Artificial protein cavities as specific ligand-binding templates: characterization of an engineered heterocyclic cation-binding site that preserves the evolved specificity of the parent protein.

Cavity complementation has been observed in many proteins, where an appropriate small molecule binds to a cavity-forming mutant. Here, the binding of compounds to the W191G cavity mutant of cytochrome c peroxidase is characterized by X-ray crystallography and binding thermodynamics. Unlike cavities created by removal of hydrophobic side-chains, the W191G cavity does not bind neutral or hydrophobic compounds, but displays a strong specificity for heterocyclic cations, consistent with the role of the protein to stabilize a tryptophan radical at this site. Ligand dissociation constants for the protonated cationic state ranged from 6 microM for 2-amino-5-methylthiazole to 1 mM for neutral ligands, and binding was associated with a large enthalpy-entropy compensation. X-ray structures show that each of 18 compounds with binding behavior bind specifically within the artificial cavity and not elsewhere in the protein. The compounds make multiple hydrogen bonds to the cavity walls using a subset of the interactions seen between the protein and solvent in the absence of ligand. For all ligands, every atom that is capable of making a hydrogen bond does so with either protein or solvent. The most often seen interaction is to Asp235, and most compounds bind with a specific orientation that is defined by their ability to interact with this residue. Four of the ligands do not have conventional hydrogen bonding atoms, but were nevertheless observed to orient their most polar CH bond towards Asp235. Two of the larger ligands induce disorder in a surface loop between Pro190 and Asn195 that has been identified as a mobile gate to cavity access. Despite the predominance of hydrogen bonding and electrostatic interactions, the small variation in observed binding free energies were not correlated readily with the strength, type or number of hydrogen bonds or with calculated electrostatic energies alone. Thus, as with naturally occurring binding sites, affinities to W191G are likely to be due to a subtle balance of polar, non-polar, and solvation terms. These studies demonstrate how cavity complementation and judicious choice of site can be used to produce a protein template with an unusual ligand-binding specificity.     

Structure, function, and evolution of biogenic amine-binding proteins in soft ticks

Two highly abundant lipocalins, monomine and monotonin, have been isolated from the salivary gland of the soft tick Argas monolakensis and shown to bind histamine and 5-hydroxytryptamine (5-HT), respectively. The crystal structures of monomine and a paralog of monotonin were determined in the presence of ligands to compare the determinants of ligand binding. Both the structures and binding measurements indicate that the proteins have a single binding site rather than the two sites previously described for the female-specific histamine-binding protein (FS-HBP), the histamine-binding lipocalin of the tick Rhipicephalus appendiculatus. The binding sites of monomine and monotonin are similar to the lower, low affinity site of FS-HBP. The interaction of the protein with the aliphatic amine group of the ligand is very similar for the all of the proteins, whereas specificity is determined by interactions with the aromatic portion of the ligand. Interestingly, protein interaction with the imidazole ring of histamine differs significantly between the low affinity binding site of FS-HBP and monomine, suggesting that histamine binding has evolved independently in the two lineages. From the conserved features of these proteins, a tick lipocalin biogenic amine-binding motif could be derived that was used to predict biogenic amine-binding function in other tick lipocalins. Heterologous expression of genes from salivary gland libraries led to the discovery of biogenic amine-binding proteins in soft (Ornithodoros) and hard (Ixodes) tick genera. The data generated were used to reconstruct the most probable evolutionary pathway for the evolution of biogenic amine-binding in tick lipocalins.     

