Discovery and hit-to-lead optimization of novel allosteric glucokinase activators.

We report on a hit generation and hit-to-lead program of a novel class of glucokinase activators (GKAs). Hit compounds, activators at low glucose concentration only were identified by vHTS. Scaffold modification reliably afforded activators also at high substrate level. Potency was increased by introduction of a hydrogen bond acceptor as proposed by molecular docking. Replacement of the initial alkylene linkers with a rigid 1,2-phenylene motif followed by further studies eventually furnished a series of potent lead compounds exhibiting steep SAR.

Targeted scoring functions for virtual screening.

The benefit offered by virtual screening methods during the early drug discovery process is directly related to the predictivity of scoring functions that assess protein-ligand binding affinity. The scoring of protein-ligand complexes, however, is still a challenge: despite great efforts, a universal and accurate scoring method has not been developed up to now. Targeted scoring functions, in contrast, enhance virtual screening performance significantly. This review analyzes recent developments and future directions in the area of targeted scoring functions.

Natural product inhibitors of protein-protein interactions mediated by Src-family SH2 domains.

In this Letter, we report the natural products salvianolic acid A, salvianolic acid B, and caftaric acid as inhibitors of the protein-protein interactions mediated by the SH2 domains of the Src-family kinases Src and Lck, two established disease targets. Moreover, we propose a binding mode for the inhibitors based on molecular modeling, which will facilitate chemical optimization efforts of these important lead structures for drug discovery.

Robust optimization of scoring functions for a target class.

Target-specific optimization of scoring functions for protein-ligand docking is an effective method for significantly improving the discrimination of active and inactive molecules in virtual screening applications. Its applicability, however, is limited due to the narrow focus on, e.g., single protein structures. Using an ensemble of protein kinase structures, the publically available directory of useful decoys ligand dataset, and a novel multi-factorial optimization procedure, it is shown here that scoring functions can be tuned to multiple targets of a target class simultaneously. This leads to an improved robustness of the resulting scoring function parameters. Extensive validation experiments clearly demonstrate that (1) virtual screening performance for kinases improves significantly; (2) variations in database content affect this kind of machine-learning strategy to a lesser extent than binary QSAR models, and (3) the reweighting of interaction types is of particular importance for improved screening performance.

Proteasome inhibition by peptide-semicarbazones.

Peptide-semicarbazones derived from Z-Trp-Trp-Phe-aldehyde inhibit the chymotryptic activity of the human proteasome at nanomolar concentrations, but are less active in a NFkappaB reporter gene assay. Cyclic semicarbazones, in contrast, combine a strong inhibitory effect on the enzyme with an inhibition of NFkappaB signaling in the nanomolar range. In addition, a practical synthesis for scale-up of such compounds was developed.

Optimizing the signal-to-noise ratio of scoring functions for protein--ligand docking.

Empirical scoring functions provide estimates of the free energy of protein-ligand binding in situations when atomic-scale simulations are intractable, for example, in virtual high-throughput screening. Currently, such scoring functions are often inaccurate, and further improvements are complicated by the lack of reliable training data, the complex interplay between scoring functions and docking algorithms, and an inconsistent statistical treatment of positive and negative training data. In comparison to various other performance measures of scoring functions, "analysis of variance" provides a well-behaved objective function for optimization, which focuses on the signal-to-noise ratio of ligand-decoy discrimination. In combination with a large database of ligands and decoys, an in situ optimization of scoring function parameters was able to generate improved, target-specific scoring functions for three different proteins of pharmaceutical interest: cyclin-dependent kinase 2, the estrogen receptor, and cyclooxygenase-2. Statistical analysis of the improvements observed in "receiver-operating characteristic" curves showed that the optimized scoring functions achieved a significantly (between p < 0.0001 and p < 0.05) higher enrichment of true ligands. A scaffold dependence of the resulting binding modes was observed, which is discussed in conjunction with the rigid receptor hypothesis commonly made in protein-ligand docking. In summary, the approach described here represents a well-adapted statistical method for setting up scoring functions.

Essential factors for successful virtual screening.

Virtual high-throughput screening (vHTS) is a powerful technique for identifying hit molecules as starting points for medicinal chemistry. Numerous successful applications of vHTS have been published using a large variety of methodologies. This review attempts to identify the essential factors for successful virtual screening in the hit identification phase.

A novel class of potent NF-kappaB signaling inhibitors.

A novel class of NF-kappaB pathway signaling inhibitors was discovered by virtual screening, medicinal chemistry, and QSAR analysis. An initial set of compounds inhibited NF-kappaB signaling in a whole cell reporter gene assay in the micro-molar range. Activity was improved step by step by medicinal chemistry to yield nano-molar signaling inhibitors.

Virtual high-throughput screening of molecular databases.

