Inhibitor Bound Dengue NS2B-NS3pro Reveals Multiple Dynamic Binding Modes.

Dengue virus poses a significant global health threat as the source of increasingly deleterious dengue fever, dengue hemorrhagic fever, and dengue shock syndrome. As no specific antiviral treatment exists for dengue infection, considerable effort is being applied to discover therapies and drugs for maintenance and prevention of these afflictions. The virus is primarily transmitted by mosquitoes, and infection occurs following viral endocytosis by host cells. Upon entering the cell, viral RNA is translated into a large multisubunit polyprotein which is post-translationally cleaved into mature, structural and nonstructural (NS) proteins. The viral genome encodes the enzyme to carry out cleavage of the large polyprotein, specifically the NS2B-NS3pro cofactor-protease complex-a target of high interest for drug design. One class of recently discovered NS2B-NS3pro inhibitors is the substrate-based trifluoromethyl ketone containing peptides. These compounds interact covalently with the active site Ser135 via a hemiketal adduct. A detailed picture of the intermolecular protease/inhibitor interactions of the hemiketal adduct is crucial for rational drug design. We demonstrate, through the use of protein- and ligand-detected solution-state 19F and 1H NMR methods, an unanticipated multibinding mode behavior of a representative of this class of inhibitors to dengue NS2B-NS3pro. Our results illustrate the highly dynamic nature of both the covalently bound ligand and protease protein structure, and the need to consider these dynamics when designing future inhibitors in this class.

Designing a diverse high-quality library for crystallography-based FBDD screening.

A well-chosen set of fragments is able to cover a large chemical space using a small number of compounds. The actual size and makeup of the fragment set is dependent on the screening method since each technique has its own practical limits in terms of the number of compounds that can be screened and requirements for compound solubility. In this chapter, an overview of the general requirements for a fragment library is presented for different screening platforms. In the case of the FBDD work at Johnson & Johnson Pharmaceutical Research and Development, L.L.C., our main screening technology is X-ray crystallography. Since every soaked protein crystal needs to be diffracted and a protein structure determined to delineate if a fragment binds, the size of our initial screening library cannot be a rate-limiting factor. For this reason, we have chosen 900 as the appropriate primary fragment library size. To choose the best set, we have developed our own mix of simple property ("Rule of 3") and "bad" substructure filtering. While this gets one a long way in terms of limiting the fragment pool, there are still tens of thousands of compounds to choose from after this initial step. Many of the choices left at this stage are not drug-like, so we have developed an FBDD Score to help select a 900-compound set. The details of this score and the filtering are presented.

Electron density guided fragment-based lead discovery of ketohexokinase inhibitors.

A fragment-based drug design paradigm has been successfully applied in the discovery of lead series of ketohexokinase inhibitors. The paradigm consists of three iterations of design, synthesis, and X-ray crystallographic screening to progress low molecular weight fragments to leadlike compounds. Applying electron density of fragments within the protein binding site as defined by X-ray crystallography, one can generate target specific leads without the use of affinity data. Our approach contrasts with most fragment-based drug design methodology where solution activity is a main design guide. Herein we describe the discovery of submicromolar ketohexokinase inhibitors with promising druglike properties.

Macrocyclic BACE inhibitors: Optimization of a micromolar hit to nanomolar leads.

We have identified macrocyclic inhibitors of the aspartic protease BACE, implicated in the etiology of Alzheimer's disease. An X-ray structure of screening hit 1 in the BACE active site revealed a hairpin conformation suggesting that constrained macrocyclic derivatives may also bind there. Several of the analogs we prepared were >100x more potent than 1, such as 7 (5 nM K(i)).

Hit triage using efficiency indices after screening of compound libraries in drug discovery.

Fragment-based drug discovery (FBDD) is an important new tool to understand the molecule basis of ligand-biological target interactions. By combining optimal fragments, it is often possible to construct larger molecular weight compounds that have greater potency in a shorter period of time than can been achieved by the initial screening of larger molecular weight compound libraries. Alternatively, if screening of more traditional larger libraries has occurred, then it may be possible to analyze the data during the process of hit triage in such as way as to essentially adopt a fragment-based approach in reverse. In this review, we highlight general principles associated with the efficiency indices such as Ligand Efficiency (LE) in which screening data is normalized for biophysical properties such as molecular size. We further focus on the concept of Fit Quality (FQ), which standardizes LE values across molecular weight for more realistic, direct comparison. Using these simple concepts, one can apply FBDD routinely in the stage of hit triage when evaluating the data obtained after screening of compound libraries in drug discovery.

Ligand efficiency and fragment-based drug discovery.