Hidden partners: Using cross‐docking calculations to predict binding sites for proteins with multiple interactions

Protein‐protein interactions control a large range of biological processes and their identification is essential to understand the underlying biological mechanisms. To complement experimental approaches, in silico methods are available to investigate protein‐protein interactions. Cross‐docking methods, in particular, can be used to predict protein binding sites. However, proteins can interact with numerous partners and can present multiple binding sites on their surface, which may alter the binding site prediction quality. We evaluate the binding site predictions obtained using complete cross‐docking simulations of 358 proteins with 2 different scoring schemes accounting for multiple binding sites. Despite overall good binding site prediction performances, 68 cases were still associated with very low prediction quality, presenting individual area under the specificity‐sensitivity ROC curve (AUC) values below the random AUC threshold of 0.5, since cross‐docking calculations can lead to the identification of alternate protein binding sites (that are different from the reference experimental sites). For the large majority of these proteins, we show that the predicted alternate binding sites correspond to interaction sites with hidden partners, that is, partners not included in the original cross‐docking dataset. Among those new partners, we find proteins, but also nucleic acid molecules. Finally, for proteins with multiple binding sites on their surface, we investigated the structural determinants associated with the binding sites the most targeted by the docking partners.     

"Acceptor-donor-acceptor" motifs recognize the Watson-Crick, Hoogsteen and Sugar "donor-acceptor-donor" edges of adenine and adenosine-containing ligands

Nucleotides are among the most extensively exploited chemical moieties in nature and, as a part of a handful of different protein ligands, nucleotides play key roles in energy transduction, enzymatic catalysis and regulation of protein function. We have previously reported that in many proteins with different folds and functions a distinctive adenine-binding motif is involved in the recognition of the Watson-Crick edge of adenine. Here, we show that many proteins do have clear structural motifs that recognize adenosine (and some other nucleotides and nucleotide analogs) not only through the Watson-Crick edge, but also through the sugar and Hoogsteen edges. Each of the three edges of adenosine has a donor-acceptor-donor (DAD) pattern that is often recognized by proteins via a complementary acceptor-donor-acceptor (ADA) motif, whereby three distinct hydrogen bonds are formed: two conventional N-H...O and N-H...N hydrogen bonds, and one weak C-H...O hydrogen bond. The local conformation of the adenine-binding loop is betabetabeta or betabetaalpha and reflects the mode of nucleotide binding. Additionally, we report 21 proteins from five different folds that simultaneously recognize both the sugar edge and the Watson-Crick edge of adenine. In these proteins a unique beta-loop-beta supersecondary structure grasps an adenine-containing ligand between two identical adenine-binding motifs as part of the betaalphabeta-loop-beta fold.     

Composite structural motifs of binding sites for delineating biological functions of proteins

Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs that represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures.     

Pre-docking filter for protein and ligand 3D structures

Virtual drug screening using protein-ligand docking techniques is a time-consuming process, which requires high computational power for binding affinity calculation. There are millions of chemical compounds available for docking. Eliminating compounds that are unlikely to exhibit high binding affinity from the screening set should speed-up the virtual drug screening procedure. We performed docking of 6353 ligands against twenty-one protein X-ray crystal structures. The docked ligands were ranked according to their calculated binding affinities, from which the top five hundred and the bottom five hundred were selected. We found that the volume and number of rotatable bonds of the top five hundred docked ligands are similar to those found in the crystal structures and corresponded with the volume of the binding sites. In contrast, the bottom five hundred set contains ligands that are either too large to enter the binding site, or too small to bind with high specificity and affinity to the binding site. A pre-docking filter that takes into account shapes and volumes of the binding sites as well as ligand volumes and flexibilities can filter out low binding affinity ligands from the screening sets. Thus, the virtual drug screening procedure speed is increased.     

