Ligand-supported homology modeling of g-protein-coupled receptor sites: models sufficient for successful virtual screening.
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Amino Acid Sequence↗
Biomedical subjects
Gerhard Klebe
Publications and source records attributed to Gerhard Klebe.
Non-thiol farnesyltransferase inhibitors: utilization of the far aryl binding site by 5-cinnamoylaminobenzophenones.
We recently described two novel aryl binding sites of farnesyltransferase. In this study, the cinnamoyl residue was designed as an appropriate substituent for our benzophenone-based AAX-peptidomimetic compound capable of occupying the far aryl binding site.
Alkyl and Aryl Transferases↗
Comparison of substructural epitopes in enzyme active sites using self-organizing maps.
This paper presents a new algorithm to compare substructural epitopes in protein binding cavities. Through the comparison of binding cavities accommodating well characterized ligands with cavities whose actual guests are yet unknown, it is possible to draw some conclusions on the required shape of a putative ligand likely to bind to the latter cavities. To detect functional relationships among proteins, their binding-site exposed physicochemical characteristics are described by assigning generic pseudocenters to the functional groups of the amino acids flanking the particular active site. The cavities are divided into small local regions of four pseudocenters having the shape of a pyramid with triangular basis. To find similar local regions, an emergent self-organizing map is used for clustering. Two local regions within the same cluster are similar and form the basis for the superpositioning of the corresponding cavities to score this match. First results show that the similarities between enzymes with the same EC number can be found correctly. Enzymes with different EC numbers are detected to have no common substructures. These results indicate the benefit of this method and motivate further studies.
Algorithms↗
Ligand-supported homology modelling of protein binding-sites using knowledge-based potentials.
A new approach, MOBILE, is presented that models protein binding-sites including bound ligand molecules as restraints. Initially generated, homology models of the target protein are refined iteratively by including information about bioactive ligands as spatial restraints and optimising the mutual interactions between the ligands and the binding-sites. Thus optimised models can be used for structure-based drug design and virtual screening. In a first step, ligands are docked into an averaged ensemble of crude homology models of the target protein. In the next step, improved homology models are generated, considering explicitly the previously placed ligands by defining restraints between protein and ligand atoms. These restraints are expressed in terms of knowledge-based distance-dependent pair potentials, which were compiled from crystallographically determined protein-ligand complexes. Subsequently, the most favourable models are selected by ranking the interactions between the ligands and the generated pockets using these potentials. Final models are obtained by selecting the best-ranked side-chain conformers from various models, followed by an energy optimisation of the entire complex using a common force-field. Application of the knowledge-based pair potentials proved efficient to restrain the homology modelling process and to score and optimise the modelled protein-ligand complexes. For a test set of 46 protein-ligand complexes, taken from the Protein Data Bank (PDB), the success rate of producing near-native binding-site geometries (rmsd<2.0A) with MODELLER is 70% when the ligand restrains the homology modelling process in its native orientation. Scoring these complexes with the knowledge-based potentials, in 66% of the cases a pose with rmsd <2.0A is found on rank 1. Finally, MOBILE has been applied to two case studies modelling factor Xa based on trypsin and aldose reductase based on aldehyde reductase.
Binding Sites↗
Flexible adaptations in the structure of the tRNA-modifying enzyme tRNA-guanine transglycosylase and their implications for substrate selectivity, reaction mechanism and structure-based drug design.
The enzyme tRNA-guanine transglycosylase (TGT, EC 2.4.2.29) catalyses a base-exchange reaction that leads to anticodon modifications of certain tRNAs. The TGT enzymes of the eubacteria Zymomonas mobilis (Z. mobilis TGT) and Escherichia coli (E. coli TGT) show a different behaviour in the presence of competitive inhibitors. The active sites of both enzymes are identical apart from a single conservative amino acid exchange, namely Tyr106 of Z. mobilis TGT is replaced by a Phe in E. coli TGT. Although Tyr106 is, in contrast to Phe106, hydrogen bonded in the ligand-free structure, we can show by a mutational study of TGT(Y106F) that this is not the reason for the different responses upon competition. The TGT enzymes of various species differ in their substrate selectivity. Depending on the applied pH conditions and/or induced by ligand binding, a peptide-bond flip modulates the recognition properties of the substrate binding site, which changes between donor and acceptor functionality. Furthermore interstitial water molecules play an important role in these adaptations of the pocket. The flip of the peptide bond is further stabilised by a glutamate residue that operates as general acid/base. An active-site aspartate residue, presumed to operate as a nucleophile through covalent bonding during the base-exchange reaction, shows different conformations depending on the nature of the bound ligand. The induced-fit adaptations observed in the various TGT complex structures by multiple crystal-structure analyses are in agreement with the functional properties of the enzyme. In consequence, full understanding of this plasticity can be exploited for drug design.