The use of fragment-based drug discovery (FBDD) has increased in recent years since it is more likely to produce a better optimized compound of lower molecular weight. Ligand efficiency (LE) has become important for assessing fragments, HTS hits, and resulting optimized ligands. LE is useful for comparing ligands of equal molecular weight, but is ineffective for comparisons of ligands of differing molecular weight. LE has a strong dependence on molecular size, which has led us to develop a size-independent efficiency score termed fit quality. Evaluating FBDD examples from the literature using LE and fit quality, we find that, in general, the LEs of starting fragments are greater than those of larger, more elaborated, structures. Fit quality scores, however, tend to improve upon optimization of the fragments.

Discovery of piperidine carboxamide TRPV1 antagonists.

A series of piperidine carboxamides were developed as potent antagonists of the transient receptor potential vanilloid-1 (TRPV1), an emerging target for the treatment of pain. A focused library of polar head groups led to the identification of a benzoxazinone amide that afforded good potency in cell-based assays. Synthesis and a QSAR model will be presented.

Ligand binding efficiency: trends, physical basis, and implications.

Ligand efficiency (i.e., potency/size) has emerged as an important metric in drug discovery. In general, smaller, more efficient ligands are believed to have improved prospects for good drug properties (e.g., bioavailability). Our analysis of thousands of ligands across a variety of targets shows that ligand efficiency is dependent on ligand size with smaller ligands having greater efficiencies, on average, than larger ligands. We propose two primary causes for this size dependence: the inevitable reduction in the quality of fit between ligand and receptor as the ligand becomes larger and more complex and the reduction in accessible ligand surface area on a per atom basis as size increases. These results have far-ranging implications for analysis of high-throughput screening hits, fragment-based approaches to drug discovery, and even computational models of potency.

Potent, nonpeptide inhibitors of human mast cell tryptase. Synthesis and biological evaluation of novel spirocyclic piperidine amide derivatives.

We have explored a series of spirocyclic piperidine amide derivatives (5) as tryptase inhibitors. Thus, 4 (JNJ-27390467) was identified as a potent, selective tryptase inhibitor with oral efficacy in two animal models of airway inflammation (sheep and guinea pig asthma models). An X-ray co-crystal structure of 4 x tryptase revealed a hydrophobic pocket in the enzyme's active site, which is induced by the phenylethynyl group and is comprised of amino acid residues from two different monomers of the tetrameric protein.

2-Amino-3,4-dihydroquinazolines as inhibitors of BACE-1 (beta-site APP cleaving enzyme): Use of structure based design to convert a micromolar hit into a nanomolar lead.

A new aspartic protease inhibitory chemotype bearing a 2-amino-3,4-dihydroquinazoline ring was identified by high-throughput screening for the inhibition of BACE-1. X-ray crystallography revealed that the exocyclic amino group participated in a hydrogen bonding array with the two catalytic aspartic acids of BACE-1 (Asp(32), Asp(228)). BACE-1 inhibitory potency was increased (0.9 microM to 11 nM K(i)) by substitution into the unoccupied S(1)' pocket.

The role of molecular size in ligand efficiency.

Ligand efficiency is a simple metric for assessing whether a ligand derives its potency from optimal fit with the protein target or simply by virtue of making many contacts. Comparison of protein-ligand binding affinities for over 8000 ligands with 28 protein targets shows conclusively that the average ligand binding affinities are not linear with molecular size. It is therefore important to scale ligand efficiencies by the size of the ligand, particularly where small ligands (e.g., fragments) are involved. We propose a simple 'fit quality' metric that removes this dependence.

Synthesis and biological evaluation of type VI beta-turn templated RGD peptidomimetics.

We report the design, synthesis, and binding affinities of a family of cyclic RGD peptides attached to type VI beta-turn scaffolds. The analogues prepared exhibit interesting binding data to the isolated receptors alphavbeta3 and alphavbeta5. The results demonstrate the utility of these type VI beta-turn scaffolds for the constraint of biologically relevant peptides.

Linear interaction energy models for beta-secretase (BACE) inhibitors: Role of van der Waals, electrostatic, and continuum-solvation terms.