Structural basis for the binding of compatible solutes by ProX from the hyperthermophilic archaeon Archaeoglobus fulgidus

Compatible solutes such as glycine betaine and proline betaine serve as protein stabilizers because of their preferential exclusion from protein surfaces. To use extracellular sources of this class of compounds as osmo-, cryo-, or thermoprotectants, Bacteria and Archaea have developed high affinity uptake systems of the ATP-binding cassette type. These transport systems require periplasmic- or extracellular-binding proteins that are able to bind the transported substance with high affinity. Therefore, binding proteins that bind compatible solutes have to avoid the exclusion of their ligands within the binding pocket. In the present study we addressed the question to how compatible solutes can be effectively bound by a protein at temperatures around 83 degrees C as this is done by the ligand-binding protein ProX from the hyperthermophilic archaeon Archaeoglobus fulgidus. We solved the structures of ProX without ligand and in complex with both of its natural ligands glycine betaine and proline betaine, as well as in complex with the artificial ligand trimethylammonium. Cation-pi interactions and non-classical hydrogen bonds between four tyrosine residues, a main chain carbonyl oxygen, and the ligand have been identified to be the key determinants in binding the quaternary amines of the three investigated ligands. The comparison of the ligand binding sites of ProX from A. fulgidus and the recently solved structure of ProX from Escherichia coli revealed a very similar solution for the problem of compatible solute binding, although both proteins share only a low degree of sequence identity. The residues involved in ligand binding are functionally equivalent but not conserved in the primary sequence.     

Altering the binding activity and specificity of the leucine binding proteins of Escherichia coli

Two leucine-binding proteins with overlapping specificities for the branched-chain amino acids are present in Escherichia coli. In order to study the basis of specificity for the very similar hydrophobic ligands, we have constructed a series of site-directed mutants of both proteins based on inspection of the leucine-isoleucine-valine-binding protein crystal structure reported by Sack et al. (Sack, J. S., Saper, M. A., and Quiocho, F. A. (1989) J. Mol. Biol. 206, 171-191). Each of the mutant proteins was overexpressed and purified, and their binding activity for a wide variety of potential ligands was measured. By introducing a common restriction endonuclease cleavage site in the two proteins, two hybrid binding proteins consisting of the amino-terminal third of one binding protein fused to the carboxyl-terminal two-thirds of the other were created. The results of these studies indicated that the binding site of the leucine-isoleucine-valine binding protein can accommodate a branch at the beta-carbon of the ligand and that hydrophilic groups on the ligand can be accommodated only in certain orientations. None of the single amino acid substitutions resulted in complete switches in specificity between the two proteins, suggesting that additional residues are involved in leucine binding and discrimination among the branched-chain amino acid substrates.     

Fast and automated functional classification with MED‐SuMo: An application on purine‐binding proteins

Ligand–protein interactions are essential for biological processes, and precise characterization of protein binding sites is crucial to understand protein functions. MED‐SuMo is a powerful technology to localize similar local regions on protein surfaces. Its heuristic is based on a 3D representation of macromolecules using specific surface chemical features associating chemical characteristics with geometrical properties. MED‐SMA is an automated and fast method to classify binding sites. It is based on MED‐SuMo technology, which builds a similarity graph, and it uses the Markov Clustering algorithm. Purine binding sites are well studied as drug targets. Here, purine binding sites of the Protein DataBank (PDB) are classified. Proteins potentially inhibited or activated through the same mechanism are gathered. Results are analyzed according to PROSITE annotations and to carefully refined functional annotations extracted from the PDB. As expected, binding sites associated with related mechanisms are gathered, for example, the Small GTPases. Nevertheless, protein kinases from different Kinome families are also found together, for example, Aurora‐A and CDK2 proteins which are inhibited by the same drugs. Representative examples of different clusters are presented. The effectiveness of the MED‐SMA approach is demonstrated as it gathers binding sites of proteins with similar structure‐activity relationships. Moreover, an efficient new protocol associates structures absent of cocrystallized ligands to the purine clusters enabling those structures to be associated with a specific binding mechanism. Applications of this classification by binding mode similarity include target‐based drug design and prediction of cross‐reactivity and therefore potential toxic side effects.     

