Anxiety and stress disorders are the most commonly occurring of all mental illnesses, and current treatments are less than satisfactory. So, the discovery of novel approaches to treat anxiety disorders remains an important area of neuroscience research. Glutamate is the major excitatory neurotransmitter in the mammalian central nervous system, and G-protein-coupled metabotropic glutamate (mGlu) receptors function to regulate excitability via pre- and postsynaptic mechanisms. Various mGlu receptor subtypes, including group I (mGlu(1) and mGlu(5)), group II (mGlu(2) and mGlu(3)), and group III (mGlu(4), mGlu(7) and mGlu(8)) receptors, specifically modulate excitability within crucial brain structures involved in anxiety states. In addition, agonists for group II (mGlu(2/3)) receptors and antagonists for group I (in particular mGlu(5)) receptors have shown activity in animal and/or human conditions of fear, anxiety or stress. These studies indicate that metabotropic glutamate receptors are interesting new targets to treat anxiety disorders in humans.

Summary Muscarinic M1–M5 acetylcholine receptors are G protein-coupled receptors (GPCRs) that regulate many vital functions of the central and peripheral nervous systems. In particular, the M1 and M4 receptor subtypes have emerged as attractive drug targets for treatments of neurological disorders, such as Alzheimer's disease and schizophrenia, but the high conservation of the acetylcholine-binding pocket has spurred current research into targeting allosteric sites on these receptors. Here, we report the first crystal structures of the M1 and M4 muscarinic receptors bound to the inverse agonist, tiotropium. Comparison of these structures to each other, as well as the previously reported M2 and M3 receptor structures, reveals differences in the orthosteric and allosteric binding sites that contribute to a role in drug selectivity at this important receptor family. We also report identification of a cluster of residues that form a network linking the orthosteric and allosteric sites of the M4 receptor, which provides new insight into how allosteric modulation may be transmitted between the two spatially distinct domains.

In the absence of a 3D structure of the target biomolecule, to propose the 3D requirements for a small molecule to exhibit a particular bioactivity, one must supply both a bioactive conformation and a superposition rule for every active compound. Our strategy identifies both simultaneously. We first generate and optimize all low-energy conformations by any suitable method. For each conformation we then use ALADDIN to calculate the location of points to be considered as part of the superposition. These points include atoms in the molecule and projections from the molecule to hydrogen-bond donors and acceptors or charged groups in the binding site. These positions and the relative energy of each conformation are the input to our new program DISCO. It uses a clique-detection method to find superpositions that contain at least one conformation of each molecule and user-specified numbers of point types and chirality. DISCO is fast; for example, it takes about 1 min CPU to propose pharmacophores from 21 conformations of seven molecules. We typically run DISCO several times to compare alternative pharmacophore maps. For D2 dopamine agonists DISCO shows that the newer 2-aminothiazoles fit the traditional pharmacophore. Using site points correctly identifies the bioactive enantiomers of indoles to compare with catechols whereas using only ligand points leads to selecting the inactive enantiomer for the pharmacophore map. In addition, DISCO reproduces pharmacophore maps of benzodiazepines in the literature and proposes subtle improvements. Our experience suggests that clique-detection methods will find many applications in computational chemistry and computer-assisted molecular design.

A statistical analysis of NMR-derived binding data on 11 protein targets was performed to identify molecular motifs that are preferred for protein binding. The analysis indicates that compounds which contain a biphenyl substructure preferentially bind to a wide range of proteins and that high levels of specificity (>250-fold) can be achieved even for these small molecules. These results suggest that high-throughput screening libraries that are enriched with biphenyl-containing compounds can be expected to have increased chances of yielding high-affinity ligands for proteins, and they suggest that the biphenyl can be utilized as a template for the discovery and design of therapeutics with high affinity and specificity for a broad range of protein targets.

The antiapoptotic proteins Bcl-x(L) and Bcl-2 play key roles in the maintenance of normal cellular homeostasis. However, their overexpression can lead to oncogenic transformation and is responsible for drug resistance in certain types of cancer. This makes Bcl-x(L) and Bcl-2 attractive targets for the development of potential anticancer agents. Here we describe the structure-based discovery of a potent Bcl-x(L) inhibitor directed at a hydrophobic groove on the surface of the protein. This groove represents the binding site for BH3 peptides from proapoptotic Bcl-2 family members such as Bak and Bad. Application of NMR-based screening yielded an initial biaryl acid with an affinity (K(d)) of approximately 300 microM for the protein. Following the classical "SAR by NMR" approach, a second-site ligand was identified that bound proximal to the first-site ligand in the hydrophobic groove. From NMR-based structural studies and parallel synthesis, a potent ligand was obtained, which binds to Bcl-x(L) with an inhibition constant (K(i)) of 36 +/- 2 nM.