Virtual high-throughput screening (vHTS) is an efficient and widely applicable method used to identify initial hit compounds for pharmaceutical research. Despite its widespread use, several aspects of protein structure-based vHTS can still be optimized, particularly its accuracy and speed in generating results. Recent developments that address these issues include machine learning and implicit solvation methods. Various machine learning methods are available to improve vHTS accuracy, for example, target-specific optimization of scoring functions, the integration of essential protein-ligand interactions, and the application of negative training data. Implicit solvation methods are exemplified by the molecular mechanics Poisson-Boltzmann solvent accessible surface area approach. Furthermore, grid computing and intelligent database screening approaches are used to improve the speed of vHTS.

Assessing the discriminatory power of scoring functions for virtual screening.

The efficiency of scoring functions for hit identification is usually quantified in terms of enrichment factors and enrichment curves. Close inspection of simulated and real score distributions from virtual screening, however, suggests that 'analysis of variance' (ANOVA) is a more reliable method for assessing their performance. Using ANOVA to quantify the discriminatory power of scoring functions with respect to ligands, decoys, and a reproducible reference database has the potential to facilitate the advancement of scoring functions significantly.

ProPose: steered virtual screening by simultaneous protein-ligand docking and ligand-ligand alignment.

The 'model-free' screening engine ProPose implements a general method for performing simultaneous protein-ligand docking, ligand-ligand alignment, pharmacophore queries-and combinations thereof-in order to incorporate a priori information into screening protocols. In this manuscript we describe a case study on herpes simplex virus thymidine kinase, an important antiviral drug target, where we evaluate different approaches for handling a specific type of a priori information, i.e., multiple target structures. We demonstrate that a simultaneous alignment on two target structures--in conjunction with logic operations on interactions and docking constraints derived from protein structure--is an effective means of (i) improving the enrichment of chemical substructures that are compatible with the a priori known ligands, (ii) ensuring the steric fit into the target protein, and (iii) handling target flexibility. The combination of ligand- and receptor-based methods steers the virtual screening by ranking molecules according to the similarity of their interaction pattern with known ligands, thereby--to some extent--outweighing the deficiencies of simple scoring functions often used in initial virtual screening.

ProPose: a docking engine based on a fully configurable protein-ligand interaction model.

Virtual high-throughput screening of molecular databases and in particular high-throughput protein-ligand docking are both common methodologies that identify and enrich hits in the early stages of the drug design process. Current protein-ligand docking algorithms often implement a program-specific model for protein-ligand interaction geometries. However, in order to create a platform for arbitrary queries in molecular databases, a new program is desirable that allows more manual control of the modeling of molecular interactions. For that reason, ProPose, an advanced incremental construction docking engine, is presented here that implements a fast and fully configurable molecular interaction and scoring model. This program uses user-defined, discrete, pharmacophore-like representations of molecular interactions that are transformed on-the-fly into a continuous potential energy surface, allowing for the incorporation of target specific interaction mechanisms into docking protocols in a straightforward manner. A torsion angle library, based on semi-empirical quantum chemistry calculations, is used to provide minimum energy torsion angles for the incremental construction algorithm. Docking results of a diverse set of protein-ligand complexes from the Protein Data Bank demonstrate the feasibility of this new approach. As a result, the seamless integration of pharmacophore-like interaction types into the docking and scoring scheme implemented in ProPose opens new opportunities for efficient, receptor-specific screening protocols. [figure: see text]. ProPose--a fully configurable protein-ligand docking program--transforms pharmacophores into a smooth potential energy surface.

Expansion of the genetic code enables design of a novel "gold" class of green fluorescent proteins.

Much effort has been dedicated to the design of significantly red shifted variants of the green fluorescent protein (GFP) from Aequoria victora (av). These approaches have been based on classical engineering with the 20 canonical amino acids. We report here an expansion of these efforts by incorporation of an amino substituted variant of tryptophan into the "cyan" GFP mutant, which turned it into a "gold" variant. This variant possesses a red shift in emission unprecedented for any avFP, similar to "red" FPs, but with enhanced stability and a very low aggregation tendency. An increasing number of non-natural amino acids are available for chromophore redesign (by engineering of the genetic code) and enable new general strategies to generate novel classes of tailor-made GFP proteins.

Backbone dynamics of green fluorescent protein and the effect of histidine 148 substitution.

Green fluorescent protein (GFP) and its mutants have become valuable tools in molecular biology. GFP has been regarded as a very stable and rigid protein with the beta-barrel shielding the chromophore from the solvent. Here, we report the 15N nuclear magnetic resonance (NMR) studies on the green fluorescent protein (GFPuv) and its mutant His148Gly. 15N NMR relaxation studies of GFPuv show that most of the beta-barrel of GFP is rigid on the picosecond to nanosecond time scale. For several regions, including the first alpha-helix and beta-sheets 3, 7, 8, and 10, increased hydrogen-deuterium exchange rates suggest a substantial conformational flexibility on the microsecond to millisecond time scales. Mutation of residue 148 located in beta-sheet 7 is known to have a strong impact on the fluorescence properties of GFPs. UV absorption and fluorescence spectra in combination with 1H-15N NMR spectra indicate that the His148Gly mutation not only reduces the absorption of the anionic chromophore state but also affects the conformational stability, leading to the appearance of doubled backbone amide resonances for a number of residues. This suggests the presence of two conformations in slow exchange on the NMR time scale in this mutant.