Similar binding sites and different partners: implications to shared proteins in cellular pathways

We studied a data set of structurally similar interfaces that bind to proteins with different binding-site structures and different functions. Our multipartner protein interface clusters enable us to address questions like: What makes a given site bind different proteins? How similar/different are the interactions? And, what drives the apparently less-specific association? We find that proteins with common binding-site motifs preferentially use conserved interactions at similar interface locations, despite the different partners. Helices are major vehicles for binding different partners, allowing alternate ways to achieve favorable association. The binding sites are characterized by imperfect packing, planar architectures, bridging water molecules, and, on average, smaller size. Interestingly, analysis of the connectivity of these proteins illustrates that they have more interactions with other proteins. These findings are important in predicting "date hubs," if we assume that "date hubs" are shared proteins with binding sites capable of transient binding to multipartners, linking higher-order networks.     

Computational identification of proteins for selectivity assays

At the stage of optimization of a chemical series the compounds are normally assayed for binding or inhibition on the target protein as well as on several proteins from a selectivity panel. These proteins are normally identified on the basis of sequence homology to the target protein. Experimental selectivity data are also taken into account if available. Cases when a nonhomologous protein has a significant affinity to the compound series are going to be missed if the selectivity panel is identified by homology. Experimental data is usually either unavailable or limited to a small fraction of proteins that should be considered. We have developed a computational method of identification of selectivity panel proteins. It is based on the evaluation of binding site similarity to the target protein using docking scores of target-selected molecular probes. These probes are obtained by docking a large library of drug-like compounds to the target protein followed by selecting a diverse subset from the best virtual binders. Docking scores of these probes to other proteins measure binding site similarity to the target. Because the method does not require prior knowledge of either affinities or structures of inhibitors for the target, it can be applied to any protein with known 3D structure. Validation of the method includes rediscovery of nonhomologous proteins that bind common ligands: estradiol, tamoxifen, and riboflavin. Given 3D structures, the method can effectively discriminate proteins with similar binding sites from random proteins independent of sequence homology.     

Fine-tuning spermidine binding modes in the putrescine binding protein PotF

A profound understanding of the molecular interactions between receptors and ligands is important throughout diverse research, such as protein design, drug discovery, or neuroscience. What determines specificity and how do proteins discriminate against similar ligands? In this study, we analyzed factors that determine binding in two homologs belonging to the well-known superfamily of periplasmic binding proteins, PotF and PotD. Building on a previously designed construct, modes of polyamine binding were swapped. This change of specificity was approached by analyzing local differences in the binding pocket as well as overall conformational changes in the protein. Throughout the study, protein variants were generated and characterized structurally and thermodynamically, leading to a specificity swap and improvement in affinity. This dataset not only enriches our knowledge applicable to rational protein design but also our results can further lay groundwork for engineering of specific biosensors as well as help to explain the adaptability of pathogenic bacteria.     

Localization of protein-binding sites within families of proteins

We address the question of whether or not the positions of protein-binding sites on homologous protein structures are conserved irrespective of the identities of their binding partners. First, for each domain family in the Structural Classification of Proteins (SCOP), protein-binding sites are extracted from our comprehensive database of structurally defined binary domain interactions (PIBASE). Second, the binding sites within each family are superposed using a structural alignment of its members. Finally, the degree of localization of binding sites within each family is quantified by comparing it with localization expected by chance. We found that 72% of the 1847 SCOP domain families in PIBASE have binding sites with localization values greater than expected by chance. Moreover, 554 (30%) of these families have localizations that are statistically significant (i.e., more than four standard deviations away from the mean expected by chance). In contrast, only 144 (8%) families have significantly low localization. The absence of a significant correlation of the binding site localization with the average sequence and structural conservations in a family suggests that localization can be helpful for describing the functional diversity of protein-protein interactions, complementing measures of sequence and structural conservation. Consideration of the binding site localization may also result in spatial restraints for the modeling of protein assembly structures.     

