Common angiotensin receptor blockers may directly modulate the immune system via VDR, PPAR and CCR2b
© Marshall et al; licensee BioMed Central Ltd. 2006
Received: 07 December 2005
Accepted: 10 January 2006
Published: 10 January 2006
There have been indications that common Angiotensin Receptor Blockers (ARBs) may be exerting anti-inflammatory actions by directly modulating the immune system. We decided to use molecular modelling to rapidly assess which of the potential targets might justify the expense of detailed laboratory validation. We first studied the VDR nuclear receptor, which is activated by the secosteroid hormone 1,25-dihydroxyvitamin-D. This receptor mediates the expression of regulators as ubiquitous as GnRH (Gonadatrophin hormone releasing hormone) and the Parathyroid Hormone (PTH). Additionally we examined Peroxisome Proliferator-Activated Receptor Gamma (PPARgamma), which affects the function of phagocytic cells, and the C-CChemokine Receptor, type 2b, (CCR2b), which recruits monocytes to the site of inflammatory immune challenge.
Telmisartan was predicted to strongly antagonize (Ki≈0.04nmol) the VDR. The ARBs Olmesartan, Irbesartan and Valsartan (Ki≈10 nmol) are likely to be useful VDR antagonists at typical in-vivo concentrations. Candesartan (Ki≈30 nmol) and Losartan (Ki≈70 nmol) may also usefully inhibit the VDR. Telmisartan is a strong modulator of PPARgamma (Ki≈0.3 nmol), while Losartan (Ki≈3 nmol), Irbesartan (Ki≈6 nmol), Olmesartan and Valsartan (Ki≈12 nmol) also seem likely to have significant PPAR modulatory activity. Olmesartan andIrbesartan (Ki≈9 nmol) additionally act as antagonists of a theoretical modelof CCR2b. Initial validation of this CCR2b model was performed, and a proposed model for the AngiotensinII Type1 receptor (AT2R1) has been presented.
Molecular modeling has proven valuable to generate testable hypotheses concerning receptor/ligand binding and is an important tool in drug design. ARBs were designed to act as antagonists for AT2R1, and it was not surprising to discover their affinity for the structurally similar CCR2b. However, this study also found evidence that ARBs modulate the activation of two key nuclear receptors-VDR and PPARgamma. If our simulations are confirmed by experiment, it is possible that ARBs may become useful as potent anti-inflammatory agents, in addition to their current indication as cardiovascular drugs.
Why would ARBs have dose-dependent efficacy?
Angiotensin Receptor Blockers (ARBs) act as antagonists of the AngiotensinII Type1 receptor (AT2R1) [Swiss-Prot:P30556], and were designed to treat moderate hypertension. Although ARBs have been marketed for nearly a decade, their mode of action is not fully understood, and debate still rages whether Angiotensin Converting Enzyme Inhibitors (ACEI) or ARBs are superior at reducing ultimate mortality due to cardiovascular dysfunction.
An editorial in the New England Journal of Medicine concluded :
"in two recently reported clinical trials in which the investigators were allowed to increase the dose of Losartan gradually to 100 mg per day, there was a significant reduction in the incidence of heart failure among high-risk patients; this finding raises the important question of whether higher doses of Losartan might have been more effective in reducing the rates of cardiovascular events"
Yet in-vitro studies  have shown that the ARBs produce an efficient and total blockade of the Angiotensin II Type 1 receptor (AT2R1) at doses much lower than this editorial was contemplating. There should be no dose related effects once a total receptor blockade is place, so the obvious question arises "how can an ARB have dose-dependent efficacy?"
It is accepted that diabetic nephropathy is beneficially affected by ARBs [3–6], yet again the mechanisms, and optimal dosage, remain elusive. A study using Irbesartan noted dosage-dependant efficacy, with significantly greater protection at 300 mg/day versus 150 mg/day .
Schieffer, et.al. , found that ARBs appeared to exert stronger systemic anti-inflammatory and anti-aggregatory effects compared with ACEIs in Atherosclerosis. Luno, et.al. , recently reviewed studies which have shown that ACE Inhibitors (ACEI) did not always lead to the same clinical outcome as ARBs, especially where the patient was suffering from inflammatory diseases such as diabetes.
The reason for this is not immediately obvious, as ACE's function is to cleave the octapeptide Angiotensin II from Angiotensin I. The AngiotensinII then binds to AT2R1 receptors on the activated phagocytes, an action inhibited by the ARBs. Interrupting either pathway, with either ACEI or ARBs, should have the same effect – the activated phagocytes will be denied Angiotensin II bound at their receptors.
Waterhouse, et.al. , and Marshall, et.al. , noted that patients with autoimmune disease were anecdotally reporting that ARBs prescribed for hypertension caused a noticeable change in their perceived immune disease symptoms, a change not easily explained in terms of hypertension, or hypotension, alone. We consequently decided to investigate whether molecular modelling could help define precise mechanism(s) of action of the ARBs upon inflammatory disease. Do they perhaps act as antagonists for receptors other than AT2R1? Immune system receptors, for example?
