We report the crystal structure of alanine racemase from Mycobacterium tuberculosis (Alr(Mtb)) at 1.9 A resolution. In our structure, Alr(Mtb) is found to be a dimer formed by two crystallographically different monomers, each comprising 384 residues. The domain makeup of each monomer is similar to that of Bacillus and Pseudomonas alanine racemases and includes both an alpha/beta-barrel at the N-terminus and a C-terminus primarily made of beta-strands. The hinge angle between these two domains is unique for Alr(Mtb), but the active site geometry is conserved. In Alr(Mtb), the PLP cofactor is covalently bound to the protein via an internal aldimine bond with Lys42. No guest substrate is noted in its active site, although some residual electron density is observed in the enzyme's active site pocket. Analysis of the active site pocket, in the context of other known alanine racemases, allows us to propose the inclusion of conserved residues found at the entrance to the binding pocket as additional targets in ongoing structure-aided drug design efforts. Also, as observed in other alanine racemase structures, PLP adopts a conformation that significantly distorts the planarity of the extended conjugated system between the PLP ring and the internal aldimine bond.

Computationally efficient structure-based virtual screening methods have recently been reported that seek to find effective means to utilize experimental structure information without employing detailed molecular docking calculations. These tools can be coupled with efficient experimental screening technologies to improve the probability of identifying hits and leads for drug discovery research. Commercial software ROCS (rapid overlay of chemical structures) from Open Eye Scientific is such an example, which is a shape-based virtual screening method using the 3D structure of a ligand, typically from a bound X-ray costructure, as the query. We report here the development of a new structure-based pharmacophore search method (called Shape4) for virtual screening. This method adopts a variant of the ROCS shape technology and expands its use to work with an empty crystal structure. It employs a rigorous computational geometry method and a deterministic geometric casting algorithm to derive the negative image (i.e., pseudoligand) of a target binding site. Once the negative image (or pseudoligand) is generated, an efficient shape comparison algorithm in the commercial OE SHAPE Toolkit is adopted to compare and match small organic molecules with the shape of the pseudoligand. We report the detailed computational protocol and its computational validation using known biologically active compounds extracted from the WOMBAT database. Models derived for five selected targets were used to perform the virtual screening experiments to obtain the enrichment data for various virtual screening methods. It was found that our approach afforded similar or better enrichment ratios than other related methods, often with better diversity among the top ranking computational hits.

Methicillin-resistant Staphylococcus aureus (MRSA), a complex of multidrug resistant Gram-positive bacterial strains, has proven especially problematic in both hospital and community-settings, resulting in increased mortality rates and hospitalization costs. Emergence of resistance even to vancomycin, the standard reference for MRSA treatment, builds up pressure for the search of novel alternatives. We report potent natural resin acid-based cationic antimicrobial compounds and polymers that exhibit surprising antimicrobial activity against a range of MRSA strains, yet are largely non-toxic against mammalian cells.Molecular dynamics simulations and dye-leakage assays with anionic phospholipid membrane mimics of bacteria demonstrate a membrane-lysing effect induced by unique fused ring structures of resin acids that may constitute the principal mechanism of action for selective lysis of bacterial cells over mammalian cells. Our antimicrobial materials are derived from an unlikely yet abundant natural source, and offer a novel alternative to currently-used approaches.

Electrostatic surface potentials in the vestibule of the nicotinic acetylcholine receptor (nAChR) were computed from structural models using the University of Houston Brownian Dynamics program to determine their effect on ion conduction and ionic selectivity. To further determine whether computed potentials accurately reflect the electrostatic environment of the channel, the potentials were used to predict the rate constants for diffusion-enhanced fluorescence energy transfer; the calculated energy transfer rates are directly comparable with those determined experimentally (see companion article by Meltzer et al. in this issue). To include any effects on the local potentials by the bound acceptor fluorophore crystal violet, its binding site was first localized within the pore by fluorescence energy transfer measurements from dansyl-C6-choline bound to the agonist sites and also by simulations of binding using Autodock. To compare the computed potentials with those determined experimentally, we used the predicted energy transfer rates from Tb3+ chelates of varying charge to calculate an expected potential using the Boltzmann relationship. This expected potential (from -20 to -40 mV) overestimates the values determined experimentally (from -10 to -25 mV) by two- to fourfold at similar conditions of ionic strength. Although the results indicate a basic discrepancy between experimental and computed surface potentials, both methods demonstrate that the vestibular potential has a relatively small effect on conduction and selectivity.

