Peripheral but crucial: A hydrophobic pocket (Tyr706, Leu337, and Met336) for potent and selective inhibition of neuronal nitric oxide synthase (original) (raw)
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Bioorganic & Medicinal Chemistry, 2013
In certain neurodegenerative diseases damaging levels of nitric oxide (NO) are produced by neuronal nitric oxide synthase (nNOS). It, therefore, is important to develop inhibitors selective for nNOS that do not interfere with other NOS isoforms, especially endothelial NOS (eNOS), which is critical for proper functioning of the cardiovascular system. While we have been successful in developing potent and isoform-selective inhibitors, such as lead compounds 1 and 2, the ease of synthesis and bioavailability have been problematic. Here we describe a new series of compounds including crystal structures of NOS-inhibitor complexes that integrate the advantages of easy synthesis and good biological properties compared to the lead compounds. These results provide the basis for additional structure-activity relationship (SAR) studies to guide further improvement of isozyme selective inhibitors.
Structural Basis for Isoform-Selective Inhibition in Nitric Oxide Synthase
Accounts of Chemical Research, 2013
Nitric oxide synthase (NOS) converts L-arginine into L-citrulline and releases the important signaling molecule nitric oxide (NO). In the cardiovascular system NO produced by endothelial NOS (eNOS) relaxes smooth muscle which controls vascular tone and blood pressure.Neuronal NOS (nNOS) produces NO in the brain, where it influences a variety of neural functions such as neural transmitter release. NO can also support immune system, serving as a cytotoxic agent during infections. Even with all of these important functions, NO is a free radical, and, when overproduced, it can cause tissue damage. This mechanism can operate in many neurodegenerative diseases, and as a result, the development of drugs targeting nNOS is a desirable therapeutic goal. However, the active sites of all 3 human isoforms are very similar, and designing inhibitors specific for nNOS is a challenging problem. It is critically important, for example, not to inhibit eNOS owing to its central role in controlling blood pressure. In this Account we summarize our efforts in collaboration with Rick Silverman at Northwestern University to develop drug candidates that specifically target NOS using crystallography, computational chemistry, and organic synthesis. As a result we have developed aminopyridine compounds that are 3,800 fold more selective for nNOS than eNOS, some of which show excellent neuro-protective effects in animal models. Our group has solved approximately 130 NOS-inhibitor crystal structures which have provided the structural basis for our design efforts. Initial crystal structures of nNOS and eNOS bound to selective dipeptide inhibitors showed that a single amino acid difference (Asp in nNOS and Asn in eNOS) results in much tighter binding to nNOS. The NOS active site is open and rigid, which produces few large structural changes when inhibitors bind. However, we have found that relatively small changes in the active site and inhibitor chirality can account for large differences in isoform-selectivity. For example, we expected that the aminopyridine group on our inhibitors would form a hydrogen bond with a conserved Glu inside the NOS active site. Instead, in one group of inhibitors, the aminopyridine group extends outside of the active site where it interacts with a heme propionate. For this orientation to occur, a conserved Tyr side chain must swing out of the way.This unanticipated observation taught us about the importance of inhibitor chirality and active site dynamics. We also successfully used computational methods to gain insights into the contribution of the state of protonation of the inhibitors to their selectivity. Employing the lessons learned from the aminopyridine inhibitors, the Silverman lab designed and synthesized symmetric double-headed
Proceedings of the National Academy of Sciences, 2004
The high level of amino acid conservation and structural similarity of the substrate-binding sites of the oxygenase domains of the nitric oxide synthase (NOS) isoforms (eNOSoxy, iNOSoxy, nNOSoxy) make the interpretation of the structural basis of inhibitor isoform specificity a challenge, and provide few clues for the design of new selective compounds. Crystal structures of iNOSoxy and nNOSoxy complexed with the neuronal NOS-specific inhibitor AR-R17447 suggest that specificity is provided by the interaction of the chlorophenyl group with an isoform-unique substrate access channel residue (L337 in rat neuronal NOS, N115 in mouse inducible NOS). This is confirmed by biochemical analysis of site-directed mutants. Inhibitors combining guanidinium-like structural motifs with long chains specifically targeting this residue are good candidates for rational isoform-specific drug design. Based on this finding, modifications of AR-R17447 to improve the specificity for the human isoforms are suggested.
