duration and amplitude of the signal is dictated by receptor phosphorylation coupled with arrestin binding and internalization (6) and by regulators of G protein signaling (RGS) proteins, which serve as GTPase-activating proteins for the GTP-bound Gα subunit (7, 8). The G protein signaling cycle is reset as the inactive Gα-GDP reassembles with the Gβγ dimer and Gαβγ re-associates with the GPCR (5).To fulfill its essential role in signaling, the G protein heterotrimer must be assembled post-translationally from its nascent polypeptides. Significant progress has been made recently regarding the mechanism by which this process occurs. It has been clear for some time that the Gβγ dimer must assemble first, followed by subsequent association of Gα with Gβγ (9). What has not been clear was how Gβγ assembly would occur given the fact that neither Gβ nor Gγ is structurally stable without the other. An important breakthrough was the finding that phosducin-like protein 1 (PhLP1) functions as a co-chaperone with the chaperonin containing tailless complex polypeptide 1 (CCT) in the folding of nascent Gβ and its association with Gγ (10–15). CCT is an important chaperone that assists in the folding of actin and tubulin and many other cytosolic proteins, including many β propeller proteins like Gβ (16). PhLP1 has been known for some time to interact with Gβγ and was initially believed to inhibit Gβγ function (17). However, several recent studies have demonstrated that PhLP1 and CCT work together in a highly orchestrated manner to form the Gβγ dimer (10–15).Studies on the mechanism of PhLP1-mediated Gβγ assembly have focused on the most common dimer Gβ1γ2 (10, 13, 14), leaving open questions about the role of PhLP1 in the assembly of the other Gβγ combinations. These are important considerations given that humans possess 5 Gβ genes and 12 Gγ genes with some important splice variants (18, 19), resulting in more than 60 possible combinations of Gβγ dimers. Gβ1–4 share between 80 and 90% sequence identity and are broadly expressed (18, 19). Gβ5, the more atypical isoform, shares only ∼53% identity with Gβ1, carries a longer N-terminal domain, and is only expressed in the central nervous system and retina (20). The Gγ protein family is more heterogeneous than the Gβ family. The sequence identity of the 12 Gγ isoforms extends from 10 to 70% (21), and the Gγ family can be separated into 5 subfamilies (21–23). All Gγ proteins carry C-terminal isoprenyl modifications, which contribute to their association with the cell membrane, GPCRs, Gαs, and effectors (9). Subfamily I Gγ isoforms are post-translationally farnesylated, whereas all others are geranylgeranylated (22, 24).There is some inherent selectivity in the assembly of different Gβγ combinations, but in general Gβ1–4 can form dimers with most Gγ subunits (25). The physiological purpose of this large number of Gβγ combinations has intrigued researchers in the field for many years, and a large body of research indicates that GPCRs and effectors couple to a preferred subset of Gβγ combinations based somewhat on specific sequence complementarity, but even more so on cellular expression patterns, subcellular localization, and post-translational modifications (18).In contrast to Gβ1–4, Gβ5 does not interact with Gγ subunits in vivo, but it instead forms irreversible dimers with RGS proteins of the R7 family, which includes RGS proteins 6, 7, 9, and 11 (26). All R7 family proteins contain an N-terminal DEP (disheveled, Egl-10, pleckstrin) domain, a central Gγ-like (GGL) domain, and a C-terminal RGS domain (8, 26). The DEP domain interacts with the membrane anchoring/nuclear shuttling R7-binding protein, and the GGL domain binds to Gβ5 in a manner similar to other Gβγ associations (27, 28). Like Gβγs, Gβ5 and R7 RGS proteins form obligate dimers required for their mutual stability (26). Without their partner, Gβ5 and R7 RGS proteins are rapidly degraded in cells (26, 29). Gβ5-R7 RGS complexes act as important GTPase-accelerating proteins for G_i/oα and G_qα subunits in neuronal cells and some immune cells (26).It has been recently shown that all Gβ isoforms are able to interact with the CCT complex, but to varying degrees (15). Gβ4 and Gβ1 bind CCT better than Gβ2 and Gβ3, whereas Gβ5 binds CCT poorly (15). These results suggest that Gβ1 and Gβ4 might be more dependent on PhLP1 than the other Gβs, given the co-chaperone role of PhLP1 with CCT in Gβ1γ2 assembly. However, another report has indicated that Gγ2 assembly with Gβ1 and Gβ2 is more PhLP1-dependent than with Gβ3 and Gβ4 (30). Thus, it is not clear from current information whether PhLP1 and CCT participate in assembly of all Gβγ combinations or whether they contribute to the specificity of Gβγ dimer formation, nor is it clear whether they or other chaperones are involved in Gβ5-R7 RGS dimer formation. This report was designed to address these issues.