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G Klebe

Publications and source records attributed to G Klebe.

At least 19 recordsLinked to original sources
PubMed2005

Cooperative effects in hydrogen-bonding of protein secondary structure elements: a systematic analysis of crystal data using Secbase.

A systematic analysis of the hydrogen-bonding geometry in helices and beta sheets has been performed. The distances and angles between the backbone carbonyl O and amide N atoms were correlated considering more than 1500 protein chains in crystal structures determined to a resolution better than 1.5 A. They reveal statistically significant trends in the H-bond geometry across the different secondary structural elements. The analysis has been performed using Secbase, a modular extension of Relibase (Receptor Ligand Database) which integrates information about secondary structural elements assigned to individual protein structures with the various search facilities implemented into Relibase. A comparison of the mean hydrogen-bond distances in alpha helices and 3(10) helices of increasing length shows opposing trends. Whereas in alpha helices the mean H-bond distance shrinks with increasing helix length and turn number, the corresponding mean dimension in 3(10) helices expands in a comparable series. Comparing similarly the hydrogen-bond lengths in beta sheets there is no difference to be found between the mean H-bond length in antiparallel and parallel beta sheets along the strand direction. In contrast, an interesting systematic trend appears to be given for the hydrogen bonds perpendicular to the strands bridging across an extended sheet. With increasing number of accumulated strands, which results in a growing number of back-to-back piling hydrogen bonds across the strands, a slight decrease of the mean H-bond distance is apparent in parallel beta sheets whereas such trends are obviously not given in antiparallel beta sheets. This observation suggests that cooperative effects mutually polarizing spatially well-aligned hydrogen bonds are present either in alpha helices and parallel beta sheets whereas such influences seem to be lacking in 3(10) helices and antiparallel beta sheets.

Crystallography, X-Ray↗
PubMed2004

Strategies for the design of inhibitors of aldose reductase, an enzyme showing pronounced induced-fit adaptations.

Aldose reductase is involved in the polyol pathway, catalyzing the reduction of glucose to sorbitol. However, due to pronounced binding site adaptations, the enzyme can operate on a broad palette of structurally diverse substrates ranging from small aliphatic and aromatic aldehydes up to steroid-type ligands. A comparative analysis of the presently accessible crystal structures of aldose reductase complexes reveals four binding-competent protein conformations. Additional relevant conformers are detected through molecular dynamics simulations. They indicate an equilibrium of several conformers which is shifted towards the binding-competent geometries upon ligand binding. Such a manifold system with several alternative binding site conformers requires some tailored concepts in virtual screening. We followed two strategies, both successfully suggesting new micromolar inhibitors. In a first attempt, we concentrated on one preferred conformer and performed a virtual screening, assuming that the binding pocket of aldose reductase adopts only this conformation. In a second approach, we followed a ligand superpositioning method. Ligands were extracted in their bound conformations from three different crystal structures, all accommodating the ligands with different active site conformations. After merging these ligands into one supermolecule, mutual alignments were computed, taking candidate ligands from a screening database. The latter strategy also retrieved several structurally new inhibitors of micromolar potency.

Aldehyde Reductase↗
PubMed2001

Factorising ligand affinity: a combined thermodynamic and crystallographic study of trypsin and thrombin inhibition.

The binding of a series of low molecular weight ligands towards trypsin and thrombin has been studied by isothermal titration calorimetry and protein crystallography. In a series of congeneric ligands, surprising changes of protonation states occur and are overlaid on the binding process. They result from induced pK(a) shifts depending on the local environment experienced by the ligand and protein functional groups in the complex (induced dielectric fit). They involve additional heat effects that must be corrected before any conclusion on the binding enthalpy (DeltaH) and entropy (DeltaS) can be drawn. After correction, trends in both contributions can be interpreted in structural terms with respect to the hydrogen bond inventory or residual ligand motions. For all inhibitors studied, a strong negative heat capacity change (DeltaC(p)) is detected, thus binding becomes more exothermic and entropically less favourable with increasing temperature. Due to a mutual compensation, Gibbs free energy remains virtually unchanged. The strong negative DeltaC(p) value cannot solely be explained by the removal of hydrophobic surface portions of the protein or ligand from water exposure. Additional contributions must be considered, presumably arising from modulations of the local water structure, changes in vibrational modes or other ordering parameters. For thrombin, smaller negative DeltaC(p) values are observed for ligand binding in the presence of sodium ions compared to the other alkali ions, probably due to stabilising effects on the protein or changes in the bound water structure.