Identifying target nuclear and transmembrane receptors
1. The VDR
The T-helper Type 1 (Th1) immune response is usually defined as one which generates significant quantities of the cytokine Interferon-gamma . Many chronic diseases are associated with Th1 inflammation , including atherosclerosis , diabetes , and perhaps even asthma .
Generation of Interferon-gamma in a Th1 activated macrophage catalyzes its mitochondrial production of the secosteroid hormone 1,25-dihydroxyvitamin-D (1,25-D) by as much as 30-fold . 1,25-D is the active secosteroid of the Vitamin-D metabolism . This steroid's presence is often ignored by clinical medicine, since it circulates in low concentrations (typically 75 picomoles/Litre, 29 pg/ml), which are very difficult to measure. Yet 1,25-D and its receptor, the Vitamin-D Receptor (VDR) [Swiss-Prot:P11473], are expressed in over 30 target tissues, and their expression is tightly coupled with regulators as ubiquitous as GnRH (Gonadatrophin hormone releasing hormone) , and the Parathyroid Hormone(PTH) .
Ripple-down effects of VDR activation include changes not only to the androgens and thyroid hormones, but also to ACTH, Insulin Receptors, P450C1, and many other biologically important metabolites [18, 46].
In patients with severe Th1 immune disease, clinical observations [9, 10] indicated that the administration of the ARB Olmesartan, at a concentration in excess of that needed for full AT2R1 antagonism, often causes the level of circulating 1,25-D to drop.
We therefore decided to target the VDR nuclear receptor  for further study.
2. Peroxisome Proliferator Activated Receptors (PPARs)
Benson, et.al. reported  that the ARB 'Telmisartan' seems to act both as an agonist and antagonist of Peroxisome Proliferator Activated Receptor gamma (PPARgamma) [Swiss-Prot:P37231], a nuclear hormone receptor from the same 'NR1' subfamily as VDR. The PPARs act as anti-inflammatory transcription factors . Part of this anti-inflammatory regulation is mediated through negative interference between PPARs and nuclear factors such as NF-kappaB. Ligands of PPAR may affect the inflammatory response in diseases as wide-ranging as Inflammatory Bowel Diseases, Atherosclerosis, Parkinson's Disease and Alzheimer's . Clearly, it is important to know exactly how the ARBs might affect PPARgamma.
3. C-C chemokine receptor type 2 (CCR2b)
Monocyte chemotactic protein-1 (MCP-1) binding to its receptor, CCR2b [EMBL:BC095540], plays an important role in a variety of diseases involving infection, inflammation, and/or injury [23, 24]. CCR2b recruits monocytes to the sites of tissue damage. The monocytes later differentiate to macrophages and/or polymorphonucleated 'giant' cells.
CCR2b belongs to the same family of 7-Transmembrane G-Protein Coupled Receptors (GPCRs)  as does AT2R1, and the similarities between these two GPCRs, together with the clinical observations [9, 10], supported the addition of CCR2b to this study.
Validation of 'AutoDock' simulation software
It was decided to use automated docking of the ligands so as to minimize subjective factors which might arise if the ligands were fitted into the binding pockets manually. The Scripps' package, AutoDock [26–28], was selected for this task. Toprakci, et.al. , recently compared the Ki values estimated by AutoDock for ten inhibitors of human monoamine oxidase-B, with the values of Ki which had been determined by experiment. In every case, there was less than one order of magnitude difference between the experimentally determined Ki, and the value estimated by computer simulation of the ligand-bound enzyme. Chen, et.al. , also concluded that AutoDock provided accurate estimation of ligand-DNA binding parameters.
We were able to compare calculated Ki for some of our docking experiments with published values, and similarly found excellent agreement. For example, we validated our PPARgamma model by docking the ligand GI262570 (Farglitazar), essentially as predicted by the data of Xu, et.al. .
It is important to understand that the 'Lamarckian genetic algorithm' used by AutoDock does not guarantee convergence to an optimal solution. The existence of the 'optimal' solution, amongst any set of docking results, only becomes assured as the number of docking attempts tends to infinity. Considerable computing power was expended in order to maximize the likelihood that this study identified the lowest energy docking configurations. Additionally, the algorithm's convergence parameters were manually adjusted whenever successive docking runs were not returning consistent minima.
ARBs exhibit a strong affinity for VDR ligand binding pocket
In order to maximize reliability, two discrete models were used for the ligand binding pocket of the VDR, extracted from two separate X-ray generated structures. The first model was "The crystal structure of the nuclear receptor for vitamin D bound to its natural ligand"  [PDB:1DB1], while the second was the VDR bound to the agonist TX522  [PDB:v].
