Browsing by Subject "telakointi"
Now showing items 1-4 of 4
-
(2010)11β-hydroxysteroid dehydrogenase/reductase (11β-HSD) enzymes 1 and 2 regulate the amount of cortisone and cortisol in human tissues. Since overexpression of 11β-HSD1 especially in the adipose tissue causes symptoms of metabolic syndrome, selective inhibition of 11β-HSD1 provides a way to treat this syndrome and type II diabetes. Inhibition of 11β-HSD2 causes cortisol-dependent mineralocorticoid activation, which leads to hypertensive side effects. There are several reported 11β-HSD1 inhibitors, for selective 11β-HSD2 inhibitition, only a few compounds have been developed. The difference between 11β-HSD1 and 2 ligand binding sites is unknown, which complicates the search of selective inhibitors to both of the enzymes. This study was done with two aims: (1) to identify the difference between the two isozymes, (2) to create pharmacophore models for selective 11β-HSD2 inhibitiors. These tasks were approached with computational methods: homology modeling, docking, ligand-based pharmacophore modeling and virtual screening. The homology model of 11β-HSD2 was constructed using SwissModeler and it showed satisfying superimposition both with is template 17β-HSD1 and 11β-HSD1. The difference between the enzymes could not be identified by visual inspections Therefore, seven compounds, of which six are 11β-HSD2 -selective, were docked both to 11β-HSD1 and 11β-HSD2 ligand binding sites using the program GOLD. The docking results revealed that the compounds orientate differently in the enzymes. To 11β-HSD1, the compounds were anchored similar than unselective compound carbenoxolone, whereas in 11β-HDS2, they adopted a flipped binding mode. The flipped binding mode in 11β-HDS2 enables hydrogen bonds to Ser310 and to Asn171, both residues that are only present in 11β-HSD2. Pharmacophore modeling and virtual screening were done using the program LigandScout3.0. The ligand-based pharmacophores were based on the six 11β-HSD2 selective compounds, which were also used for the docking studies. Both of the models consisted of six features (hydrogen bond acceptors, hydrogen bond donor and hydrophobic feature) besides the exclusion volumes. The most important features considering the 11β-HSD2 selectivity seem to be the hydrogen bond acceptor feature that could interact with the Ser310 and the hydrogen bond donor feature next to it. The interaction pair for this hydrogen bond donor feature was not observed in the homology model. However, a possibility of water molecule as an interaction pair was evaluated and it seems to be a possible solution to the problem. Since both of the models were able to find the selective 11β-HSD2 inhibitors and exclude the unselective ones from the test set database, they were employed for the screening of the database that consists of 2700 compounds stored at the University of Innsbruck. From the hits of these screenings ten compounds were selected and sent to biological testing. The results of the biological tests will decide how well the models represent the theory of the 11β-HSD2 selectivity.
-
(2012)The orexinergic system is a central regulator for sleep-wake rhythm and energy homeostasis. Dysfunction of the system is at least one of the reasons behind narcolepsy, in addition to which insomnia, obesity and certain cancers could be treated by targeting orexin receptors. The orexin system in human comprises two receptor subtypes, orexin receptor 1 and 2 (OX₁R and OX₂R respectively) as well as two cognate ligands, peptides orexin-A and -B. In this study the focus is on OX₁R and orexin-A. The aims of the study are (1) to propose a binding mode for orexin-A to OX₁R and (2) to understand the molecular interactions of OX₁R leading to receptor activation. I order to create 3D molecular models of OX₁R, a sequence alignment of the eight G proteincoupled receptors (GPCRs) that have been crystallized up to date was first generated by ClustalX and adjusted based on the superimposition by SYBYL-X. Structurally conserved regions were deduced from the alignment and used to add the orexin receptors. Five different models built with MODELLER were selected for their large binding cavity among a large pool of models. These models were constructed based on the chemokine receptor 4 (PDB Id:3ODU), as such and a modified version where TM3 was moved by 1 Å further from the center of the binding cavity, from the β₂-adrenoceptor (PDB Id: 2RH1) and from the adenosine receptor A2A (PDB Id: 2YD0), as such and with rotamer changes to few binding site residues. Orexin-A with straight conformation found by NMR (PDB Id:1WSO) was docked to these models using ZDOCK and RDOCK. In addition, an in-house docking protocol was implemented, but could not be validated. Docking poses were scored by purpose built knowledge based scoring function and clustered. High scoring clusters were then used to converge to three different binding modes. As a result, we suggest that the binding site of OX₁R consists of two hydrophobic walls, one from TM3 and TM5, the other from TM6 and TM7. Binding modes include a hydrogen bond network between the ligand and especially binding site residues Gln1263.32, Thr2235.46, Asn3186.55, Lys3216.58 and Tyr3117.43. Based on the binding modes, it is suggested that the OX₁R is activated by similar binding site contraction as β-adrenoceptors and adenosine A2A. The contraction in could result from the hydrogen bonds between ligand, Gln1263.32, Thr2235.46 and Asn3186.55. The hydrogen bonding of Thr2235.46 can also disrupt interactions between TM5 and TM3, an interaction which is identified as an important factor in keeping the receptor in the inactive state. The role of other ligand residues would be to direct ligand binding and keep the ligand in the helical conformation.
