A second fatty acid amide hydrolase with variable distribution among placental mammals.

Fatty acid amides constitute a large and diverse class of lipid transmitters that includes the endogenous cannabinoid anandamide and the sleep-inducing substance oleamide. The magnitude and duration of fatty acid amide signaling are controlled by enzymatic hydrolysis in vivo. Fatty acid amide hydrolase (FAAH) activity in mammals has been primarily attributed to a single integral membrane enzyme of the amidase signature (AS) family. Here, we report the functional proteomic discovery of a second membrane-associated AS enzyme in humans that displays FAAH activity. The gene that encodes this second FAAH enzyme was found in multiple primate genomes, marsupials, and more distantly related vertebrates, but, remarkably, not in a number of lower placental mammals, including mouse and rat. The two human FAAH enzymes, which share 20% sequence identity and are referred to hereafter as FAAH-1 and FAAH-2, hydrolyzed primary fatty acid amide substrates (e.g. oleamide) at equivalent rates, whereas FAAH-1 exhibited much greater activity with N-acyl ethanolamines (e.g. anandamide) and N-acyl taurines. Both enzymes were sensitive to the principal classes of FAAH inhibitors synthesized to date, including O-aryl carbamates and alpha-keto heterocycles. These data coupled with the overlapping, but distinct tissue distributions of FAAH-1 and FAAH-2 suggest that these proteins may collaborate to control fatty acid amide catabolism in primates. The apparent loss of the FAAH-2 gene in some lower mammals should be taken into consideration when extrapolating genetic or pharmacological findings on the fatty acid amide signaling system across species.

A streamlined platform for high-content functional proteomics of primary human specimens.

Achieving information content of satisfactory breadth and depth remains a formidable challenge for proteomics. This problem is particularly relevant to the study of primary human specimens, such as tumor biopsies, which are heterogeneous and of finite quantity. Here we present a functional proteomics strategy that unites the activity-based protein profiling and multidimensional protein identification technologies (ABPP-MudPIT) for the streamlined analysis of human samples. This convergent platform involves a rapid initial phase, in which enzyme activity signatures are generated for functional classification of samples, followed by in-depth analysis of representative members from each class. Using this two-tiered approach, we identified more than 50 enzyme activities in human breast tumors, nearly a third of which represent previously uncharacterized proteins. Comparison with cDNA microarrays revealed enzymes whose activity, but not mRNA expression, depicted tumor class, underscoring the power of ABPP-MudPIT for the discovery of new markers of human disease that may evade detection by other molecular profiling methods.

Soft docking and multiple receptor conformations in virtual screening.

Protein conformational change is an important consideration in ligand-docking screens, but it is difficult to predict. A simple way to account for protein flexibility is to soften the criterion for steric fit between ligand and receptor. A more comprehensive but more expensive method would be to sample multiple receptor conformations explicitly. Here, these two approaches are compared. A "soft" scoring function was created by attenuating the repulsive term in the Lennard-Jones potential, allowing for a closer approach between ligand and protein. The standard, "hard" Lennard-Jones potential was used for docking to multiple receptor conformations. The Available Chemicals Directory (ACD) was screened against two cavity sites in the T4 lysozyme. These sites undergo small but significant conformational changes on ligand binding, making them good systems for soft docking. The ACD was also screened against the drug target aldose reductase, which can undergo large conformational changes on ligand binding. We evaluated the ability of the scoring functions to identify known ligands from among the over 200 000 decoy molecules in the database. The soft potential was always better at identifying known ligands than the hard scoring function when only a single receptor conformation was used. Conversely, the soft function was worse at identifying known leads than the hard function when multiple receptor conformations were used. This was true even for the cavity sites and was especially true for aldose reductase. To test the multiple-conformation method predictively, we screened the ACD for molecules that preferentially docked to the expanded conformation of aldose reductase, known to bind larger ligands. Six novel molecules that ranked among the top 0.66% of hits from the multiple-conformation calculation, but ranked relatively poorly in the soft docking calculation, were tested experimentally for enzyme inhibition. Four of these six inhibited the enzyme, the best with an IC(50) of 8 microM. Although ligands can get better scores in soft docking, the same is also true for decoys. The improved ranking of such decoys can come at the expense of true ligands.

Testing a flexible-receptor docking algorithm in a model binding site.