Optimization of chemical library composition affords more efficient identification of hits from biological screening experiments. The optimization could be achieved through rational selection of reagents used in combinatorial library synthesis. However, with a rapid advent of parallel synthesis methods and availability of millions of compounds synthesized by many vendors, it may be more efficient to design targeted libraries by means of virtual screening of commercial compound collections. This chapter reviews the application of advanced cheminformatics approaches such as quantitative structure-activity relationships (QSAR) and pharmacophore modeling (both ligand and structure based) for virtual screening. Both approaches rely on empirical SAR data to build models; thus, the emphasis is placed on achieving models of the highest rigor and external predictive power. We present several examples of successful applications of both approaches for virtual screening to illustrate their utility. We suggest that the expert use of both QSAR and pharmacophore models, either independently or in combination, enables users to achieve targeted libraries enriched with experimentally confirmed hit compounds.

The electrostatic environments near the acetylcholine binding sites on the nicotinic acetylcholine receptor (nAChR) and acetylcholinesterase were measured by diffusion-enhanced fluorescence energy transfer (DEFET) to determine the influence of long-range electrostatic interactions on ligand binding kinetics and net binding energy. Changes in DEFET from variously charged Tb3+ -chelates revealed net potentials of -20 mV at the nAChR agonist sites and -14 mV at the entrance to the AChE active site, in physiological ionic strength conditions. The potential at the alphadelta-binding site of the nAChR was determined independently in the presence of d-tubocurarine to be -14 mV; the calculated potential at the alphagamma-site was approximately threefold stronger than at the alphadelta-site. By determining the local potential in increasing ionic strength, Debye-Hückel theory predicted that the potentials near the nAChR agonist binding sites are constituted by one to three charges in close proximity to the binding site. Examination of the binding kinetics of the fluorescent acetylcholine analog dansyl-C6-choline at ionic strengths from 12.5 to 400 mM revealed a twofold decrease in association rate. Debye-Hückel analysis of the kinetics revealed a similar charge distribution as seen by changes in the potentials. To determine whether the experimentally determined potentials are reflected by continuum electrostatics calculations, solutions to the nonlinear Poisson-Boltzmann equation were used to compute the potentials expected from DEFET measurements from high-resolution models of the nAChR and AChE. These calculations are in good agreement with the DEFET measurements for AChE and for the alphagamma-site of the nAChR. We conclude that long-range electrostatic interactions contribute -0.3 and -1 kcal/mol to the binding energy at the nAChR alphadelta- and alphagamma-sites due to an increase in association rates.

3D molecular shape similarity search has recently become an attractive method for virtual screening and scaffold hopping in drug discovery and chemical genomics research. Among these 3D similarity methods is ROCS (Rapid Overlay of Chemical Structures), a popular tool because of its efficiency and effectiveness. However, searching a large multiconformer molecular database remains a very challenging task because of the nature of such calculations. To simplify shape similarity calculations and potentially increase the efficiency for large scale virtual screening, we have explored an alternative shape similarity approach that does not depend on multiconformers of molecules. The hypothesis underlying this approach is that similar chemical structures tend to have similar 2D chemical depictions and that shape comparison techniques can be utilized to effectively compare the shapes between chemical depictions. We use a 2D depiction program to generate 2-D chemical drawings for both the query molecule and database molecules. We have built a 2D shape comparison program based on the OESHAPE Toolkit (OE Scientific, NM) that compares the molecular depictions and quantifies the shape similarity between the molecules. We demonstrate that this unconventional 2D shape similarity method performs fairly well in virtual screening experiments compared to the 3D Shape method ROCS, with an added advantage of its computational efficiency.

Shape complementarity is a critically important factor in molecular recognition among drugs and their biological receptors. The notion that molecules with similar 3D shapes tend to have similar biological activity has been recognized and implemented in computational drug discovery tools for decades. But the low computational efficiency and the lack of widely accessible software tools limited the use of early shape-matching algorithms. However, recent development of fast and accurate shape comparison tools has changed the landscape, and facilitated the wide spread use of both the ligand-based and receptor-based shape-matching technologies in drug discovery. In this article, we summarize some of the well-known shape algorithms. We first describe the computational principles for both the superposition-based and the superposition-free shape-matching methods. These include ROCS (Rapid Overlay of Compound Structures), SQ, and the CatShape method in the former category; and the shape signatures algorithm and USR (Ultrafast Shape Recognition) that belong to the latter category. We then highlight some recent validation studies and practical applications of various shape technologies. Because of the rapid development of modern shape-matching algorithms, and the increasingly affordable computational resources and software tools, we anticipate much broader use of the molecular shape technologies in future drug discovery. They will be especially useful in chemogenomics research, where large scale associations between small molecules and protein targets are studied. Thus, molecular shape technologies, together with well-defined pharmacophore constraints, can afford both efficient and effective means for drug discovery and chemical genomics research.