-
(2015)Lead molecule search is the first part of drug design. This process can be done using computerized docking of ligands into target proteins. Usually this requires expensive software and powerful computer systems specifically made for the process. There are however some programs that are available for free and can be run on home computers. The purpose of this Master's Thesis was to see how these free software can be used for the task of docking and also to create a method or a guideline for such work. Protein kinase C (PKC), a popular target for drug design, was chosen as a target of inhibitor design. PKC is part of a larger family of serine/threonine kinases and formed of 10 isoforms all with different effects on cellular functions. The large amount of related kinases and the similarities in their sequences make finding selective inhibitors a difficult process. Homology models of all PKC isoforms in three known conformations solved by x-ray diffraction (pdb: 1XJD, 2I0E and 3A8W) were created using Modeller. Into these models a set of possible ligands from the free database of molecules ZINC was docked using Autodock Vina utilizing a script created for docking multiple ligands into multiple targets. The dockings resulted in some interesting results. Six molecules were recognized as possible lead molecules for further research. None of these molecules had any patents or previous results of protein kinase inhibition connected to them. The most interesting result was the finding that coluracetam, a nootropic drug of the racetam family, might be a protein kinase inhibitor. Racetams are usually considered drugs that lead to PKC activation. It has been proposed that inhibitors may prolong the lifetime of kinases in the cells leading to increased activity in the long term. In our opinion coluracetam might prove to be a good tool for studying the complex way kinase activity is modulated. The methods and scripts used in this work will be released for free use.
-
(2016)Membrane-bound pyrophosphatases (mPPases) are a potential target for drugs against many neglected protozoan diseases, such as malaria, leishmaniasis, toxoplasmosis and trypanosomiasis. New drugs against these diseases are urgently needed, as the clinically used ones are either not effective, suffer from side effects, or resistance against them is developing. The mPPases of these protozoans are genetically conserved, while mammalian DNA does not encode them. A drug development project to find mPPase inhibitors was started, based on mPPase structures solved through X-Ray crystallography. Four hit compounds were identified. The aim of this study was to investigate the binding of these hit compounds at the mPPase binding site, and based on these results, to develop and synthesize novel compounds with higher affinity. A hit compound with an isoxazole ring was chosen as the model compound to be developed further. These novel compounds were evaluated by docking them into the binding site. Eight compounds were chosen to be synthesized and four to be purchased. The Suzuki-Miyaura cross-coupling reaction was used to couple the isoxazole core to different aromatic substituents, producing 3,5-disubstituted isoxazoles. The reactions mostly succeeded, but the yields were uniformly low. Developing the reaction using different solvents and reaction conditions did not produce clear results. Thirteen compounds were tested for activity, including an intermediate product of the synthesis. Two of the compounds showed increased inhibition activity compared to the hit compound, with approximated IC50 values of 10 and 40 μM, respectively. The knowledge gained from these studies can be used to further develop more efficient inhibitors.
Now showing items 1-4 of 4