Aspartic Acid↗
An essential role for aspartate 264 in catalysis by tRNA-guanine transglycosylase from Escherichia coli.
tRNA-guanine transglycosylase (TGT) catalyzes a post-transcriptional base-exchange reaction involved in the incorporation of the modified base queuine (Q) into the wobble position of certain tRNAs. Catalysis by TGT occurs through a double-displacement mechanism that involves the formation of a covalent enzyme-RNA intermediate (Kittendorf, J. D., Barcomb, L. M., Nonekowski, S. T., and Garcia, G. A. (2001) Biochemistry 40, 14123-14133). The TGT chemical mechanism requires the protonation of the displaced guanine and the deprotonation of the incoming heterocyclic base. Based on its position in the active site, it is likely that aspartate 264 is involved in these proton transfer events. To investigate this possibility, site-directed mutagenesis was employed to convert aspartate 264 to alanine, asparagine, glutamate, glutamine, lysine, and histidine. Biochemical characterization of these TGT mutants revealed that only the conservative glutamate mutant retained catalytic activity, with Km values for both tRNA and guanine 3-fold greater than those for wild-type, whereas the kcat was depressed by an order of magnitude. Furthermore, of these six TGT mutants, only the TGT(D264E) was capable of forming a TGT.RNA covalent intermediate; however, unlike wild-type TGT, only hydroxylamine is capable of cleaving the TGT(D264E).RNA covalent complex. In an effort to better understand the unique biochemical properties of the D264E TGT mutant, we solved the crystal structure of the Zymomonas mobilis TGT with the analogous mutation (D280E). The results of these studies support two roles for aspartate 264 in catalysis by TGT, protonation of the leaving guanine and deprotonation of the incoming preQ1.
Amino Acid Substitution↗
ZZ made EZ: influence of inhibitor configuration on enzyme selectivity.
Selectivity of drug targeting is necessary in order to forestall undesired side-effects. Here, we examine the structural grounds for the configuration-dependent selectivity of 2,7-bis(4-amidinobenzylidene)-cycloheptan-1-one (1) for factor Xa and trypsin: Previous studies showed that factor Xa is preferentially inhibited by the (Z,Z) configuration isomer of (1), whilst trypsin binds equally well to both (E,Z) and (Z,Z) forms. Using engineered trypsin variants, we find similar overall binding modes for the (E,Z) and (Z,Z) isomers. Minor changes in van der Waals' contacts to Tyr99 (Leu in trypsin) explain the differential inhibition of factor Xa. We note differences in the experimental electron densities observed from co-crystallisation and soaking experiments: while the co-crystallisation of (1) with variants containing Tyr99 (Leu99) reveal the exclusive presence of the (Z,Z) ((E,Z)) configurations respectively, soaking experiments with either variant result in mixtures of (E,Z), (Z,Z) and (E,E). This discrepancy arises presumably from differences in the spatial (packing considerations) or chemical (crystallisation conditions) microenvironments. The results presented here represent an extreme example of the problems that face structure-based drug design, in particular the dangers inherent in relying on a single crystal structure for interpreting protein-ligand interactions.
Animals↗
Crystal structure of 2-methylisocitrate lyase (PrpB) from Escherichia coli and modelling of its ligand bound active centre.
