Enzyme/non-enzyme discrimination and prediction of enzyme active site location using charge-based methods

Calculations of charge interactions complement analysis of a characterised active site, rationalising pH-dependence of activity and transition state stabilisation. Prediction of active site location through large DeltapK(a)s or electrostatic strain is relevant for structural genomics. We report a study of ionisable groups in a set of 20 enzymes, finding that false positives obscure predictive potential. In a larger set of 156 enzymes, peaks in solvent-space electrostatic properties are calculated. Both electric field and potential match well to active site location. The best correlation is found with electrostatic potential calculated from uniform charge density over enzyme volume, rather than from assignment of a standard atom-specific charge set. Studying a shell around each molecule, for 77% of enzymes the potential peak is within that 5% of the shell closest to the active site centre, and 86% within 10%. Active site identification by largest cleft, also with projection onto a shell, gives 58% of enzymes for which the centre of the largest cleft lies within 5% of the active site, and 70% within 10%. Dielectric boundary conditions emphasise clefts in the uniform charge density method, which is suited to recognition of binding pockets embedded within larger clefts. The variation of peak potential with distance from active site, and comparison between enzyme and non-enzyme sets, gives an optimal threshold distinguishing enzyme from non-enzyme. We find that 87% of the enzyme set exceeds the threshold as compared to 29% of the non-enzyme set. Enzyme/non-enzyme homologues, "structural genomics" annotated proteins and catalytic/non-catalytic RNAs are studied in this context.     

Predicting protein interaction sites: binding hot-spots in protein-protein and protein-ligand interfaces

MOTIVATION: Protein assemblies are currently poorly represented in structural databases and their structural elucidation is a key goal in biology. Here we analyse clefts in protein surfaces, likely to correspond to binding 'hot-spots', and rank them according to sequence conservation and simple measures of physical properties including hydrophobicity, desolvation, electrostatic and van der Waals potentials, to predict which are involved in binding in the native complex. RESULTS: The resulting differences between predicting binding-sites at protein-protein and protein-ligand interfaces are striking. There is a high level of prediction accuracy (< or =93%) for protein-ligand interactions, based on the following attributes: van der Waals potential, electrostatic potential, desolvation and surface conservation. Generally, the prediction accuracy for protein-protein interactions is lower, with the exception of enzymes. Our results show that the ease of cleft desolvation is strongly predictive of interfaces and strongly maintained across all classes of protein-binding interface.     

A method for localizing ligand binding pockets in protein structures

The accurate identification of ligand binding sites in protein structures can be valuable in determining protein function. Once the binding site is known, it becomes easier to perform in silico and experimental procedures that may allow the ligand type and the protein function to be determined. For example, binding pocket shape analysis relies heavily on the correct localization of the ligand binding site. We have developed SURFNET-ConSurf, a modular, two-stage method for identifying the location and shape of potential ligand binding pockets in protein structures. In the first stage, the SURFNET program identifies clefts in the protein surface that are potential binding sites. In the second stage, these clefts are trimmed in size by cutting away regions distant from highly conserved residues, as defined by the ConSurf-HSSP database. The largest clefts that remain tend to be those where ligands bind. To test the approach, we analyzed a nonredundant set of 244 protein structures from the PDB and found that SURFNET-ConSurf identifies a ligand binding pocket in 75% of them. The trimming procedure reduces the original cleft volumes by 30% on average, while still encompassing an average 87% of the ligand volume. From the analysis of the results we conclude that for those cases in which the ligands are found in large, highly conserved clefts, the combined SURFNET-ConSurf method gives pockets that are a better match to the ligand shape and location. We also show that this approach works better for enzymes than for nonenzyme proteins.     

Strategies to search and design stabilizers of protein-protein interactions: a feasibility study

Since protein-protein interactions play a pivotal role in the communication on the molecular level in virtually every biological system and process, the search and design for modulators of such interactions is of utmost importance. In recent years many inhibitors for specific protein-protein interactions have been developed, however, in only a few cases, small and druglike molecules are able to interfere in the complex formation of proteins. On the other hand, there are several small molecules known to modulate protein-protein interactions by means of stabilizing an already assembled complex. To achieve this goal, a ligand is binding to a pocket, which is located rim-exposed at the interface of the interacting proteins, for example as the phytotoxin Fusicoccin, which stabilizes the interaction of plant H+-ATPase and 14-3-3 protein by nearly a factor of 100. To suggest alternative leads, we performed a virtual screening campaign to discover new molecules putatively stabilizing this complex. Furthermore, we screen a dataset of 198 transient recognition protein-protein complexes for cavities, which are located rim-exposed at their interfaces. We provide evidence for high similarity between such rim-exposed cavities and usual ligands accommodating active sites of enzymes. This analysis suggests that rim-exposed cavities at protein-protein interfaces are druggable binding sites. Therefore, the principle of stabilizing protein-protein interactions seems to be a promising alternative to the approach of the competitive inhibition of such interactions by small molecules.     