Estimated Inhibition Constant, Ki (nmol), for ARBs docking into several immune system receptors.
Irbesartan and Valsartan gave predicted Ki values in the 10–14 nanomolar region, probably indicating significant antagonistic action at concentrations safely achievable in-vivo.
Olmesartan similarly predicted useful Ki values, ranging from 10 to 34 nmol. Particularly interesting is that two distinct conformations were identified.
Losartan docked with a Ki around 70 nanomolar, Candesartan around 30 nanomolar. These are likely also significant antagonists, but higher dosage levels would be necessary.
Hydrogen bonds and hydrophobic contacts during docking with the VDR
A double hydrogen bond was formed from the oxygen of the triol group of 1,25-D, both to the imidazole nitrogen of HIS305, and to the imidazole nitrogen of HIS397. Another hydrogen bond extends from the 1-hydroxyl oxygen to the aminoacetal of ARG274 and the hydroxyl of SER237, and another pair from the ligand's O3 oxygen to SER278 and TYR143.
Valsartan, although it exhibits a potentially useful affinity as a VDR antagonist, failed to form hydrogen bonds with any key residue (Figure 10).
ARBs exhibit an affinity for PPARgamma
We extracted the coordinate data for PPARgamma from [PDB:1FM9], an X-ray structure. As model validation, the PPARgamma agonist GI262570 (Farglitazar) was docked with Ki≈0.04 nmol, close to the (approx.) 0.01 nmol predicted by the inhibition curve in figure 1A of Xu, et.al. .
Table 1 shows that the ARBs exhibited a strong affinity for the ligand binding pocket of PPARgamma, with Ki ranging from 0.29 to 61 nanomoles.
Telmisartan is the strongest modulator of PPARgamma (Ki≈0.3 nmol), while Losartan (Ki≈3 nmol), Olmesartan (Ki≈12 nmol), Irbesartan (Ki≈6 nmol) and Valsartan (Ki≈12 nmol) also seem likely to have significant PPAR modulatory activity. Candesartan (Ki≈ 61 nmol) may also have useful activity at a higher dosage.
ARBs exhibit a strong affinity for CCR2b
The ARBs are designed as antagonists for the Angiotensin II Type 1 Receptor (AT2R1). This is a GPCR  of the "Class A (Rhodopsin-like) 7-transmembrane receptors." CCR2b is another Class A GPCR, with surprising similarity to AT2R1.
Multiple sequence alignment for AT2R1 and Bovine Rhodopsin (PDB:1L9H)
Multiple sequence alignment for CCR2b and Bovine Rhodopsin (PDB:1L9H)
Multiple sequence alignment for AT2R1 and CCR2b
There are no complete X-ray or NMR structures of Homo sapiens' Class A GPCRs in PDB, or any other public database. However, Shi, et.al.  had derived a theoretical model, [PDB:1KP1], which provided a basis for us to study. We tried to improve upon [PDB:1KP1] by using, inter alia, Truncated Newton energy minimization with Ponder's TINKER Tools [38, 39] and homology modelling with Sali's 'Modeller' [40, 41]. However, even extensive homology modelling against the Bovine Rhodopsin X-ray structure [PDB:1L9H], and other theoretical models, such as [PDB:1KPX], failed to improve upon [PDB:1KP1].
We accepted that [PDB:1KP1] was probably a valid model for CCR2b based on the detailed nature of Shi, et.al's studies , our failed attempts to improve upon it, and the manner in which it docked, exactly as predicted, with the CCR2b antagonist, TAK779.
A binding pocket exists between helices seven and one of [PDB:1KP1], extending back to extracellular regions one and three. Baba, et.al.  had measured the inhibitory effects of Tak779 on CCR2b in their laboratory, showing an experimental Ki≈9 nmol. When we docked TAK779 into our putative binding pocket, it predicted a Ki≈10 nmol, essentially identical with this experimental value.
Olmesartan and Irbesartan each showed excellent affinity (Ki≈9 nmol) for this binding pocket, while Valsartan, Telmisartan, Candesartan and Losartan exhibited slightly less (Kifrom 22 to 40 nmol).
The ARBs, and TAK779, not only fill space within this binding pocket, but also 'anchor' the top of helices seven and one to extracellular regions three and one, restraining the motion of GPCR elements, and, most probably, inhibiting its activation .
A putative AT2R1 receptor model
A primary goal set for this study had been the validation of every structure and tool we used. It had therefore been decided to ensure that the ARBs would dock into AT2R1 with inhibition constants close to the values measured in-vitro, as documented in the various FDA New Drug Applications (NDAs). For example, NDA21-286 , indicates a Ki for Olmesartan and Candesartan of approx. 0.1 nanomolar, and for Losartan about 3 times higher.
