Novel inhibitors of anthrax edema factor
Graphical abstract
Introduction
Many pathogenic bacteria, regardless of their cellular morphology and grouping, produce toxins with similar functions that are often plasmid encoded. For example, Bacillus anthracis, a Gram-positive, spore-forming, rod-shaped bacterium, produces two types of factors that enhance its lethality, a polysaccharide capsule1 and two protein toxins, lethal toxin (LT) and edema toxin (ET). Both toxins are lethal when injected into mice, and they suppress the functions of macrophages, polymorphoneutrophils, and lymphocytes. One component of both toxins is protective antigen (PA), which enables the cell entry of the enzymatic toxin components lethal factor (LF) and edema factor (EF).2 LF contains metalloprotease activity that is specific for the MAP kinase-kinases; inhibitors have been identified by many paths, including high throughput screening.3 One inhibitor of LF has been shown to be an effective adjunct to antibiotic therapy in animal studies.4 This inhibitor does not affect the activity of EF, which is an adenylyl cyclase with sequence similarity to that produced by Bordetella pertussis (the causative agent of whooping cough).5, 6, 7 These ‘adenylyl cyclase’ toxins8, 9 catalyze the production of cAMP from ATP.10, 11, 12, 13 High levels of cAMP perturb the water homeostasis of the cell leading to abnormalities in the intracellular signaling pathways and stimulation of the chloride channel.14, 15, 16 This contributes to edema (and widening) of the mediastinum located between the lobes of the lungs of patients with inhalation anthrax. Patients with cutaneous anthrax often display tissue edema near the lesion. Inhibitors that would bind to EF and prevent its enzymatic activity could reduce the severity of infections by B. anthracis and other bacteria that produce similar toxins.
The active site residues of anthrax EF have been identified by several crystal structures of the toxin alone or complexed with substrate analogues and small molecule inhibitors.8, 9, 17, 18, 19 Since the active site of the mammalian AC is distinct from that of the toxin, we sought to design inhibitors that bind specifically to anthrax EF. Previous authors have identified nucleotide-like inhibitors of adenylyl cyclases, starting from ATP20, 21, 22, 23 or by molecular docking of large libraries.24 Our approach was to identify discrete fragments with tight binding to the active site, and assemble these into a flexible 3D-pharmacophore that could be used to screen databases of known compounds for those that would fit the active site.
Fragment-based drug design is an emerging lead discovery approach to construct highly potent inhibitors. There are many variations of this approach for molecular drug design25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, all of which begin by determining the binding energy of compounds of low molecular complexity, to identify those with the highest ‘ligand efficiency’ (ΔG of binding per heavy atom28, 29, 33). Both experimental and computational approaches can be taken to screen fragment libraries. For the former, biophysical methods such as X-ray crystallography26, NMR spectroscopy25, 27, 30, and surface plasmon resonance38 have been used to design and synthesize high-affinity ligands, based on fragments with good binding properties.25, 31, 32, 35, 36, 37 Some compounds identified using fragment-based approaches have entered clinical trials36, and fragment-based discovery can identify quality leads for targets where high throughput screening has not succeeded.31, 32, 39
Computational methods40, 41, 42, such as computational solvent mapping (CS-Map)40, 42, have also been developed to enhance ligand efficiency of the starting fragments, by identifying hot spots, or regions of protein binding sites that are major contributors to the binding energy in silico. Our approach was based, in the same fashion, on identifying fragments with high binding energy to discrete areas of the EF active site (Fig. 1), as determined by their Hydropathic INTeractions, or HINT, program43, 44, 45 scores. The fragments were then converted to molecular frameworks (3D-pharmacophores), using distance constraints based on inter-fragment distances in the active site. Instead of relying on synthesis in the early stages of the project, we used these pharmacophores to screen large compound libraries for small molecules with the desired arrangement of fragments. In initial tests, compounds were selected from the NCI database, and screened for those which have better docking scores than known inhibitors. We then went on to identify compounds with even better docking scores in the larger ZINC database.46 From an initial list of about 10,000 compounds that matched the pharmacophores, AutoDock scores were used to select 19 compounds that were assayed for their ability to inhibit the EF-induced secretion of cAMP from mammalian cells. Three of these compounds inhibited cAMP production in the range of 2–8 μM, and were thus promising lead compounds for combinatorial design. This selection was related to our ability to account for the metal ion charge during the docking, as has been described separately47, and to identify tight binding fragments with the HINT program.
Section snippets
Overall procedure
The basic steps in our procedure can be summarized:
Pharmacophore development → UNITY search/2D searches of the NCI and ZINC libraries → Docking → MW/logP filter → 19 compounds for screening → obtained 3 compounds that were active in the cell-based assay for further testing.
A pictorial overview is shown in Figure 1. We began searching in the smaller NCI library, which contains many drug-like molecules, and then expanded our search to the ZINC database.
Pharmacophore design
A fragment library (Fig. 2) search and docking were
Discussion
There are several ways to begin screening for compounds in libraries that could be inhibitors of a given protein. The most common begins with the known substrate, or another lead compound identified experimentally. The major problem with these approaches is that they are inherently limiting in the compound space that can be explored. Here, rather than relying on the ubiquitous reaction substrate, ATP, as our pharmacophore for in silico compound selection, we directly interrogated the active
Conclusions
The fragment-based 3D-pharmacophore and in silico screening enabled us to identify novel inhibitors of EF from compound databases, using a reasonable amount of CPU. As the small list of compounds for assay yielded several candidates with significant inhibitory activity, laboratory assays were kept to a minimum (an important consideration when dealing with assays that involve toxins and expensive reagents). The major advantage of the flexible, fragment based pharmacophore design is that it did
Protein Data Bank structures
Structure of anthrax EF. The Protein Data Bank (PDB) structure, 1K908 (resolution 2.75 Å, r-value 0.225) was used. Here, anthrax EF, with the PA binding domain removed is complexed with calmodulin and a non-cyclizable nucleotide analogue, 3’-deoxy-ATP (3’dATP). One Yb3+ ion in the active site coordinates carboxyl groups of residues Asp491, Asp493, and His577 (Yb-N: 2.78 Å) and an oxygen atom of the α-phosphate group of the 3′-dATP ligand (Fig. 1a). For all the dockings using 1K90, Yb3+ was
Acknowledgments
Funding for this project was provided by Grants from the NIH (5UO1-AI053858-03), the US Army (DAMD17-02-1-0699), and MISSION PHARMACAL COMPANY, San Antonio, TX.
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Present address: Computational Biosciences Department, Sandia National Laboratories, PO Box 5800, MS-1413, Albuquerque, NM 87185-1413, USA.