Residue centrality, functionally important residues, and active site shape: analysis of enzyme and non-enzyme families

The representation of protein structures as small-world networks facilitates the search for topological determinants, which may relate to functionally important residues. Here, we aimed to investigate the performance of residue centrality, viewed as a family fold characteristic, in identifying functionally important residues in protein families. Our study is based on 46 families, including 29 enzyme and 17 non-enzyme families. A total of 80% of these central positions corresponded to active site residues or residues in direct contact with these sites. For enzyme families, this percentage increased to 91%, while for non-enzyme families the percentage decreased substantially to 48%. A total of 70% of these central positions are located in catalytic sites in the enzyme families, 64% are in hetero-atom binding sites in those families binding hetero-atoms, and only 16% belong to protein-protein interfaces in families with protein-protein interaction data. These differences reflect the active site shape: enzyme active sites locate in surface clefts, hetero-atom binding residues are in deep cavities, while protein-protein interactions involve a more planar configuration. On the other hand, not all surface cavities or clefts are comprised of central residues. Thus, closeness centrality identifies functionally important residues in enzymes. While here we focus on binding sites, we expect to identify key residues for the integration and transmission of the information to the rest of the protein, reflecting the relationship between fold and function. Residue centrality is more conserved than the protein sequence, emphasizing the robustness of protein structures.     

Computational solvent mapping reveals the importance of local conformational changes for broad substrate specificity in mammalian cytochromes P450

Computational solvent mapping moves small organic molecules as probes around a protein surface, finds favorable binding positions, clusters the conformations, and ranks the clusters on the basis of their average free energy. Prior mapping studies of enzymes, crystallized in either substrate-free or substrate-bound form, have shown that the largest number of solvent probe clusters invariably overlaps in the active site. We have applied this method to five cytochromes P450. As expected, the mapping of two bacterial P450s, P450 cam (CYP101) and P450 BM-3 (CYP102), identified the substrate-binding sites in both ligand-bound and ligand-free P450 structures. However, the mapping finds the active site only in the ligand-bound structures of the three mammalian P450s, 2C5, 2C9, and 2B4. Thus, despite the large cavities seen in the unbound structures of these enzymes, the features required for binding small molecules are formed only in the process of substrate binding. The ability of adjusting their binding sites to substrates that differ in size, shape, and polarity is likely to be responsible for the broad substrate specificity of these mammalian P450s. Similar behavior was seen at "hot spots" of protein-protein interfaces that can also bind small molecules in grooves created by induced fit. In addition, the binding of S-warfarin to P450 2C9 creates a high-affinity site for a second ligand, which may help to explain the prevalence of drug-drug interactions involving this and other mammalian P450s.     

Comparison of protein-protein interactions in serine protease-inhibitor and antibody-antigen complexes: implications for the protein docking problem

The protein-protein interaction energy of 12 nonhomologous serine protease-inhibitor and 15 antibody-antigen complexes is calculated using a molecular mechanics formalism and dissected in terms of the main-chain vs. side-chain contribution, nonrotameric side-chain contributions, and amino acid residue type involvement in the interface interaction. There are major differences in the interactions of the two types of protein-protein complex. Protease-inhibitor complexes interact predominantly through a main-chain-main-chain mechanism while antibody-antigen complexes interact predominantly through a side-chain-side-chain or a side-chain-main-chain mechanism. However, there is no simple correlation between the main-chain-main-chain interaction energy and the percentage of main-chain surface area buried on binding. The interaction energy is equally effected by the presence of nonrotameric side-chain conformations, which constitute approximately 20% of the interaction energy. The ability to reproduce the interface interaction energy of the crystal structure if original side-chain conformations are removed from the calculation is much greater in the protease-inhibitor complexes than the antibody-antigen complexes. The success of a rotameric model for protein-protein docking appears dependent on the extent of the main-chain-main-chain contribution to binding. Analysis of (1) residue type and (2) residue pair interactions at the interface show that antibody-antigen interactions are very restricted with over 70% of the antibody energy attributable to just six residue types (Tyr > Asp > Asn > Ser > Glu > Trp) in agreement with previous studies on residue propensity. However, it is found here that 50% of the antigen energy is attributable to just four residue types (Arg = Lys > Asn > Asp). On average just 12 residue pair interactions (6%) contribute over 40% of the favorable interaction energy in the antibody-antigen complexes, with charge-charge and charge/polar-tyrosine interactions being prominent. In contrast protease inhibitors use a diverse set of residue types and residue pair interactions.     