Animals↗
PubMed2001

Docking ligands onto binding site representations derived from proteins built by homology modelling.

Due to the abundant sequence information available from genome projects, an increasing number of structurally unknown proteins, homologous to examples of known 3D structure, will be discovered as new targets for drug design. Since homology models do not provide sufficient accuracy to apply common drug design tools, a new approach, DragHome, has been developed to dock ligands into such approximate protein models. DragHome combines information from homology modelling with ligand data, used by and derived from 3D quantitative structure-activity relationships (QSAR). The binding-site of a model-built protein is analysed in terms of putative ligand interaction sites and translated via Gaussian functions into a functional binding-site description represented by physico-chemical properties. Ligands to be docked onto these binding-site representations are similarly translated into a description based on Gaussian functions. The docking is computed by optimising the overlap between the functional description of the binding site and the ligand, generating multiple solutions. For a set of different ligands, these solutions are ranked according to the internal similarity consistance among the various ligands in the binding modes obtained from docking. DragHome has been validated at examples for which crystal structures are available: structurally distinct thrombin inhibitors were docked onto models of thrombin generated from serine proteases of 28 to 40 % sequence identity, yielding ligand binding modes with an average RMS deviation of 1.4 A. Mostly the near-native solutions are ranked best. Molecular flexibility of ligands can be considered in terms of pre-calculated multiple conformers. DragHome has been used to automatically generate an alignment of 88 thrombin inhibitors, for which a significant 3D QSAR model could be derived. The contribution maps resulting from this analysis can be interpreted with respect to the surrounding protein model. They highlight inconsistencies and deficiencies present in the model. In future developments, this information could be fed back into a subsequent modelling step to improve the protein model.

Algorithms↗
PubMed2001

A new target for shigellosis: rational design and crystallographic studies of inhibitors of tRNA-guanine transglycosylase.

Eubacterial tRNA-guanine transglycosylase (TGT) is involved in the hyper-modification of cognate tRNAs leading to the exchange of G34 at the wobble position in the anticodon loop by preQ1 (2-amino-5-(aminomethyl)pyrrolo[2,3-d]pyrimidin-4(3H)-one) as part of the biosynthesis of queuine (Q). Mutation of the tgt gene in Shigella flexneri results in a significant loss of pathogenicity of the bacterium, revealing TGT as a new target for the design of potent drugs against Shigellosis. The X-ray structure of Zymomonas mobilis TGT in complex with preQ1 was used to search for new putative inhibitors with the computer program LUDI. An initial screen of the Available Chemical Directory, a database compiled from commercially available compounds, suggested several hits. Of these, 4-aminophthalhydrazide (APH) showed an inhibition constant in the low micromolar range. The 1.95 A crystal structure of APH in complex with Z. mobilis TGT served as a starting point for further modification of this initial lead.

Binding Sites↗
PubMed2001

Statistical potentials and scoring functions applied to protein-ligand binding.

In virtual screening, small-molecule ligands are docked into protein binding sites and their binding affinity is predicted. Knowledge-based, regression-based and first-principle-based methods have been developed to rank computer-generated binding modes. As a result of still existing deficiencies, a best compromise might be the combination of several scoring schemes into a consensus scoring approach.

Drug Evaluation, Preclinical↗
PubMed2001

Transport of peptidomimetic thrombin inhibitors with a 3-amidino-phenylalanine structure: permeability and efflux mechanism in monolayers of a human intestinal cell line (Caco-2).