This validation task proved to be the most difficult of the study. There was no AT2R1 X-ray structure publicly available, nor any comprehensive theoretical model. Additionally, there was very little comparative experimental ARB data available (FDA NDA21-286 is the exception to this). Most authors studied only one commercial ARB product in isolation.
We tried to use the theoretical model published by Martin, et.al.  [PDB:1ZV0] for an activated AT2R1. But no ARB would bind to that receptor configuration, even after the extensive energy optimization required to move helix seven back into its un-activated position.
We then decided to produce an AT2R1 model by comparative homology  with Bovine Rhodopsin [PDB:1L9H], but still could not produce a model which would dock the known ARBs, even after extensive energy minimization. Eventually we used the putative CCR2b, [PDB:1KP1] as the comparative model. Surprisingly, straight out of the 'Modeller' , all the ARBs docked into a pocket on the opposite side of the GPCR from the binding pocket which had been located on CCR2b. The Ki for the ARBs ranged from 0.10 to 1.5 nmol, as detailed in Table 1.
It is interesting to note that although the comparative homology between AT2R1 and Rhodopsin is only 17% (Table 2) the AT2R1 sequence is much closer to that of CCR2b (Table 4). Our failure to produce a usable receptor by comparative homology with Bovine Rhodopsin would seem to caste doubt on its utility as a prototype for the Class A 7-transmembrane GPCR structures.
Models provided to ease visualization of nuclear receptors
It is evident from the lack of clarity in Figure 4 that it is extremely difficult to visualize ligand conformation in the binding pockets of nuclear receptors using two dimensional media. For this reason we have provided, as an attached file, an archive of the receptor configurations used in this study, in addition to the most significant bound ligand conformations. The models can be loaded into, for example, the Python Molecular Viewer , and 3D analysis performed.
This archive will also facilitate the testability of our results.
Does telmisartan selectively modulate PPARgamma?
Benson, et.al. , presented the ARBs as suited to PPARgamma modulation. Their primary conclusion was that Telmisartan's structure allowed it to exhibit selective modulation, exhibiting in-vitro PPARgamma agonistic activity at low concentrations, changing to antagonistic activity at higher concentrations.
Tsukahara, et.al.  recently studied a number of PPAR agonists. They found that agonistic activity disappears when TYR473 is mutated, and noted the importance of HIS323 and HIS449.
We would note, however, that the extreme affinity which Telmisartan exhibits for the ubiquitous VDR might well alter expression of many hormones at concentrations lower than those at which Telmisartan begins to modulate PPARgamma. This may make it very difficult to evaluate cause and effect in the cascade of metabolic changes which will result from Telmisartan's blockade of the VDR.
Bovine and guinea pig AT2R1 for FDA in-vitro ARB studies
While modelling the ARBs docking into the AT2R1 receptor, we were struck by data in United States Food and Drug Administration (US FDA) documents which did not exactly match our own observations.
For example, there are inconsistencies between our predictions for the relative efficacies of Olmesartan, Candesartan and Losartan; and those of Figure 22.214.171.124 of FDA NDA21-286 . The NDA's in-vitro experiments, using Cavia porcellus, showed Olmesartan as having the highest ARB efficacy, as we did, but found Candesartan close in efficacy to Olmesartan (1.2×) and Losartan to be less effective (3.4×). Our study found Losartan (Ki≈0.5 nmol) to be a better antagonist of AT2R1 than was Candesartan (Ki≈1.5 nmol).
Multiple sequence alignment highlighting differences between AT2R1 from Homo sapiens, Cavia porcellus and Bos taurus.
Our model predicts that the primary residues involved in docking most of the ARBs are GLN15, GLY194, GLY196, THR198 and GLY203.
The binding pocket around GLN15 is conserved in all three homologies.
However, in Bos taurus, the Isoleucine residue 193 is mutated to Valine. Candesartan has 6 hydrophobic contacts with ILE193, while Losartan and Olmesartan have only one. It is thus very likely that substitution of ILE193 will differentially effect the degree of Candesartan's antagonism of Bos taurus AT2R1 receptors, when compared with that of other ARBs, less dependent on contacts with ILE193.
Additionally, there is a mutation in Leucine 205, structurally adjacent to GLY203. GLY203 has seven hydrophobic contacts with Olmesartan, eight with Losartan, and six with Candesartan. In Cavia porcellus, this Glycine is mutated to Methionine.
The authors consequently believe that the FDA should re-examine the acceptability of Bos taurus and Caviaporcellus tissues for demonstration of the efficacy of ARBs.
It was beyond the scope of this study to model AT2R1 receptors for all three species used in the FDA in-vitro data. This should form a topic for ongoing research.
The FDA-approved prescribing information for Valsartan states "Valsartan does not bind to or block other hormone receptors or ion channels known to be important in cardiovascular regulation." This is an accurate statement of current knowledge about ARB in-vivo activity.