Following acetate, propionate is the second most abundant low molecular mass carbon compound found in soil. Many microorganisms, including most, if not all fungi, as well as several aerobic bacteria, such as Escherichia coli and Salmonella enterica oxidize propionate via the methylcitrate cycle. The enzyme 2-methylisocitrate lyase (PrpB) from Escherichia coli catalysing the last step of this cycle, the cleavage of 2-methylisocitrate to pyruvate and succinate, was crystallised and its structure determined to a resolution of 1.9A. The enzyme, which strictly depends on Mg(2+) for catalysis, belongs to the isocitrate lyase protein family. A common feature of members of this enzyme family is the movement of a so-called "active site loop" from an open into a closed conformation upon substrate binding thus shielding the reactants from the surrounding solvent. Since in the presented structure, PrpB contains, apart from a Mg(2+), no ligand, the active site loop is found in an open conformation. This conformation, however, differs significantly from the open conformation present in the so far known structures of ligand-free isocitrate lyases. A possible impact of this observation with respect to the different responses of isocitrate lyases and PrpB upon treatment with the common inhibitor 3-bromopyruvate is discussed. Based on the structure of ligand-bound isocitrate lyase from Mycobacterium tuberculosis a model of the substrate-bound PrpB enzyme in its closed conformation was created which provides hints towards the substrate specificity of this enzyme.
Amino Acid Sequence↗
Non-thiol farnesyltransferase inhibitors: N-(4-acylamino-3-benzoylphenyl)-3-[5-(4-nitrophenyl)-2-furyl]acrylic acid amides.
We have designed the nitrophenylfurylacryl-substituted benzophenone 4f as a non-thiol farnesyltransferase inhibitor utilizing a novel aryl binding site of farnesyltransferase. Variation of the 2-acylamino substituent at the benzophenone core structure of our initial lead 4f yielded several non-thiol farnesyltransferase inhibitors with improved activity. These compounds display activity in the low nanomolar range.
Alkyl and Aryl Transferases↗
Virtual screening for submicromolar leads of tRNA-guanine transglycosylase based on a new unexpected binding mode detected by crystal structure analysis.
Eubacterial tRNA-guanine transglycosylase (TGT) is involved in the hypermodification of cognate tRNAs, leading to the exchange of G34 by preQ1 at the wobble position in the anticodon loop. Mutation of the tgt gene in Shigella flexneri results in a significant loss of pathogenicity of the bacterium due to inefficient translation of a virulence protein mRNA. Herein, we describe the discovery of a ligand with an unexpected binding mode. On the basis of this binding mode, three slightly deviating pharmacophore hypotheses have been derived. Virtual screening based on this composite pharmacophore model retrieved a set of potential TGT inhibitors belonging to several compound classes. All nine tested inhibitors being representatives of these classes showed activity in the micromolar range, two of them even in the submicromolar range.
Binding Sites↗
Relibase: design and development of a database for comprehensive analysis of protein-ligand interactions.
Knowledge discovery from the exponentially growing body of structurally characterised protein-ligand complexes as a source of information in structure-based drug design is a major challenge in contemporary drug research. Given the need for powerful data retrieval, integration and analysis tools, Relibase was developed as a database system particularly designed to handle protein-ligand related problems and tasks. Here, we describe the design and functionality of the Relibase core database system. Features of Relibase include, e.g. the detailed analysis of superimposed ligand binding sites, ligand similarity and substructure searches, and 3D searches for protein-ligand and protein-protein interaction patterns. The broad range of functions provided in Relibase and its high level of data integration, along with its flexible and intuitive interface, makes Relibase an invaluable data mining tool which can significantly enhance the drug development process. An example, illustrating a 3D query for quarternary ligand nitrogen atoms interacting with aromatic ring systems in proteins, a pattern found in pharmaceutically relevant target proteins such as, e.g. acetylcholine-esterase, is discussed.
Animals↗
Utilising structural knowledge in drug design strategies: applications using Relibase.
The concept of structure-based drug design is based upon an in-depth understanding of the principles of molecular recognition. Despite our lack of a thorough comprehension of these principles, the wealth of protein structures available opens up unprecedented possibilities for new insights from the analysis of these data. Unravelling universal rules of molecular recognition is certainly one of the most appealing goals. But our knowledge is enhanced also when studying the specific determinants that characterise single targets or target families only, and the factors governing and discriminating their recognition properties.Here, we illustrate how the structure-based design process can benefit from the consequent incorporation of database query tools. We discuss representative examples to address issues such as protein flexibility, water molecules in binding pockets, and ligand specificity as some of the most critical aspects of drug design. All studies are carried out using our database system Relibase. We also show the application of Relibase in searching for preferred geometrical patterns between interacting molecular fragments.