Purification, crystallization, NMR spectroscopy and biochemical analyses of alpha-phycoerythrocyanin peptides.

The alpha-phycoerythrocyanin subunits of the different phycoerythrocyanin complexes of the phycobilisomes from the cyanobacterium Mastigocladus laminosus perform a remarkable photochemistry. Similar to phytochromes - the photoreceptors of higher plants - the spectral properties of the molecule reversibly change according to the irradiation wavelength. To enable extensive analyses, the protein has been produced at high yield by improving purification protocols. As a result, several comparative studies on the Z- and E-configurations of the intact alpha-subunit, and also on photoactive peptides originating from nonspecific degradations of the chromoprotein, were possible. The analyses comprise absorbance, fluorescence and CD spectroscopy, crystallization, preliminary X-ray measurements, mass spectrometry, N-terminal amino acid sequencing and 1D NMR spectroscopy. Intact alpha-phycoerythrocyanin aggregates significantly, due to hydrophobic interactions between the two N-terminal helices. Removal of these helices reduces the aggregation but also destabilizes the protein fold. The complete subunit could be crystallized in its E-configuration, but the X-ray measurement conditions must be improved. Nevertheless, NMR spectroscopy on a soluble photoactive peptide presents the first insight into the complex chromophore protein interactions that are dependent on the light induced state. The chromophore environment in the Z-configuration is rigid whereas other regions of the protein are more flexible. In contrast, the E-configuration has a mobile chromophore, especially the pyrrole ring D, while other regions of the protein rigidified compared to the Z-configuration.

Slow exchange in the chromophore of a green fluorescent protein variant.

Green fluorescent protein and its mutants have become valuable tools in molecular biology. They also provide systems rich in photophysical and photochemical phenomena of which an understanding is important for the development of new and optimized variants of GFP. Surprisingly, not a single NMR study has been reported on GFPs until now, possibly because of their high tendency to aggregate. Here, we report the (19)F nuclear magnetic resonance (NMR) studies on mutants of the green fluorescent protein (GFP) and cyan fluorescent protein (CFP) labeled with fluorinated tryptophans that enabled the detection of slow molecular motions in these proteins. The concerted use of dynamic NMR and (19)F relaxation measurements, supported by temperature, concentration- and folding-dependent experiments provides direct evidence for the existence of a slow exchange process between two different conformational states of CFP. (19)F NMR relaxation and line shape analysis indicate that the time scale of exchange between these states is in the range of 1.2-1.4 ms. Thermodynamic analysis revealed a difference in enthalpy (Delta)H(0) = (18.2 +/- 3.8) kJ/mol and entropy T(Delta)S(0) = (19.6 +/- 1.2) kJ/mol at T = 303 K for the two states involved in the exchange process, indicating an entropy-enthalpy compensation. The free energy of activation was estimated to be approximately 60 kJ/mol. Exchange between two conformations, either of the chromophore itself or more likely of the closely related histidine 148, is suggested to be the structural process underlying the conformational mobility of GFPs. The possibility to generate a series of single-atom exchanges ("atomic mutations") like H --> F in this study offers a useful approach for characterizing and quantifying dynamic processes in proteins by NMR.

Phosphorylation and flexibility of cyclic-AMP-dependent protein kinase (PKA) using (31)P NMR spectroscopy.

Cell signaling pathways rely on phosphotransfer reactions that are catalyzed by protein kinases. The protein kinases themselves are typically regulated by phosphorylation and concurrent structural rearrangements, both near the catalytic site and elsewhere. Thus, physiological function requires posttranslational modification and deformable structures. A prototypical example is provided by cyclic AMP-dependent protein kinase (PKA). It is activated by phosphorylation, is inhomogeneously phosphorylated when expressed in bacteria, and exhibits a wide range of dynamic properties. Here we use (31)P nuclear magnetic resonance (NMR) spectroscopy to characterize the phosphorylation states and to estimate the flexibility of the phosphorylation sites of 2-, 3-, and 4-fold phosphorylated PKA. The phosphorylation sites Ser10, Ser139, Thr197, and Ser338 are assigned to individual NMR resonances, assisted by complexation with AMP-PNP and dephosphorylation with alkaline phosphatase. Rotational diffusion correlation times estimated from resonance line widths show progressively increasing flexibilities for phosphothreonine 197, phosphoserines 139 and 338, and disorder at phosphoserine 10, consistent with crystal structures of PKA. However, because the apparent rotational diffusion correlation time fitted for phosphothreonine 197 of the activation loop is longer than the overall PKA rotational diffusion time, microsecond to millisecond time scale conformational exchange effects involving motions of phosphothreonine 197 are probable. These may represent "open"-"closed" transitions of the uncomplexed protein in solution. These data represent direct measurements of flexibilities also associated with functional properties, such as ATP binding and membrane association, and illustrate the applicability of (31)P NMR for functional and dynamic characterization of protein kinase phosphorylation sites.