PURPOSE: Peptidomimetic thrombin inhibitors derived from Nalpha-(2-naphthylsulfonyl)-3-amidino-phenylalanine with different basic and acidic substituents were investigated with respect to their intestinal transport behavior. METHODS: Intestinal permeability coefficients were studied using Caco-2 monolayers and a reversed-phase HPLC method for quantitation. RESULTS: Apparent permeability coefficients Papp of compounds with a free amidino group were in general low (<10 x 10(-8) cm/s) and independent of the structure of the amide part (C-terminus). Polarized efflux, however, was strongly affected by substituents in the amide moiety yielding the following efflux ratios (ER): methylpiperidide (1) (ER 45) > piperidine carboxylic acid methylester (ER 6-11) > piperidine carboxylic acids (ER 1.9-2.9) > piperazide (ER -0.17). Efflux of (1) was temperature-dependent, but independent of the enantiomeric configuration, accompanied by an increase in transepithelial electrical resistance (TEER), and could be reduced by P-gp inhibitors (PSC 833, Cremophor EL) but not by indomethacin. Replacement of the amidine group of (1) by aminomethyl-, amino-, and oxamidine- moieties drastically increased absorptive permeability (46-68 fold) with ER < 3.4. In contrast, the oxamidine with a C-terminal nipecotic acid residue (8) displayed also a temperature dependent efflux- without altering TEER (ER 22). This efflux was sensitive to PSC833/Cremophor EL and indomethacin. CONCLUSIONS: Basic and acidic residues of amidino-phenylalanine-derived thrombin inhibitors mediate affinity to intestinal efflux pumps. presumably P-gp and MRP. P-gp mediated efflux was related to a net positive charge and accompanied by an increased TEER. Among the methylpiperide (1) promoieties studied the oxamidino group seems to be very promising in overcoming both transport and efflux problems frequently encountered with peptidomimetics containing amidines.

Amidines↗
PubMed2000

The crystal structure of 3alpha -hydroxysteroid dehydrogenase/carbonyl reductase from Comamonas testosteroni shows a novel oligomerization pattern within the short chain dehydrogenase/reductase family.

The crystal structure of 3alpha-hydroxysteroid dehydrogenase/carbonyl reductase from Comamonas testosteroni (3alpha-HSDH) as well as the structure of its binary complex with NAD(+) have been solved at 1.68-A and 1.95-A resolution, respectively. The enzyme is a member of the short chain dehydrogenase/reductase (SDR) family. Accordingly, the active center and the conformation of the bound nucleotide cofactor closely resemble those of other SDRs. The crystal structure reveals one homodimer per asymmetric unit representing the physiologically active unity. Dimerization takes place via an interface essentially built-up by helix alphaG and strand betaG of each subunit. So far this type of intermolecular contact has exclusively been observed in homotetrameric SDRs but never in the structure of a homodimeric SDR. The formation of a tetramer is blocked in 3alpha-HSDH by the presence of a predominantly alpha-helical subdomain which is missing in all other SDRs of known structure.

3-Hydroxysteroid Dehydrogenases↗
PubMed2000

Knowledge-based scoring function to predict protein-ligand interactions.

The development and validation of a new knowledge-based scoring function (DrugScore) to describe the binding geometry of ligands in proteins is presented. It discriminates efficiently between well-docked ligand binding modes (root-mean-square deviation <2.0 A with respect to a crystallographically determined reference complex) and those largely deviating from the native structure, e.g. generated by computer docking programs. Structural information is extracted from crystallographically determined protein-ligand complexes using ReLiBase and converted into distance-dependent pair-preferences and solvent-accessible surface (SAS) dependent singlet preferences for protein and ligand atoms. Definition of an appropriate reference state and accounting for inaccuracies inherently present in experimental data is required to achieve good predictive power. The sum of the pair preferences and the singlet preferences is calculated based on the 3D structure of protein-ligand binding modes generated by docking tools. For two test sets of 91 and 68 protein-ligand complexes, taken from the Protein Data Bank (PDB), the calculated score recognizes poses generated by FlexX deviating <2 A from the crystal structure on rank 1 in three quarters of all possible cases. Compared to FlexX, this is a substantial improvement. For ligand geometries generated by DOCK, DrugScore is superior to the "chemical scoring" implemented into this tool, while comparable results are obtained using the "energy scoring" in DOCK. None of the presently known scoring functions achieves comparable power to extract binding modes in agreement with experiment. It is fast to compute, regards implicitly solvation and entropy contributions and produces correctly the geometry of directional interactions. Small deviations in the 3D structure are tolerated and, since only contacts to non-hydrogen atoms are regarded, it is independent from assumptions of protonation states.