Animals↗
Reconstructing the binding site of factor Xa in trypsin reveals ligand-induced structural plasticity.
In order to investigate issues of selectivity and specificity in protein-ligand interactions, we have undertaken the reconstruction of the binding pocket of human factor Xa in the structurally related rat trypsin by site-directed mutagenesis. Three sequential regions (the "99"-, the "175"- and the "190"- loops) were selected as representing the major structural differences between the ligand binding sites of the two enzymes. Wild-type rat trypsin and variants X99rT and X(99/175/190)rT were expressed in yeast, and analysed for their interaction with factor Xa and trypsin inhibitors. For most of the inhibitors studied, progressive loop replacement at the trypsin surface resulted in inhibitory profiles akin to factor Xa. Crystals of the variants were obtained in the presence of benzamidine (3), and could be soaked with the highly specific factor Xa inhibitor (1). Binding of the latter to X99rT results in a series of structural adaptations to the ligand, including the establishment of an "aromatic box" characteristic of factor Xa. In X(99/175/190)rT, introduction of the 175-loop results in a surprising re-orientation of the "intermediate helix", otherwise common to trypsin and factor Xa. The re-orientation is accompanied by an isomerisation of the Cys168-Cys182 disulphide bond, and burial of the critical Phe174 side-chain. In the presence of (1), a major re-organisation of the binding site takes place to yield a geometry identical to that of factor Xa. In all, binding of (1) to trypsin and its variants results in significant structural rearrangements, inducing a binding surface strongly reminiscent of factor Xa, against which the inhibitor was optimised. The structural data reveal a plasticity of the intermediate helix, which has been implicated in the functional cofactor dependency of many trypsin-like serine proteinases. This approach of grafting loops onto scaffolds of known related structures may serve to bridge the gap between structural genomics and drug design.
Animals↗
A new method to detect related function among proteins independent of sequence and fold homology.
A new method has been developed to detect functional relationships among proteins independent of a given sequence or fold homology. It is based on the idea that protein function is intimately related to the recognition and subsequent response to the binding of a substrate or an endogenous ligand in a well-characterized binding pocket. Thus, recognition of similar ligands, supposedly linked to similar function, requires conserved recognition features exposed in terms of common physicochemical interaction properties via the functional groups of the residues flanking a particular binding cavity. Following a technique commonly used in the comparison of small molecule ligands, generic pseudocenters coding for possible interaction properties were assigned for a large sample set of cavities extracted from the entire PDB and stored in the database Cavbase. Using a particular query cavity a series of related cavities of decreasing similarity is detected based on a clique detection algorithm. The detected similarity is ranked according to property-based surface patches shared in common by the different clique solutions. The approach either retrieves protein cavities accommodating the same (e.g. co-factors) or closely related ligands or it extracts proteins exhibiting similar function in terms of a related catalytic mechanism. Finally the new method has strong potential to suggest alternative molecular skeletons in de novo design. The retrieval of molecular building blocks accommodated in a particular sub-pocket that shares similarity with the pocket in a protein studied by drug design can inspire the discovery of novel ligands.
Algorithms↗
DrugScore meets CoMFA: adaptation of fields for molecular comparison (AFMoC) or how to tailor knowledge-based pair-potentials to a particular protein.
The development of a new tailor-made scoring function to predict binding affinities of protein-ligand complexes is described. Knowledge-based pair-potentials are specifically adapted to a particular protein by considering additional ligand-based information. The formalism applied to derive the new function is similar to the well-known CoMFA approach, however, the fields used in the approach originate from the protein environment (and not from the aligned ligands as in CoMFA, thus, a "reverse" CoMFA (= AFMoC) named Adaptation of Fields for Molecular Comparison is performed). A regular-spaced grid is placed into the binding site and knowledge-based pair-potentials between protein atoms and ligand atom probes are mapped onto the grid intersections resulting in "potential fields". By multiplying distance-dependent atom-type properties of actual ligands docked into the binding site with the neighboring grid values, "interaction fields" are produced from the original "potential fields". In a PLS analysis, these atom-type specific interaction fields are correlated to the actual binding affinities of the embedded ligands, resulting in individual weighting factors for each field value. As in CoMFA, the results of the analysis can be interpreted in graphical terms by contribution maps, and binding affinities of novel ligands are predicted by applying the derived 3D QSAR equation. The scope of the new method is demonstrated using thermolysin and glycogen phosphorylase b as test examples. Impressive improvements of the predictive power for affinity prediction can be achieved compared to the application of the original knowledge-based potentials by considering a sample set of only 15 known training ligands. Thus, with growing information about the drug target studied, the new method allows one to move gradually from generally valid to protein-specifically adapted pair-potentials, depending on the amount of training information available and its degree of structural diversity. In addition, convincing predictive power is also achieved for ligand poses generated by automatic docking tools.