Peptides that inhibit HIV-1 integrase by blocking its protein-protein interactions

HIV-1 integrase (IN) is one of the key enzymes in the viral replication cycle. It mediates the integration of viral cDNA into the host cell genome. IN activity requires interactions with several viral and cellular proteins, as well as IN oligomerization. Inhibition of IN is an important target for the development of anti-HIV therapies, but there is currently only one anti-HIV drug used in the clinic that targets IN. Several other small-molecule anti-IN drug leads are either undergoing clinical trials or in earlier stages of development. These molecules specifically inhibit one of the IN-mediated reactions necessary for successful integration. However, small-molecule inhibitors of protein-protein interactions are difficult to develop. In this review, we focus on peptides that inhibit IN. Peptides have advantages over small-molecule inhibitors of protein-protein interactions: they can mimic the structures of the binding domains within proteins, and are large enough to competitively inhibit protein-protein interactions. The development of peptides that bind IN and inhibit its protein-protein interactions will increase our understanding of the IN mode of action, and lead to the development of new drug leads, such as small molecules derived from these peptides, for better anti-HIV therapy.     

Examining multiprotein signaling complexes from all angles

Dynamic protein-protein interactions are involved in most physiological processes and, in particular, for the formation of multiprotein signaling complexes at transmembrane receptors, adapter proteins and effector molecules. Because the unregulated induction of signaling complexes has substantial clinical relevance, the investigation of these complexes is an active area of research. These studies strive to answer questions about the composition and function of multiprotein signaling complexes, along with the molecular mechanisms of their formation. In this review, the adapter protein, linker for activation of T cells (LAT), will be employed as a model to exemplify how signaling complexes are characterized using a range of techniques. The intensive investigation of LAT highlights how the systematic use of complementary techniques leads to an integrated understanding of the formation, composition and function of multiprotein signaling complexes that occur at receptors, adapter proteins and effector molecules.     

The use of immobilized ubiquitin for biosensor analysis of the mitochondrial subinteractome

Protein ubiquitination is an important mechanism responsible not only for specific labeling of proteins for their subsequent degradation; it also determines localization of proteins in the cell and regulation of protein-protein interactions. In the context of protein-protein interactions binding of (mono/poly)ubiquitinated molecules to proteins containing specific ubiquitin binding domains plays the decisive role. Formation of the ubiquitin interactome has been demonstrated for cytosol. Involvement of mitochondria and associated extramitochondrial proteins into such interactions still requires detailed investigation. In this study using an optical biosensor we have demonstrated binding of proteins of mouse brain mitochondrial lysates to immobilized monomeric ubiquitin. Model purified proteins, which are known to be associated with the outer mitochondrial compartment (glyceraldehyde-3-phosphate dehydorgenase, creatine phosphokinase), interacted with immobilized ubiquitin as well as with each other. This suggests that (poly)ubiquitinated chains may be involved in protein-protein interactions between ubiquitinated and non-ubiquitinated proteins and thus may contribute to formation of (mitochondrial) ubiquitin subinteractome.     

Analysis of protein-protein interaction by simulation of small-zone size-exclusion chromatography: application to an antibody-antigen association

The association of two or more macromolecules results in the formation of a complex characterized by a larger Stokes radius than that of its components. Therefore, analytical procedures such as ultracentrifugation and size-exclusion gel chromatography that resolve molecules on the basis of size have been used to characterize the association. In this paper we describe an iterative computer simulation of small-zone size-exclusion gel filtration. The simulation describes univalent and bivalent interactions of proteins of equal and nonequal molecular weight and appears to have both qualitative and quantitative application to the evaluation of protein-protein interaction as revealed by alteration of chromatographic elution profiles. To test the validity of the simulation, the model was applied to an antibody-antigen interaction by determining the association constant (Ka) for the interaction between the binding fragment derived from a human immunoglobulin A rheumatoid factor and the antigenic fragment obtained from a human myeloma immunoglobulin G. The self-consistency of the estimated Ka values obtained with a valence value of 2 in contrast to the lack of self-consistency if an antigenic valence of 1 was assumed was taken to support the ability of the algorithm to reasonably emulate the chromatographic processes of interacting proteins. In conjunction with the computer simulation, a sensitive microcomputer-interfaced chromatography system was assembled, which is capable of analyzing 300 ng of protein in less than 1 h. This combination of rapid reagent-conservative chromatography and simulation analysis may contribute to the usefulness of small-zone gel filtration in studies of protein-protein interaction.     