Journal of the American Chemical Society, 2012
The reduction of pathophysiologic levels of nitric oxide through inhibition of neuronal nitric oxide synthase (nNOS) has the potential to be therapeutically beneficial in various neurodegenerative diseases. We have developed a series of pyrrolidine-based nNOS inhibitors that exhibit excellent potencies and isoform selectivities (J. Am. Chem. Soc. 2010, 132, 5437). However, there are still important challenges, such as how to decrease the multiple positive charges derived from basic amino groups, which contribute to poor bioavailability, without losing potency and/or selectivity. Here we present an interdisciplinary study combining molecular docking, crystallography, molecular dynamics simulations, synthesis, and enzymology to explore potential pharmacophoric features of nNOS inhibitors and to design potent and selective monocationic nNOS inhibitors. The simulation results indicate that different hydrogen bond patterns, electrostatic interactions, hydrophobic interactions, and a water molecule bridge are key factors for stabilizing ligands and controlling ligand orientation. We find that a heteroatom in the aromatic head or linker chain of the ligand provides additional stability and blocks the substrate binding pocket. Finally, the computational insights are experimentally validated with double-headed pyridine analogs. The compounds reported here are among the most potent and selective monocationic pyrrolidine-based nNOS inhibitors reported to date, and 10 shows improved membrane permeability.
Journal of the American Chemical Society, 2008
Experimental Section Computer Modeling Protein Structures The crystallographic coordinates for NOS from the Research Collaboratory for Structural Bioinformatics (RCSB) protein database are as follows: rat nNOS 1 :1p6h (1.98 Å resolution, R cryst = 0.231); 1p6i (1.90 Å resolution, R cryst = 0.228); 1p6j (2.00 Å resolution, R cryst = 0.225); 1qw6 (2.1 Å resolution, R cryst = 0.20), human eNOS 2 : 3nos (2.4 Å resolution, R cryst = 0.193), bovine eNOS 1 : 1p6l (2.35 Å resolution, R cryst = 0.214); 1p6m (2.27 Å resolution, R cryst = 0.215); 1p6n (2.5 Å resolution, R cryst = 0.219), human iNOS: 3 1nsi (2.55 Å resolution, R cryst = 0.209), murine iNOS 4 : 1qw4 (2.3 Å resolution, R cryst = 0.213). The amino acid sequences of NOS were retrieved from the PIR protein sequence database. The sequences are human nNOS (entry P29475), rat nNOS (entry P29476), human eNOS (entry P29474), bovine eNOS (entry P29473), human iNOS (entry P35228), and murine iNOS (entry P29477). All of the computational work was performed on Silicon Graphics Octane 2 Workstations with an IRIX 6.5 operating system. The molecular modeling was achieved with commercially available InsightII 2000 5 and SYBYL 6.8 6 software packages. The NOS model was prepared by first adding H-atoms using the Accerlyrs/InsightII 2000 software, and the protonation states of the residues were set to pH 7.0. The cvff force field of the Discover 98.0 program within Insight II was used to optimize the orientation of hydrogen atoms of the protein and of structural waters. The ligands and solvent molecules of the protein structures were removed, but the heme and H 4 B were retained near the active site. The size and spatial orientation of the active site was analyzed by the Binding Site S2 Analysis module within Insight II. The grid size for searching the proteins was set to 1 Å ×1 Å ×1 Å. All of the solvent-accessible surfaces in the proteins were filled with grid points, and only those having at least 125 grid points were accepted as possible ligand binding sites. GRID Calculations The calculations were performed with version 22 of the GRID software. 7 Hydrogens were added with the program GRIN. The GRID box dimensions were chosen to encompass all of the active site residues shown in Figure 1. This results in a box size of 31 × 28 × 31 Å. The grid spacings were set to 1 Å (directive NPLA = 1) and 0.5 Å (directive NPLA = 2), respectively. The amino acids in the active site were considered rigid (directive move = 0). The directives NETA and ALMD were set to 120 and 1, respectively, to include the atoms of heme and H 4 B in calculations and to interpret which atom(s) in the active site contribute(s) to the interaction with a specific probe atom. The following single atom probes were used in the calculation: DRY, C3, NM3, N1+, N3+, N1, NH=, O, O1, and the multi-atom probes COO-, Amidine, and ARamidine. MCSS Calculations The functional groups chosen for the MCSS calculations were benzene (all hydrogen model), cyclohexane, isobutene, N-methylacetamide, methanol, ether, acetate ion, methylammonium, trimethylamine cation, and pyrrolidine cation. The binding site area in the MCSS simulation was defined as an approximately 27 Å × 26 Å × 31 Å box, which was centered around the grid points searched by InsightII/Binding Site Analysis. Replicas of a given functional group were randomly distributed inside the binding site and then simultaneously and independently energy minimized. Pairs of molecules were considered to be identical if the root-mean-square deviation (RMSD) between them was less than 0.2 Å, and in such cases one of the pairs was eliminated. The above protocol was repeated 10 times for each of the functional groups to allow complete searching of the active site. The minima with the binding energy lower than 0 kcal/mol were retrieved in the analysis. All of the above calculations were performed using the CHARMM 22 force field and MCSS 2.1 program. 