As part of our ongoing research to identify novel agents acting at metabotropic glutamate 2 (mGlu2) and 3 (mGlu3) receptors, we have previously reported the identification of the C4α-methyl analog of mGlu2/3 receptor agonist 1 (LY354740). This molecule, 1S,2S,4R,5R,6S-2-amino-4-methylbicyclo[3.1.0]hexane-2,6-dicarboxylate 2 (LY541850), exhibited an unexpected mGlu2 agonist/mGlu3 antagonist pharmacological profile, whereas the C4β-methyl diastereomer (3) possessed dual mGlu2/3 receptor agonist activity. We have now further explored this structure-activity relationship through the preparation of cyclic and acyclic C4-disubstituted analogs of 1, leading to the identification of C4-spirocyclopropane 5 (LY2934747), a novel, potent, and systemically bioavailable mGlu2/3 receptor agonist which exhibits both antipsychotic and analgesic properties in vivo. In addition, through the combined use of protein-ligand X-ray crystallography employing recombinant human mGlu2/3 receptor amino terminal domains, molecular modeling, and site-directed mutagenesis, a molecular basis for the observed pharmacological profile of compound 2 is proposed.

Ofloxacin, a potent quinolone antibacterial agent, has a tricyclic ring structure with a methyl group attached to the asymmetric carbon at the C-3 position on the oxazine ring. The S isomer (DR-3355) of ofloxacin has antibacterial activity up to 2 orders of magnitude greater than that of the R isomer (DR-3354). This differential antibacterial activity was not due to different drug transport mechanisms of the two isomers but was found to be derived from the inhibitory activity against the target enzyme, DNA gyrase. Previous mechanistic studies have suggested that the bactericidal effect of the drug is mediated through the stabilization of a cleavable complex via a cooperative drug binding process to a partially denatured DNA pocket created by DNA gyrase. The drug binds to supercoiled DNA in a manner similar to that to which it binds to the enzyme-DNA complex. In the present studies, we first examined the binding of the two radiolabeled ofloxacin enantiomers to supercoiled pUC9 plasmid DNA. Surprisingly, the two enantiomers possessed similar apparent binding affinities and binding cooperatives. The major difference in binding between the two stereoisomers was the molar binding ratio: 4 for the more active S isomer versus 2 for the less active R isomer. We next examined the relative binding potencies of the stereoisomers to the DNA-DNA gyrase complex. The results of a competition assay showed that (S)-ofloxacin binds 12-fold better to the complex than (R)-ofloxacin. The binding potencies of the two enantiomers and two other quinolones correlated well with their respective concentrations causing 50% inhibition against DNA gyrase. The results are interpreted by a stacking model by using the concept of the cooperative drug-DNA binding mechanism, indicating that the potencies of quinolones cannot be determined solely by the DNA binding affinity and cooperativity but can also be determined by their capability in maximally saturating the binding site. The capability of the drug in saturating the binding pocket manifests itself in an increased efficacy at inhibiting the enzyme through a direct interaction between the drug and the enzyme. The results augment the previous suggestion that the binding pocket in the enzyme-DNA complex involves multiple receptor groups including not only DNA bases but also a gyrase subunit. The higher level of potency of (S)-ofloxacin is proposed to derive from the fact that a greater number of molecules are assembled in the pocket. This greater number of molecules optimizes the interaction between the drug and the enzyme, possibly through a contact between the C-7 substituent and the quinolone pocket on the B subunit of DNA gyrase.

Virtual screening has been widely used in the drug discovery process. Ligand-based virtual screening (LBVS) methods compare a library of compounds with a known active ligand. Two notable advantages of LBVS methods are that they do not require structural information of a target receptor and that they are faster than structure-based methods. LBVS methods can be classified based on the complexity of ligand structure information utilized: one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D). Unlike 1D and 2D methods, 3D methods can have enhanced performance since they treat the conformational flexibility of compounds. In this paper, a number of 3D methods will be reviewed. In addition, four representative 3D methods of were benchmarked to understand their performance in virtual screening. Specifically, we tested overall performance in key aspects including the ability of finding dissimilar active compounds, and computational speed.