Readout of protein microarrays using intrinsic time resolved UV fluorescence for label-free detection

Detecting protein-protein interactions other than those of antibody-antigen pairs still represents a demanding and tedious task. In the present work, a novel method as an alternative to current molecular biology-based detection procedures is established. It solely relies on the change of fluorescence decay times of the protein's intrinsic fluorophores tryptophan and tyrosine due to protein-protein interaction. Unlike previously utilized related methods, no labelling of the binding partners is required. This opens the possibility to detect proteins and their natural interactions without perturbation due to chemical alteration. The technique uses immobilization of one of the protein partners onto solid supports, which allows performance of protein binding studies in the microarray format. Fluorescence lifetime experiments of proteins in their different binding states have been applied to protease/protease-substrate pairs, as well as to the tubulin/kinesin system. Different binding behavior of proteins in solution towards protein partners immobilized on protein microarrays was detected with regard to binding specificity and protein amount. This label-free method for analyzing protein microarrays offers broad applicability ranging from principal investigations of protein interactions to applications in molecular biology and medicine.     

Catalysis by a de novo zinc-mediated protein interface: implications for natural enzyme evolution and rational enzyme engineering

Here we show that a recent computationally designed zinc-mediated protein interface is serendipitously capable of catalyzing carboxyester and phosphoester hydrolysis. Although the original motivation was to design a de novo zinc-mediated protein-protein interaction (called MID1-zinc), we observed in the homodimer crystal structure a small cleft and open zinc coordination site. We investigated if the cleft and zinc site at the designed interface were sufficient for formation of a primitive active site that can perform hydrolysis. MID1-zinc hydrolyzes 4-nitrophenyl acetate with a rate acceleration of 10(5) and a k(cat)/K(M) of 630 M(-1) s(-1) and 4-nitrophenyl phosphate with a rate acceleration of 10(4) and a k(cat)/K(M) of 14 M(-1) s(-1). These rate accelerations by an unoptimized active site highlight the catalytic power of zinc and suggest that the clefts formed by protein-protein interactions are well-suited for creating enzyme active sites. This discovery has implications for protein evolution and engineering: from an evolutionary perspective, three-coordinated zinc at a homodimer interface cleft represents a simple evolutionary path to nascent enzymatic activity; from a protein engineering perspective, future efforts in de novo design of enzyme active sites may benefit from exploring clefts at protein interfaces for active site placement.     

I-type lectins

The immunoglobulin superfamily is a large category of proteins defined by their structural similarity to immunoglobulins. The majority of these proteins are involved in protein-protein binding as receptors, antibodies or cell adhesion molecules. The I-type lectins are a subset of the immunoglobulin superfamily that are capable of carbohydrate-protein interactions. There are I-type lectins recognizing sialic acids, other sugars and glycosaminoglycans. The occurrence, structure, binding properties and (potential) biological functions of the I-type lectins are reviewed here.     

Specificity of molecular interactions in transient protein-protein interaction interfaces