8 LUDI Ligand Design The constructed targeted fragment libraries were converted into a LUDI user library. To determine the appropriate position and orientation of the fragments from the LUDI user library in the active site of NOS, LUDI was first applied to generate the interaction sites for each pharmacophore. Four different types of the interaction sites are defined in the LUDI program: lipophilic-aliphatic, lipophilic-aromatic, hydrogen donor, and hydrogen acceptor. The residues inside an 8.0 Å radius sphere, which centered on the centroid of the minimal pharmacophoric elements, were used to generate the interaction sites. The link library switch was turned off, and the target mode switch was turned on. The LUDI scoring function was set to Energy-estimate-2. 9 Other settings were kept with the standard default parameters. To convert the above determined fragments into a molecule, the side chain library in Supporting Information Figure 5 was converted into a LUDI link library and was used further in the connection operation. The hydrogen atoms in the above fragment structure were replaced by a link fragment to create a new substructure. The switch for the target mode was turned off, but the switch for the link library was turned on. The linkage parameter can be set to 1 (the link fragment fit at least one link site), 2 (the link fragment simultaneously fit at least two link sites), or be specified (the link site was S3 specifically assigned) according to the actual requirements. The other settings are the standard default parameters. AutoDock Analysis AutoDock 3.0 was employed to perform the docking calculations, as reported in our previous paper. 10 The ligands and solvent molecules of the protein structures were removed, but the cofactors heme and H 4 B were retained near the active site. For each protein structure, polar hydrogen atoms were added, and Kollman united atom charges were assigned. 11 Hydrogens were also added to the heme and H 4 B, and charges were calculated by the Gasteiger-Marsili method. 12 The charge of the Fe atom bound to heme was assigned +3. The nonpolar hydrogen atoms of heme and H 4 B were removed manually and their charges were united with the bonded carbon atoms. Atomic solvation parameters and fragmental volumes were assigned using the AddSol utility. The 3D structures of the ligands were built using SYBYL 6.8. Partial atomic charges were also calculated using the Gasteiger-Marsili method. The rotatable bonds in the ligands were defined using another AutoDock 3.0 auxiliary program, AutoTors, which also unites the nonpolar hydrogens and partial atomic charges to the bonded carbon atoms. The grid maps were calculated using AutoGrid. The dimensions of the grid box was 27 × 26 × 31 Å and the grid spacing was set to 0.375 Å. Docking was performed using the Lamarckian genetic algorithm (LGA), and the pseudo-Solis and Wets method were applied for the local search. Each docking experiment was performed 100 times, yielding 100 docked conformations. Parameters for the docking experiments were as follows: initial population size of 200; random starting position and conformation; maximal mutation of 0.2 Å in translation and 5º in orientation and rotation; elitism of 5; mutation rate of 0.02 and crossover rate of 0.8; local search rate of 0.06 and maximal iteration per local search of 300. Simulations were performed with a maximum of 1.5 × 10 6 energy evaluations and a maximum of 27,000 generations. Other settings were the standard default parameters. All of the ligands followed the same docking protocol. The results of the docking experiments were evaluated by calculating the positional root-mean-square deviation (RMSD) of the corresponding atoms of each conformation 13 and/or by a visual comparison to determine if the orientation of the inhibitor matches the pharmacophores determined. Chemical Synthesis General Methods, Reagents and Materials All reagents were purchased from Aldrich, Acros Organics, and Fisher Scientific and were used without further purification unless stated otherwise. NADPH, calmodulin, and human ferrous hemoglobin were obtained from Sigma Chemical Co. Tetrahydrobiopterin (H 4 B) was purchased from Alexis Biochemicals. 1 H NMR and 13 C NMR spectra were recorded on a Varian Mercury 400 MHz or a Varian Inova 500 MHz spectrometer (100.6, or 125.7 MHz, for 13 C NMR spectra, respectively) in CDCl 3 , DMSO-d 6 , CD 3 OD or D 2 O. Chemical shifts are reported as values in parts per million and the reference resonance peaks set at 0 ppm [TMS(CDCl 3)], 2.50 ppm [(CD 2 H) 2 SO], 3.31 ppm (CD 2 HOD), and 4.80 ppm (HOD) respectively for 1 H NMR and 77.23 ppm (CDCl 3), 39.52 ppm (DMSO-d 6) and 49.00 ppm (CD 3 OD) for 13 C NMR spectra. An Orion research model 701H pH meter with a general combination electrode was used for pH measurements. Mass spectra were performed on a Micromass Quattro II triple quadrupole HPLC/MS mass spectrometer with an electrospray ionization (ESI) source or atmospheric pressure chemical ionization (APCI) source. High-resolution mass spectra were carried out
International journal of molecular sciences, 2014
Neuronal nitric oxide synthase (nNOS) plays an important role in neurotransmission and smooth muscle relaxation. Selective inhibition of nNOS over its other isozymes is highly desirable for the treatment of neurodegenerative diseases to avoid undesirable effects. In this study, we present a workflow for the identification and prioritization of compounds as potentially selective human nNOS inhibitors. Three-dimensional pharmacophore models were constructed based on a set of known nNOS inhibitors. The pharmacophore models were evaluated by Pareto surface and CoMFA (Comparative Molecular Field Analysis) analyses. The best pharmacophore model, which included 7 pharmacophore features, was used as a search query in the SPECS database (SPECS®, Delft, The Netherlands). The hit compounds were further filtered by scoring and docking. Ten hits were identified as potential selective nNOS inhibitors.