Artificial Intelligence↗
PubMed2000

Recent developments in structure-based drug design.

Structure-based design has emerged as a new tool in medicinal chemistry. A prerequisite for this new approach is an understanding of the principles of molecular recognition in protein-ligand complexes. If the three-dimensional structure of a given protein is known, this information can be directly exploited for the retrieval and design of new ligands. Structure-based ligand design is an iterative approach. First of all, it requires the crystal structure or a model derived from the crystal structure of a closely related homolog of the target protein, preferentially complexed with a ligand. This complex unravels the binding mode and conformation of a ligand under investigation and indicates the essential aspects determining its binding affinity. It is then used to generate new ideas about ways of improving an existing ligand or of developing new alternative bonding skeletons. Computational methods supplemented by molecular graphics are applied to assist this step of hypothesis generation. The features of the protein binding pocket can be translated into queries used for virtual computer screening of large compound libraries or to design novel ligands de novo. These initial proposals must be confirmed experimentally. Subsequently they are optimized toward higher affinity and better selectivity. The latter aspect is of utmost importance in defining and controlling the pharmacological profile of a ligand. A prerequisite to tailoring selectivity by rational design is a detailed understanding of molecular parameters determining selectivity. Taking examples from current drug development programs (HIV proteinase, t-RNA transglycosylase, thymidylate synthase, thrombin and, related serine proteinases), we describe recent advances in lead discovery via computer screening, iterative design, and understanding of selectivity discrimination.

Chemistry, Pharmaceutical↗
PubMed2000

Simple knowledge-based descriptors to predict protein-ligand interactions. methodology and validation.

A new type of shape descriptor is proposed to describe the spatial orientation for non-covalent interactions. It is built from simple, anisotropic Gaussian contributions that are parameterised by 10 adjustable values. The descriptors have been used to fit propensity distributions derived from scatter data stored in the IsoStar database. This database holds composite pictures of possible interaction geometries between a common central group and various interacting moieties, as extracted from small-molecule crystal structures. These distributions can be related to probabilities for the occurrence of certain interaction geometries among different functional groups. A fitting procedure is described that generates the descriptors in a fully automated way. For this purpose, we apply a similarity index that is tailored to the problem, the Split Hodgkin Index. It accounts for the similarity in regions of either high or low propensity in a separate way. Although dependent on the division into these two subregions, the index is robust and performs better than the regular Hodgkin index. The reliability and coverage of the fitted descriptors was assessed using SuperStar. SuperStar usually operates on the raw IsoStar data to calculate propensity distributions, e.g., for a binding site in a protein. For our purpose we modified the code to have it operate on our descriptors instead. This resulted in a substantial reduction in calculation time (factor of five to eight) compared to the original implementation. A validation procedure was performed on a set of 130 protein-ligand complexes, using four representative interacting probes to map the properties of the various binding sites: ammonium nitrogen, alcohol oxygen, carbonyl oxygen, and methyl carbon. The predicted 'hot spots' for the binding of these probes were compared to the actual arrangement of ligand atoms in experimentally determined protein-ligand complexes. Results indicate that the version of SuperStar that applies to our descriptors is capable to predict the above-mentioned atom types in ligands correctly with success rates of 59% and 74%, respectively, for all ligand atoms (regardless of their solvent accessibility), and a subset of solvent-inaccessible ones. If not only exact atom-type matches are counted, but also those that identify ligand atoms of similar physicochemical properties, the prediction rates rise to 75% and 89%. These rates are close to those obtained by the original SuperStar method (being 67% and 82%, respectively, for the prediction of exact matching atom types, and 81% and 91% in the case of predicting similar atom types).