In this study, we investigate what types of interactions are specific to their biological function, and what types of interactions are persistent regardless of their functional category in transient protein-protein heterocomplexes. This is the first approach to analyze protein-protein interfaces systematically at the molecular interaction level in the context of protein functions. We perform systematic analysis at the molecular interaction level using classification and feature subset selection technique prevalent in the field of pattern recognition. To represent the physicochemical properties of protein-protein interfaces, we design 18 molecular interaction types using canonical and noncanonical interactions. Then, we construct input vector using the frequency of each interaction type in protein-protein interface. We analyze the 131 interfaces of transient protein-protein heterocomplexes in PDB: 33 protease-inhibitors, 52 antibody-antigens, 46 signaling proteins including 4 cyclin dependent kinase and 26 G-protein. Using kNN classification and feature subset selection technique, we show that there are specific interaction types based on their functional category, and such interaction types are conserved through the common binding mechanism, rather than through the sequence or structure conservation. The extracted interaction types are C(alpha)-- H...O==C interaction, cation...anion interaction, amine...amine interaction, and amine...cation interaction. With these four interaction types, we achieve the classification success rate up to 83.2% with leave-one-out cross-validation at k = 15. Of these four interaction types, C(alpha)--H...O==C shows binding specificity for protease-inhibitor complexes, while cation-anion interaction is predominant in signaling complexes. The amine ... amine and amine...cation interaction give a minor contribution to the classification accuracy. When combined with these two interactions, they increase the accuracy by 3.8%. In the case of antibody-antigen complexes, the sign is somewhat ambiguous. From the evolutionary perspective, while protease-inhibitors and sig-naling proteins have optimized their interfaces to suit their biological functions, antibody-antigen interactions are the happenstance, implying that antibody-antigen complexes do not show distinctive interaction types. Persistent interaction types such as pi...pi, amide-carbonyl, and hydroxyl-carbonyl interaction, are also investigated. Analyzing the structural orientations of the pi...pi stacking interactions, we find that herringbone shape is a major configuration in transient protein-protein interfaces. This result is different from that of protein core, where parallel-displaced configurations are the major configuration. We also analyze overall trend of amide-carbonyl and hydroxyl-carbonyl interactions. It is noticeable that nearly 82% of the interfaces have at least one hydroxyl-carbonyl interactions.     

Binding interactions between the active center cleft of recombinant pokeweed antiviral protein and the alpha-sarcin/ricin stem loop of ribosomal RNA

Pokeweed antiviral protein (PAP) is a ribosome-inactivating protein that catalytically cleaves a specific adenine base from the highly conserved alpha-sarcin/ricin loop of the large ribosomal RNA, thereby inhibiting protein synthesis at the elongation step. Recently, we discovered that alanine substitutions of the active center cleft residues significantly impair the depurinating and ribosome inhibitory activity of PAP. Here we employed site-directed mutagenesis combined with standard filter binding assays, equilibrium binding assays with Scatchard analyses, and surface plasmon resonance technology to elucidate the putative role of the PAP active center cleft in the binding of PAP to the alpha-sarcin/ricin stem loop of rRNA. Our findings presented herein provide experimental evidence that besides the catalytic site, the active center cleft also participates in the binding of PAP to the target tetraloop structure of rRNA. These results extend our recent modeling studies, which predicted that the residues of the active center cleft could, via electrostatic interactions, contribute to both the correct orientation and stable binding of the substrate RNA molecules in PAP active site pocket. The insights gained from this study also explain why and how the conserved charged and polar side chains located at the active center cleft of PAP and certain catalytic site residues, that do not directly participate in the catalytic deadenylation of ribosomal RNA, play a critical role in the catalytic removal of the adenine base from target rRNA substrates by affecting the binding interactions between PAP and rRNA.     

Structure and mechanism of metallocarboxypeptidases

Metallocarboxpeptidases cleave C-terminal residues from peptide substrates and participate in a wide range of physiological processes, but they also contribute to human pathology. On the basis of structural information, we can distinguish between two groups of such metallopeptidases: cowrins and funnelins. Cowrins comprise protozoan, prokaryotic, and mammalian enzymes related to both neurolysin and angiotensin-converting enzyme and their catalytic domains contain 500-700 residues. They are ellipsoidal and traversed horizontally by a long, deep, narrow active-site cleft, in which the C-terminal residues are cut from oligopeptides and unstructured protein tails. The consensus cowrin structure contains a common core of 17 helices and a three-stranded beta-sheet, which participates in substrate binding. This protease family is characterized by a set of spatially conserved amino acids involved in catalysis, HEXXH+EXXS/G+H+Y/R+Y. Funnelins comprise structural relatives of the archetypal bovine carboxypeptidase A1 and feature mammalian, insect and bacterial proteins with strict carboxypeptidase activity. Their approximately 300-residue catalytic domains evince a consensus central eight-stranded beta-sheet flanked on either side by a total of eight helices. They also contain a characteristic set of conserved residues, HXXE+R+NR+H+Y+E, and their active-site clefts are rather shallow and lie at the bottom of a funnel-like cavity. Therefore, these enzymes act on a large variety of well-folded proteins. In both cowrins and funnelins, substrate hydrolysis follows a common general base/acid mechanism. A metal-bound solvent molecule ultimately performs the attack on the scissile peptide bond with the assistance of a strictly conserved glutamate residue.