Computing the binding affinity of a protein-ligand complex is one of the most fundamental and difficult tasks in computer-aided drug design. Many approaches for computing binding affinities can be classified as linear interaction energy (LIE) models as they rely on some type of linear fit of computed interaction energies between ligand and protein. We have examined the computed interaction energies of a series of beta-secretase (BACE) inhibitors in terms of van der Waals, coulombic, and continuum-solvation contributions to ligand binding. We have also systematically examined the effect of different protonation states of the protein and ligands. We find that the binding affinities are relatively insensitive to the protonation state of the protein when neutral ligands are considered. Inclusion of charged ligands leads to large deviations in the coulomb, solvation, and even van der Waals terms. The latter is due to increased repulsive van der Waals interactions in the complex due to the strong coulomb attraction found between oppositely charged functional groups in the protein and ligand. In general, we find that the best models are obtained when the protein is judiciously charged (e.g. Asp32-, Arg235+) and the potentially charged ligands are treated as neutral.

A two-state homology model of the hERG K+ channel: application to ligand binding.

Homology models based on available K+ channel structures have been used to construct a multiple state representation of the hERG cardiac K+ channel. These states are used to capture the flexibility of the channel. We show that this flexibility is essential in order to correctly model the binding affinity of a set of diverse ligands. Using this multiple state approach, a binding affinity model was constructed for set of known hERG channel binders. The predicted pIC50s are in good agreement with experiment (RMSD: 0.56 kcal/mol). In addition, these calculations provide structures for the bound ligands that are consistent with published mutation studies. These computed ligand bound complex structures can be used to guide synthesis of analogs with reduced hERG liability.

Defining privileged reagents using subsimilarity comparison.

We have developed a new method for assigning a drug-like score to reagents. This algorithm uses topological torsion (TT) 2D descriptors to compute the subsimilarity of any given reagent to a substructural element of any compound in the CMC. The utility of this approach is demonstrated by scoring a test set of reagents derived from the "Comprehensive Survey of Combinatorial Library Synthesis: 2000" (J. Comb. Chem.). R-groups were extracted from the most-active compounds found in each of the reviewed libraries, and the distribution of the subsimilarity scores for these monomers were compared to the ACD. This comparison showed a dramatic shift in the distribution of the JCC R-group subset toward higher subsimilarity scores in comparison to the entire ACD database. The ACD was also used to examine the relationship between molecular weight and various subsimilarity scoring algorithms. This analysis was used to derive a subsimilarity score that is less biased by molecular weight.

Piperidine-containing beta-arylpropionic acids as potent antagonists of alphavbeta3/alphavbeta5 integrins.

The synthesis and SAR of a new class of piperidine-based alphavbeta3/alphavbeta5 integrin antagonists is described. Replacement of an amide bond in a prototype isonipecotamide by a C-C isostere, and adjustment of the spacer length between the carboxylic acid and basic moieties, led to low nanomolar antagonists of alphavbeta3 and/or alphavbeta5 integrins with excellent selectivity versus alpha(IIb)beta3.

A Web-based chemoinformatics system for drug discovery.

One of the key questions that must be addressed when implementing a chemoinformatics system is whether the tools will be designed for use by the expert user or by the "bench scientist." This decision can impact not only the style of tools that are rolled out, but is also a factor in terms of how these tools are delivered to the end users. The system that we outline here was designed for use by the non-expert user. As such, the tools that we discuss are in many cases simplified versions of some common algorithms used in chemoinformatics. In addition, the focus is on how to distribute these tools using a web-services interface, which greatly simplifies delivering new protocols to the end user.

Noncovalent self-assembly of bicyclo[4.2.2]diketopiperazines: influence of saturation in the bridging carbacyclic ring.

[structure: see text] We have prepared 7,9-diazabicyclo[4.2.2]dec-3-ene-8,10-dione (3) and 7,9-diazabicyclo[4.2.2]decane-8,10-dione (4), which differ by virtue of the degree of unsaturation in the bridging carbacyclic tether on a 2,5-diketopiperazine. Remarkably different self-assembly patterns were observed in the solid state for the two compounds, attributed to subtle variations in the conformational constraints imposed by the tether.

Calculation of the binding affinity of beta-secretase inhibitors using the linear interaction energy method.

It has been shown that the rate-limiting step in the production of beta-amyloid peptide (Abeta) is the proteolytric cleavage of the membrane-bound beta-amyloid precursor protein (APP) by beta-secretase (BACE). Since the accumulation of Abeta has been implicated as one of the key events in the progression of Alzheimer's disease, BACE has become an important therapeutic target. Recently, two crystal structures of BACE cocrystallized with the inhibitors OM99-2 and OM00-3 were published by Tang and co-workers. In addition, the Ghosh group has published binding data on a series of inhibitors based on their initial lead, OM99-2. Using this set as a basis, we have developed a model for the binding affinity of these ligands to BACE using the linear interaction energy method. The best binding affinity model for the full set of ligands had a RMSD of 1.10 kcal/mol. The best model excluding the two charged ligands had a RMSD of 0.87 kcal/mol.