Hydrogen Bonding↗
PubMed2000

Screening orthologs as an important variable in crystallization: preliminary X-ray diffraction studies of the tRNA-modifying enzyme S-adenosyl-methionine:tRNA ribosyl transferase/isomerase.

The genes encoding the tRNA-modifying enzyme S-adenosylmethionine:tRNA ribosyl transferase/isomerase (QueA) from 12 eubacterial sources were overexpressed in Escherichia coli and the resulting products were purified to homogeneity and subjected to crystallization trials. Using the hanging-drop vapour-diffusion method, crystals suitable for X-ray diffraction experiments were only obtained for the queA gene product from Bacillus subtilis. The crystals belong to the space group P422, with unit-cell parameters a = b = 100.7, c = 150.9 A. Using highly focused synchrotron radiation from the EMBL/ESRF beamline ID13 (Grenoble, France), diffraction to at least 3.2 A could be achieved. A selenomethionyl derivative of the protein was prepared and crystallized for future multiwavelength anomalous diffraction (MAD) experiments.

Bacteria↗
PubMed2000

The structure of human aldose reductase bound to the inhibitor IDD384.

The crystallographic structure of the complex between human aldose reductase (AR2) and one of its inhibitors, IDD384, has been solved at 1.7 A resolution from crystals obtained at pH 5.0. This structure shows that the binding of the inhibitor's hydrophilic head to the catalytic residues Tyr48 and His110 differs from that found previously with porcine AR2. The difference is attributed to a change in the protonation state of the inhibitor (pK(a) = 4.52) when soaked with crystals of human (at pH 5.0) or pig lens AR2 (at pH 6.2). This work demonstrates how strongly the detailed binding of the inhibitor's polar head depends on its protonation state.

Aldehyde Reductase↗
PubMed1999

Mutagenesis and crystallographic studies of Zymomonas mobilis tRNA-guanine transglycosylase to elucidate the role of serine 103 for enzymatic activity.

The tRNA modifying enzyme tRNA-guanine transglycosylase (TGT) is involved in the exchange of guanine in the first position of the anticodon with preQ1 as part of the biosynthesis of the hypermodified base queuine (Q). Mutation of Ser90 to an alanine in Escherichia coli TGT leads to a dramatic reduction of enzymatic activity (Reuter, K. et al. (1994) Biochemistry 33, 7041-7046). To further clarify the role of this residue in the catalytic center, we have mutated the corresponding Ser103 of the crystallizable Zymomonas mobilis TGT into alanine. The crystal structure of a TGT(S103A)/preQ1 complex combined with biochemical data presented in this paper suggest that Ser103 is essential for substrate orientation in the TGT reaction.

Crystallography↗
PubMed1999

Three-dimensional quantitative structure-activity relationship analyses using comparative molecular field analysis and comparative molecular similarity indices analysis to elucidate selectivity differences of inhibitors binding to trypsin, thrombin, and factor Xa.

Three-dimensional quantitative structure-activity relationship (3D QSAR) methods were applied using a training set of 72 inhibitors of the benzamidine type with respect to their binding affinities (Ki values) toward thrombin, trypsin, and factor Xa to yield statistically reliable models of good predictive power. Two methods were compared: the widely used comparative molecular field analysis (CoMFA) and the recently reported CoMSIA approach (comparative molecular similarity indices analysis). CoMSIA produced significantly better results for all correlations. Furthermore, in contrast to CoMFA, CoMSIA is not sensitive to changes in orientation of the superimposed molecules in the lattice. The correlation results obtained by CoMSIA were graphically interpreted in terms of field contribution maps allowing physicochemical properties relevant for binding to be easily mapped back onto molecular structures. The advantage of this feature is demonstrated using the maps to design new molecules. Finally, the CoMSIA method was applied to elucidate structural features among ligands which are responsible for affinity differences toward thrombin and trypsin. These selectivity-determining features were interpreted graphically in terms of spatial regions responsible for affinity discrimination. Such indicators are highly informative for the lead optimization process with respect to selectivity enhancement.

Binding Sites↗