Yet this study found Valsartan (and the other ARBs) had a profound affinity for the hormone receptor VDR, for PPARgamma and for CCR2b. Clearly, if our modelling data sustains validation in the laboratory, clinical medicine will need to re-examine current concepts of how ARBs function in-vivo. It is possible that ARBs may become useful as potent immunomodulatory agents in addition to their current indication as cardiovascular drugs. This study has shown how each ARB acts upon several key receptors of the immune system, and should serve as a solid basis for better understanding the anti-inflammatory properties of this class of pharmaceutical.
Hardware and molecular tools
Two network servers were configured with Debian Linux. 'AutoDock' [25, 26, 43, 44] was kindly supplied by Scripps' and 'Modeller' by Salilab . Ponder's 'Tinker' Toolset was downloaded from the cited location . The Fortran software sources for 'Modeller' and 'Tinker' were recompiled with 64-bit Athlon-class optimizations applied, to suit the 64-bit CPU. Each server had 1 Gigabyte of memory, and a 160 Gigabyte hard disk. They were networked (using Samba ) to the primary Windows 2000 based workstation. The workstation also ran AutoDock (using the Cygwin executables), Python Molecular Viewer , and AutoDock Tools .
Optimization of the modelling software parameters
Autodock uses a default grid size of 0.375 Angstroms. This was changed to 0.2 Angstroms, noticeably improving upon the Ki calculated with the coarser grid. However, the computing time with this more precise grid was increased four-fold. To ensure more reliable minima from AutoDock's Lamarckian genetic algorithm, the 'population size' parameter "ga_pop_size" was increased from 50 to 100, and the number of energy calculations for each set, "ga_num_evals," was increased from 250,000 to 1,000,000. One set of AutoDock grid maps was typically generated for each receptor, and multiple ligands were docked without changing the grid maps. Docking parameter files were edited using the Linux ASCII text editor.
Construction of ligand and receptor molecules
Akira Dobashi's 3D Pharmaceutical Structure Database at Pharmis.org  (Tokyo University of Pharmacy and Life Sciences) was the primary source of ARB models. Olmesartan had to be built with Ghemical , running on a Linux server. Receptor coordinates were taken from the RCSB Protein Databank (PDB), or generated using Modeller  (as detailed in the text).
LigPlot and HBPLUS
McDonald's HBPLUS software [56, 55] takes, as input, the computed 3D ligand-receptor complex and produces a table of hydrogen bonds formed between the ligand and the receptor. It also produces tables of non-bonding hydrophobic contacts between the ligand atoms and receptor residues (default distance parameters were used for both bonds and contacts). Wallace and Laskowski's LigPlot software [53, 54] takes those tables and creates a 2D representation of the bonds and contacts, iteratively optimizing the output against a set of user-specified plot parameters. For example, weight-parameters can be assigned to minimize areas where the plot of hydrophobic bonds becomes too dense, forcing LigPlot to iteratively move the 2D positions of the residues so as to minimize that clutter, and thus make the output more readable. The output of Ligplot is PostScript, which was modified with a text editor to maximize font readability, and crop excess white space.
Special thanks to Meg Mangin, Belinda J Fenter, Barb Oberle, Lottie Stanley, and Karen Marshall.
- Mann DL, Deswal A: Angiotensin-receptor blockade in acute myocardial infarction – a matter of dose. N Engl J Med. 349 (20): 1963-5. 10.1056/NEJMe038163. 2003 Nov 13View ArticlePubMedGoogle Scholar
- United States Food and Drug Administration: Approval Package for NDA21-286. Pharmacology Review, figures 126.96.36.199,188.8.131.52 and184.108.40.206, http://www.fda.gov/cder/foi/nda/2002/21-286_Benicar_pharmr_P1.pdf