Sampling receptor flexibility is challenging for database docking. We consider a method that treats multiple flexible regions of the binding site independently, recombining them to generate different discrete conformations. This algorithm scales linearly rather than exponentially with the receptor's degrees of freedom. The method was first evaluated for its ability to identify known ligands of a hydrophobic cavity mutant of T4 lysozyme (L99A). Some 200000 molecules of the Available Chemical Directory (ACD) were docked against an ensemble of cavity conformations. Surprisingly, the enrichment of known ligands from among a much larger number of decoys in the ACD was worse than simply docking to the apo conformation alone. Large decoys, accommodated in the larger cavity conformations sampled in the ensemble, were ranked better than known small ligands. The calculation was redone with an energy correction term that considered the cost of forming the larger cavity conformations. Enrichment improved, as did the balance between high-ranking large and small ligands. In a second retrospective test, the ACD was docked against a conformational ensemble of thymidylate synthase. Compared to docking against individual enzyme conformations, the flexible receptor docking approach improved enrichment of known ligands. Including a receptor conformational energy weighting term improved enrichment further. To test the method prospectively, the ACD database was docked against another cavity mutant of lysozyme (L99A/M102Q). A total of 18 new compounds predicted to bind this polar cavity and to change its conformation were tested experimentally; 14 were found to bind. The bound structures for seven ligands were determined by X-ray crystallography. The predicted geometries of these ligands all corresponded to the observed geometries to within 0.7A RMSD or better. Significant conformational changes of the cavity were observed in all seven complexes. In five structures, part of the observed accommodations were correctly predicted; in two structures, the receptor conformational changes were unanticipated and thus never sampled. These results suggest that although sampling receptor flexibility can lead to novel ligands that would have been missed when docking a rigid structure, it is also important to consider receptor conformational energy.

Structure-based inhibitor discovery against adenylyl cyclase toxins from pathogenic bacteria that cause anthrax and whooping cough.

Edema factor (EF) and CyaA are adenylyl cyclase toxins secreted by pathogenic bacteria that cause anthrax and whooping cough, respectively. Using the structure of the catalytic site of EF, we screened a data base of commercially available, small molecular weight chemicals for those that could specifically inhibit adenylyl cyclase activity of EF. From 24 compounds tested, we have identified one quinazoline compound, ethyl 5-aminopyrazolo[1,5-a]quinazoline-3-carboxylate, that specifically inhibits adenylyl cyclase activity of EF and CyaA with approximately 20 microm Ki. This compound neither affects the activity of host resident adenylyl cyclases type I, II, and V nor exhibits promiscuous inhibition. The compound is a competitive inhibitor, consistent with the prediction that it binds to the adenine portion of the ATP binding site on EF. EF is activated by the host calcium sensor, calmodulin. Surface plasmon resonance spectroscopic analysis shows that this compound does not affect the binding of calmodulin to EF. This compound is dissimilar from a previously described, non-nucleoside inhibitor of host adenylyl cyclase. It may serve as a lead to design antitoxins to address the role of adenylyl cyclase toxins in bacterial pathogenesis and to fight against anthrax and whooping cough.

A model binding site for testing scoring functions in molecular docking.

Prediction of interaction energies between ligands and their receptors remains a major challenge for structure-based inhibitor discovery. Much effort has been devoted to developing scoring schemes that can successfully rank the affinities of a diverse set of possible ligands to a binding site for which the structure is known. To test these scoring functions, well-characterized experimental systems can be very useful. Here, mutation-created binding sites in T4 lysozyme were used to investigate how the quality of atomic charges and solvation energies affects molecular docking. Atomic charges and solvation energies were calculated for 172,118 molecules in the Available Chemicals Directory using a semi-empirical quantum mechanical approach by the program AMSOL. The database was first screened against the apolar cavity site created by the mutation Leu99Ala (L99A). Compared to the electronegativity-based charges that are widely used, the new charges and desolvation energies improved ranking of known apolar ligands, and better distinguished them from more polar isosteres that are not observed to bind. To investigate whether the new charges had predictive value, the non-polar residue Met102, which forms part of the binding site, was changed to the polar residue glutamine. The structure of the resulting Leu99Ala and Met102Gln double mutant of T4 lysozyme (L99A/M102Q) was determined and the docking calculation was repeated for the new site. Seven representative polar molecules that preferentially docked to the polar versus the apolar binding site were tested experimentally. All seven bind to the polar cavity (L99A/M102Q) but do not detectably bind to the apolar cavity (L99A). Five ligand-bound structures of L99A/M102Q were determined by X-ray crystallography. Docking predictions corresponded to the crystallographic results to within 0.4A RMSD. Improved treatment of partial atomic charges and desolvation energies in database docking appears feasible and leads to better distinction of true ligands. Simple model binding sites, such as L99A and its more polar variants, may find broad use in the development and testing of docking algorithms.