Atomic structures of periplasmic binding proteins and the high-affinity active transport systems in bacteria

We have determined and refined the X-ray crystal structures of six periplasmic binding proteins that serve as initial receptors for the osmotic-shock sensitive, active transport of L-arabinose, D-galactose/D-glucose, maltose, sulphate, leucine/isoleucine/valine and leucine. The tertiary structures and atomic interactions between proteins and ligands show common features that are important for understanding the function of the binding proteins. All six structures are ellipsoidal, consisting of two similar, globular domains. The ligand-binding site is located deep in the cleft between the two domains. Irrespective of the nature of the ligand (e.g. saccharide, sulphate dianion or leucine zwitterion), the specificities and affinities of the binding sites are achieved mainly through hydrogen-bonding interactions. Binding of ligands induces a large protein conformational change. Three different structures have been observed among the binding proteins: unliganded 'open cleft', liganded 'open cleft', and liganded 'closed cleft'. Here we discuss the functions of binding proteins in the light of numerous crystallographic and ligand-binding studies and propose a mechanism for the binding protein-dependent, high-affinity active transport.     

Recognition of functional sites in protein structures

Recognition of regions on the surface of one protein, that are similar to a binding site of another is crucial for the prediction of molecular interactions and for functional classifications. We first describe a novel method, SiteEngine, that assumes no sequence or fold similarities and is able to recognize proteins that have similar binding sites and may perform similar functions. We achieve high efficiency and speed by introducing a low-resolution surface representation via chemically important surface points, by hashing triangles of physico-chemical properties and by application of hierarchical scoring schemes for a thorough exploration of global and local similarities. We proceed to rigorously apply this method to functional site recognition in three possible ways: first, we search a given functional site on a large set of complete protein structures. Second, a potential functional site on a protein of interest is compared with known binding sites, to recognize similar features. Third, a complete protein structure is searched for the presence of an a priori unknown functional site, similar to known sites. Our method is robust and efficient enough to allow computationally demanding applications such as the first and the third. From the biological standpoint, the first application may identify secondary binding sites of drugs that may lead to side-effects. The third application finds new potential sites on the protein that may provide targets for drug design. Each of the three applications may aid in assigning a function and in classification of binding patterns. We highlight the advantages and disadvantages of each type of search, provide examples of large-scale searches of the entire Protein Data Base and make functional predictions.     

Lipid-binding surfaces of membrane proteins: evidence from evolutionary and structural analysis

Membrane proteins function in the diverse environment of the lipid bilayer. Experimental evidence suggests that some lipid molecules bind tightly to specific sites on the membrane protein surface. These lipid molecules often act as co-factors and play important functional roles. In this study, we have assessed the evolutionary selection pressure experienced at lipid-binding sites in a set of α-helical and β-barrel membrane proteins using posterior probability analysis of the ratio of synonymous vs. nonsynonymous substitutions (ω-ratio). We have also carried out a geometric analysis of the membrane protein structures to identify residues in close contact with co-crystallized lipids. We found that residues forming cholesterol-binding sites in both β(2)-adrenergic receptor and Na(+)-K(+)-ATPase exhibit strong conservation, which can be characterized by an expanded cholesterol consensus motif for GPCRs. Our results suggest the functional importance of aromatic stacking interactions and interhelical hydrogen bonds in facilitating protein-cholesterol interactions, which is now reflected in the expanded motif. We also find that residues forming the cardiolipin-binding site in formate dehydrogenase-N γ-subunit and the phosphatidylglycerol binding site in KcsA are under strong purifying selection pressure. Although the lipopolysaccharide (LPS)-binding site in ferric hydroxamate uptake receptor (FhuA) is only weakly conserved, we show using a statistical mechanical model that LPS binds to the least stable FhuA β-strand and protects it from the bulk lipid. Our results suggest that specific lipid binding may be a general mechanism employed by β-barrel membrane proteins to stabilize weakly stable regions. Overall, we find that the residues forming specific lipid binding sites on the surfaces of membrane proteins often experience strong purifying selection pressure.