- Izuhara Y, Nangaku M, Inagi R, Tominaga N, Aizawa T, Kurokawa K, van Ypersele de Strihou C, Miyata T: Renoprotective Properties of Angiotensin Receptor Blockers beyond Blood Pressure Lowering. J Am Soc Nephrol. 2005, 16 (12): 3631-41. 10.1681/ASN.2005050522.View ArticlePubMedGoogle Scholar
- Lewis EJ, Lewis JB: Treatment of diabetic nephropathy with angiotensin II receptor antagonist. Clin Exp Nephrol. 2003, 7 (1): 1-8. 10.1007/s101570300000.View ArticlePubMedGoogle Scholar
- Brenner BM, Cooper ME, de Zeeuw D, Keane WF, Mitch WE, Parving HH: Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Engl J Med. 2001, 345: 861-869. 10.1056/NEJMoa011161.View ArticlePubMedGoogle Scholar
- Viberti GC, Wheeldon MN: Microalbuminuria reduction with valsartan in patients with type 2 diabetes mellitus: A blood pressure-independent effect. Circulation. 2002, 106: 672-678. 10.1161/01.CIR.0000024416.33113.0A.View ArticlePubMedGoogle Scholar
- Schieffer B, Bunte C, Witte J, Hoeper K, Boger RH, Schwedhelm E, Drexler H: Comparative effects of AT1-antagonism and angiotensin-converting enzyme inhibition on markers of inflammation and platelet aggregation in patients with coronary artery disease. J Am Coll Cardiol. 44 (2): 362-8. 10.1016/j.jacc.2004.03.065. 2004 Jul 21View ArticlePubMedGoogle Scholar
- Luno J, Praga M, de Vinuesa SG: The reno-protective effect of the dual blockade of the renin angiotensin system (RAS). Curr Pharm Des. 2005, 11 (10): 1291-300. 10.2174/1381612053507413.View ArticlePubMedGoogle Scholar
- Waterhouse JC, Marshall TG, Fenter B, Mangin M, Blaney G: High levels of active 1,25-dihydroxyvitamin D despite low levels of the 25-hydroxyvitamin D precursor - Implications of dysregulated vitamin D for disgnosis and treatment of Chronic Disease. Vitamin D: New Research. Edited by: Stoltz VD. 2006, New York: Nova Science Publishers, 1:Google Scholar
- Marshall TG, Marshall FE: Sarcoidosis succumbs to antibiotics – implications for autoimmune disease. Autoimmun Rev. 2004, 3 (4): 295-300. 10.1016/j.autrev.2003.10.001.View ArticlePubMedGoogle Scholar
- Raz E, Tighe H, Sato Y, Corr M, Dudler JA, Roman M, Swain SL, Spiegelberg HL, Carson DA: Preferential induction of a Th1 immune response and inhibition of specific IgE antibody formation by plasmid DNA immunization. Proc Natl Acad Sci USA. 93 (10): 5141-5145. 10.1073/pnas.93.10.5141. 1996 May 14PubMed CentralView ArticlePubMedGoogle Scholar
- Cantorna MT, Zhu Y, Froicu M, Wittke A: Vitamin D status, 1,25-dihydroxyvitamin D3, and the immune system. Am J Clin Nutr. 2004, 80 (6 Suppl): 1717S-20S.PubMedGoogle Scholar
- Mallat Z, Ait-Oufella H, Tedgui A: Regulatory T cell responses: potential role in the control of atherosclerosis. Curr Opin Lipidol. 2005, 16 (5): 518-24. 10.1097/01.mol.0000182532.11512.90.View ArticlePubMedGoogle Scholar
- Yoon JW, Jun HS: Autoimmune destruction of pancreatic Beta cells. Am J Ther. 2005, 12 (6): 580-91. 10.1097/01.mjt.0000178767.67857.63.View ArticlePubMedGoogle Scholar
- Wittke A, Weaver V, Mahon BD, August A, Cantorna MT: Vitamin D receptor-deficient mice fail to develop experimental allergic asthma. J Immunol. 173 (5): 3432-6. 2004 Sep 1View ArticlePubMedGoogle Scholar
- Dusso AS, Kamimura S, Gallieni M, Zhong M, Negrea L, Shapiro S, Slatopolsky E: gamma-Interferon-induced resistance to 1,25-(OH)2 D3 in human monocytes and macrophages: a mechanism for the hypercalcemia of various granulomatoses. J Clin Endocrinol Metab. 1997, 82 (7): 2222-32. 10.1210/jc.82.7.2222.PubMedGoogle Scholar
- Potashnik G, Lunenfeld E, Levitas E, Itskovitz J, Albutiano S, Yankowitz N, Sonin Y, Levy J, Glezerman M, Shany S: The relationship between endogenous oestradiol and vitamin D3 metabolites in serum and follicular fluid during ovarian stimulation for in-vitro fertilization and embryo transfer. Hum Reprod. 1992, 7 (10): 1357-60.PubMedGoogle Scholar
- Chatterjee M: Vitamin D and genomic stability. Mutat Res. 475 (1–2): 69-87. 2001 Apr 18View ArticlePubMedGoogle Scholar
- Nagpal S, Na S, Rathnachalam R: Noncalcemic actions of vitamin D receptor ligands. Endocr Rev. 2005, 26 (5): 662-87. 10.1210/er.2004-0002.View ArticlePubMedGoogle Scholar