JOURNAL OF PHARMACEUTICAL CHEMISTRY, 2015
Nitric oxide, a gaseous free radical molecule (NO) behaves, as a secondary messenger in various tissues. It is responsible for different physiological functions and pathological symptoms. Mammals contain three different nitric oxide synthase (NOS) isoforms: neuronal NOS (nNOS: in the brain, in peripheral nervous system and muscle tissues), inducible NOS (iNOS: in macrophage cells), endothelial NOS (eNOS: in endothelial cells). Under certain pathological conditions and/or after certain ages excessive NO produced in brain causes tissue damage and oxidative stress. It also reacts with other free radicals to create specific molecular modifications. The excessive production of NO, especially by nNOS (in brain) is implicated in various disease states such as neurodegeneration, stroke, migraine and Parkinsons, Alzheimers, and Huntingtons diseases. The active sites of three NOS isoforms show great similarity; therefore, designing of selective nNOS inhibitors is not an easy task. The computa...
Journal of Medicinal Chemistry, 2009
New nitric oxide synthase (NOS) inhibitors were designed de novo with knowledge gathered from the studies on the nNOS-selective dipeptide inhibitors. Each of the new inhibitors consists of three fragments: an aminopyridine ring, a pyrrolidine, and a tail of various length and polarity. The in vitro inhibitory assays indicate good potency and isoform selectivity for some of the compounds. Crystal structures of these inhibitors bound to either wild type or mutant nNOS and eNOS have confirmed design expectations. The aminopyridine ring mimics the guanidinium group of Larginine and functions as an anchor to place the compound in the NOS active site where it hydrogen bonds to a conserved Glu. The rigidity of the pyrrolidine ring places the pyrrolidine ring nitrogen between the same conserved Glu and the selective residue nNOS Asp597/eNOS Asn368 which results in similar interactions observed with the α-amino group of dipeptide inhibitors bound to nNOS. These structures provide additional information to help in the design of inhibitors with greater potency, physico-chemical properties, and isoform selectivity.
Potent and selective neuronal nitric oxide synthase inhibitors with improved cellular permeability
Bioorganic & Medicinal Chemistry Letters, 2010
Recently, a series of potent and selective neuronal nitric oxide synthase inhibitors containing two basic nitrogen atoms was reported (Ji, H.; Stanton, B. Z.; Igarashi, J.;, Li, H.; Martásek, P.; Roman, L. J.; Poulos, T. L.; Silverman, R. B. J. Am. Chem. Soc. 2008, 130(12), 3900-3914). In an effort to improve their bioavailability, three compounds (2a-c) were designed with electron-withdrawing groups near one of the basic nitrogen atoms to lower its pK a . Inhibition studies with these compounds showed that two of them not only retained most of the potency and selectivity of the best analogue of the earlier series, but also showed improved membrane permeability based on data from a cellbased assay.
A new class of selective and potent inhibitors of neuronal nitric oxide synthase
Bioorganic & Medicinal Chemistry Letters, 1999
The synthesis and SAR of a series of 6-(4-(substituted)phenyl)-2-aminopyridines as inhibitors of nitric oxide synthase are described. Compound 3a from this series shows potent and selective inhibition of the human nNOS isoform, with pharmacokinetics sufficient to provide in vivo inhibition of nNOS activity.