Databases, Factual↗
Successful virtual screening for novel inhibitors of human carbonic anhydrase: strategy and experimental confirmation.
Virtual screening of compound libraries is an alternative and complementary approach to high-throughput screening in the lead discovery process. A new strategy is described to search for possible leads of human carbonic anhydrase II, applying a protocol of several consecutive hierarchical filters involving a preselection based on functional group requirements and fast pharmacophore matching. A suitable pharmacophore is derived by a sophisticated "hot spot" analysis of the binding site to detect regions favorable for protein-ligand interactions. In subsequent steps, molecular similarity with known reference ligands is used to rerank the hits from the pharmacophore matching. Finally the best scored candidates are docked flexibly into the protein binding pocket. After examination of the affinity predictions, 13 compounds were selected for experimental testing. Of these 13, three could be shown to be subnanomolar, one is nanomolar, while a further seven are micromolar inhibitors. The binding mode of two hits could be confirmed by crystal structure analysis. The novelty of the discovered leads is best supported by the fact that a search in the patent literature showed the newly discovered subnanomolar compounds to comprise scaffolds not yet covered by existing patents.
Carbonic Anhydrase II↗
Nonaromatic sulfonamide group as an ideal anchor for potent human carbonic anhydrase inhibitors: role of hydrogen-bonding networks in ligand binding and drug design.
X-ray crystal structures of the adducts of human carbonic anhydrase (hCA) isozyme II with derivatives incorporating a sulfamide or sulfamic acid moiety are reported. The absence of a C-SO(2)NH(2) bond in the first type of compound can be exploited for the design of more potent and selective CA inhibitors. This study also explains why sulfate is a several-orders-of-magnitude weaker CA inhibitor compared to derivatives incorporating sulfonamide/sulfamide moieties.
Carbonic Anhydrase II↗
Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors.
The influence of a xenobiotic compound on an organism is usually summarized by the expression biological activity. If a controlled, therapeutically relevant, and regulatory action is observed the compound has potential as a drug, otherwise its toxicity on the biological system is of interest. However, what do we understand by the biological activity? In principle, the overall effect on an organism has to be considered. However, because of the complexity of the interrelated processes involved, as a simplification primarily the "main action" on the organism is taken into consideration. On the molecular level, biological activity corresponds to the binding of a (low-molecular weight) compound to a macromolecular receptor, usually a protein. Enzymatic reactions or signal-transduction cascades are thereby influenced with respect to their function for the organism. We regard this binding as a process under equilibrium conditions; thus, binding can be described as an association or dissociation process. Accordingly, biological activity is expressed as the affinity of both partners for each other, as a thermodynamic equilibrium quantity. How well do we understand these terms and how well are they theoretically predictable today? The holy grail of rational drug design is the prediction of the biological activity of a compound. The processes involving ligand binding are extremely complicated, both ligand and protein are flexible molecules, and the energy inventory between the bound and unbound states must be considered in aqueous solution. How sophisticated and reliable are our experimental approaches to obtaining the necessary insight? The present review summarizes our current understanding of the binding affinity of a small-molecule ligand to a protein. Both theoretical and empirical approaches for predicting binding affinity, starting from the three-dimensional structure of a protein-ligand complex, will be described and compared. Experimental methods, primarily microcalorimetry, will be discussed. As a perspective, our own knowledge-based approach towards affinity prediction and experimental data on factorizing binding contributions to protein-ligand binding will be presented.
Animals↗