- Benson SC, Pershadsingh HA, Ho CI, Chittiboyina A, Desai P, Pravenec M, Qi N, Wang J, Avery MA, Kurtz TW: Identification of telmisartan as a unique angiotensin II receptor antagonist with selective PPARgamma-modulating activity. Hypertension. 2004, 43 (5): 993-1002. 10.1161/01.HYP.0000123072.34629.57.View ArticlePubMedGoogle Scholar
- Cabrero A, Laguna JC, Vazquez M: Peroxisome proliferator-activated receptors and the control of inflammation. Curr Drug Targets Inflamm Allergy. 2002, 1: 243-8. 10.2174/1568010023344616.View ArticlePubMedGoogle Scholar
- Genolet R, Wahli W, Michalik L: PPARs as drug targets to modulate inflammatory responses?. Curr Drug Targets Inflamm Allergy. 2004, 3 (4): 361-75. 10.2174/1568010042634578.View ArticlePubMedGoogle Scholar
- Preobrazhensky AA, Dragan S, Kawano T, Gavrilin MA, Gulina IV, Chakravarty L, Kolattukudy PE: Monocyte chemotactic protein-1 receptor CCR2B is a glycoprotein that has tyrosine sulfation in a conserved extracellular N-terminal region. J Immunol. 165 (9): 5295-303. 2000 Nov 1View ArticlePubMedGoogle Scholar
- Tanaka S, Green SR, Quehenberger O: Differential expression of the isoforms for the monocyte chemoattractant protein-1 receptor, CCR2, in monocytes. Biochem Biophys Res Commun. 290 (1): 73-80. 10.1006/bbrc.2001.6149. 2002 Jan 11View ArticlePubMedGoogle Scholar
- Casey PJ, Gilman AG: G protein involvement in receptor-effector coupling. J Biol Chem. 263 (6): 2577-80. 1988 Feb 25PubMedGoogle Scholar
- AutoDock, Automatic Docking of Flexible Ligands to Macromolecules.http://www.scripps.edu/mb/olson/doc/autodock/
- Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK, Olson AJ: Automated docking using Lamarckian genetic algorithm and an empirical binding free energy function. J Comp Chem. 19: 1639-1662. 10.1002/(SICI)1096-987X(19981115)19:14<1639::AID-JCC10>3.0.CO;2-B.
- Osterberg F, Morris GM, Sanner MF, Olson AJ, Goodsell DS: Automated docking to multiple target structures: incorporation of protein mobility and structural water heterogeneity in AutoDock. Proteins. 46 (1): 34-40. 10.1002/prot.10028. 2002 Jan 1View ArticlePubMedGoogle Scholar
- Toprakci M, Yelekci K: Docking studies on monoamine oxidase-B inhibitors: estimation of inhibition constants (K(i)) of a series of experimentally tested compounds. Bioorg Med Chem Lett. 15 (20): 4438-46. 10.1016/j.bmcl.2005.07.043. 2005 Oct 15View ArticlePubMedGoogle Scholar
- Chen K, Adelstein SJ, Kassis AI: Molecular simulation of ligand-binding with DNA: implications for 125I-labeled pharmaceutical design. Int J Radiat Biol. 2004, 80 (11–12): 921-6.View ArticlePubMedGoogle Scholar
- Xu HE, Lambert MH, Montana VG, Plunket KD, Moore LB, Collins JL, Oplinger JA, Kliewer SA, Gampe RT, McKee DD, Moore JT, Willson TM: Structural determinants of ligand binding selectivity between the peroxisome proliferator-activated receptors. Proc Natl Acad Sci U S A. 98 (24): 13919-24. 10.1073/pnas.241410198. 2001 Nov 20PubMed CentralView ArticlePubMedGoogle Scholar
- Rochel N, Wurtz JM, Mitschler A, Klaholz B, Moras D: The crystal structure of the nuclear receptor for vitamin D bound to its natural ligand. Mol Cell. 2000, 5 (1): 173-9. 10.1016/S1097-2765(00)80413-X.View ArticlePubMedGoogle Scholar
- Eelen G, Verlinden L, Rochel N, Claessens F, De Clercq P, Vandewalle M, Tocchini-Valentini G, Moras D, Bouillon R, Verstuyf A: Superagonistic action of 14-epi-analogs of 1,25-dihydroxyvitamin D explained by vitamin D receptor-coactivator interaction. Mol Pharmacol. 2005, 67 (5): 1566-73. 10.1124/mol.104.008730.View ArticlePubMedGoogle Scholar
- Scripps Research Institute, Molecular Graphics Laboratory, MGLtools. http://www.scripps.edu/~sanner/software/
- The Python Molecular Viewer. http://www.pymol.org
- Strader CD, Fong TM, Graziano MP, Tota MR: The family of G-protein-coupled receptors. FASEB J. 1995, 9 (9): 745-54.PubMedGoogle Scholar
- Shi XF, Liu S, Xiangyu J, Zhang Y, Huang J, Liu S, Liu CQ: Structural analysis of human CCR2b and primate CCR2b by molecular modeling and molecular dynamics simulation. J Mol Model (Online). 2002, 8 (7): 217-22. 10.1007/s00894-002-0089-6.View ArticleGoogle Scholar
- Pappu RV, Marshall GR, Ponder JW: A potential smoothing algorithm accurately predicts transmembrane helix packing. Nat Struct Biol. 1999, 6 (1): 50-5. 10.1038/4922.View ArticlePubMedGoogle Scholar
- TINKER – Software tools for molecular design. http://dasher.wustl.edu/tinker
- Sali A, Blundell TL: Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol. 234 (3): 779-815. 10.1006/jmbi.1993.1626. 1993 Dec 5View ArticlePubMedGoogle Scholar
- MODELLER Program for comparative protein structure modelling by satisfaction of spatial restraints. http://salilab.org/modeller/modeller.html
- Baba M, Nishimura O, Kanzaki N, Okamoto M, Sawada H, Iizawa Y, Shiraishi M, Aramaki Y, Okonogi K, Ogawa Y, Meguro K, Fujino M: A small-molecule, nonpeptide CCR5 antagonist with highly potent and selective anti-HIV-1 activity. Proc Natl Acad Sci USA. 96 (10): 5698-5703. 10.1073/pnas.96.10.5698. 1999 May 11PubMed CentralView ArticlePubMedGoogle Scholar
- Martin SS, Boucard AA, Clement M, Escher E, Leduc R, Guillemette G: Analysis of the third transmembrane domain of the human type 1 angiotensin II receptor by cysteine scanning mutagenesis. J Biol Chem. 279 (49): 51415-23. 10.1074/jbc.M407965200. 2004 Dec 3View ArticlePubMedGoogle Scholar
- Goodsell DS, Olson AJ: Automated Docking of Substrates to Proteins by Simulated Annealing. Proteins. 1990, 8 (3): 195-202. 10.1002/prot.340080302.View ArticlePubMedGoogle Scholar
- Morris GM, Goodsell DS, Huey R, Olson AJ: Distributed Automated Docking of Flexible Ligands to Proteins: Parallel Applications of AutoDock 2.4. J Comput Aided Mol Des. 1996, 10 (4): 293-304. 10.1007/BF00124499.View ArticlePubMedGoogle Scholar
- Omdahl JL, Morris HA, May BK: Hydroxylase enzymes of the vitamin D pathway: expression, function, and regulation. Annu Rev Nutr. 2002, 22: 139-66. 10.1146/annurev.nutr.22.120501.150216.View ArticlePubMedGoogle Scholar
- Wang J, Cieplak P, Kollman PA: How Well Does a Restrained Electrostatic Potential (RESP) Model Perform in Calcluating Conformational Energies of Organic and Biological Molecules?. J Comput Chem. 2000, 21: 1049-1074. 10.1002/1096-987X(200009)21:12<1049::AID-JCC3>3.0.CO;2-F.View ArticleGoogle Scholar
- Akira Dobashi's: 3D Pharmaceutical Structure Database. Tokyo University of Pharmacy and Life Sciences, http://www.pharmis.org/3dpsd/index.htm
- Ghemical molecular modelling package. http://www.bioinformatics.org/ghemical/
- Blair JD: SAMBA: Integrating UNIX and Windows. 1998, Seattle: SSC Publishing, ISBN: 1-57831-006-7Google Scholar
- Acevedo A, Stoynova L, Davis K, Solorzano R, Collins ED: Role of residues 143 and 278 of the human nuclear Vitamin D receptor in the full-length and Delta165-215 deletion mutant. J Steroid Biochem Mol Biol. 2004, 89–90 (1–5): 83-7. 10.1016/j.jsbmb.2004.03.051.View ArticlePubMedGoogle Scholar
- Tsukahara T, Tsukahara R, Yasuda S, Makarova N, Valentine WJ, Allison P, Yuan H, Baker DL, Li Z, Bittman R, Parrill A, Tigyi G: Different residues mediate recognition of 1-O-oleyl-lysophosphatidic acid and rosiglitazone in the ligand binding domain of PPAR1. J Biol Chem. 2005 Dec 1.
- Wallace AC, Laskowski RA, Thornton JM: A program to generate schematic diagrams of protein-ligand interactions. Protein Eng. 1995, 8 (2): 127-34.View ArticlePubMedGoogle Scholar
- LIGPLOT-Program for automatically plotting protein-ligand interactions. http://www.biochem.ucl.ac.uk/bsm/ligplot/ligplot.html
- McDonald IK, Thornton JM: Satisfying Hydrogen Bonding Potential in Proteins. J Mol Biol. 238 (5): 777-93. 10.1006/jmbi.1994.1334. 1994 May 20View ArticlePubMedGoogle Scholar
- HBPLUS-Hydrogen Bond Calculation Program. http://www.biochem.ucl.ac.uk/bsm/hbplus/home.html
- Shaffer PL, McDonnell DP, Gewirth DT: Characterization of transcriptional activation and DNA-binding functions in the hinge region of the vitamin D receptor. Biochemistry. 44 (7): 2678-85. 10.1021/bi0477182. 2005 Feb 22View ArticlePubMedGoogle Scholar
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