Ameliorative potential of Lavandula stoechas in metabolic syndrome via multitarget interactions.

ETHNOPHARMACOLOGICAL IMPORTANCE: Decoction and infusion prepared from aerial parts of Lavandula stoechas L. (L. stoechas) have been traditionally used as remedy against several components of metabolic syndrome (MetS) and associated disorders including type II diabetes and cardiovascular diseases by Anatolian people. AIM OF THE STUDY: The aim is to elucidate the potential ameliorative effects of L. stoechas aqueous extracts on insulin resistance and inflammation models through multitarget in vitro approaches and also to elucidate mechanism of action by analyzing transcriptional and metabolic responses. MATERIALS AND METHODS: An aqueous extract was prepared and fractionated to give rise to ethyl acetate (EE) and butanol (BE) extracts. The anti-insulin resistance effects of BE and EE were evaluated on palmitate induced insulin resistance model of H4IIE, C2C12 and 3T3L1 cells by using several metabolic parameters. Specifically, whole genome transcriptome analysis was performed by using microarray over 55.000 genes in control, insulin resistant and EE (25 µg/mL) treated insulin resistant H4IIE cells. Anti-inflammatory effects of both extracts were analyzed in LPS-stimulated RAW264.7 macrophages. RESULTS: Both EE and BE at low doses (25-50 µg/mL) significantly decreased hepatic gluconeogenesis in H4IIE cell line by suppressing the expression of PEPCK and G6Pase. In C2C12 myotubes, both extracts increased the insulin stimulated glucose uptake more effectively than metformin. Both extracts decreased the isoproterenol induced lipolysis in 3T3L1 cell line. Moreover, they also effectively increased the expression of lipoprotein lipase protein level in insulin resistant myotubes at low doses. EE increased the protein level of PPARγ and stimulated the activation AKT in insulin resistant H4IIE and C2C12 cell lines. The results obtained from biochemical assays, mRNA/protein studies and whole genome transcriptome analyses were found to be complementary and provided support for the hypothesis that EE might be biologically active against insulin resistance and act through the inhibition of liver gluconeogenesis and AKT activation. Besides, LPS induced inflammation in RAW264.7 macrophages was mainly inhibited by EE through suppression of iNOS/NO signaling, IL1ß and COX-2 genes. HPLC-TOF/MS analysis of EE of L. stoechas mainly resulted in caffeic acid, apigenin, luteolin, rosmarinic acid and its methyl ester, 4-hydroxybenzoic acid, vanillic acid, ferrulic acid and salicylic acid. CONCLUSION: Data suggest that EE of L. stoechas contains phytochemicals that can be effective in the treatment/prevention of insulin resistance and inflammation. These results validate the traditional use of L. stoechas in Anatolia against several metabolic disorders including metabolic syndrome.

TcR recognition of the MHC-peptide dimer: structural properties of a ternary complex.

We have developed a method that utilizes site-specific mutation data, sequence analysis, immunological data and free-energy minimization, to determine structural features of the ternary complex formed by the T-cell receptor (TcR) and the class I major histocompatibility complex (MHC) molecule bound by peptide. The analysis focuses on the mouse Kd MHC system, for which a large set of clones with sequenced T-cell receptors is available for specific peptides. The general philosophy is to reduce the uncertainties and computation time in a free-energy minimization procedure by identifying and imposing experimental constraints. In addition to assessing compatibility with various kinds of immunological data, we are particularly interested in differentiating the structural features peculiar to this particular system from generic features, and in ascertaining the robustness of the structure; i.e. determining, in so far as possible, the variations in the structure that leave its compatibility with experiment unaltered from those that do not. This last is equivalent to recognizing that certain features of the model are presented with a reasonable degree of confidence, while others remain highly tentative. The central conclusion in the former category is a placement of the TcR on the Kd peptide complex, which has its beta 2, beta 3 and alpha 3 loops (i.e. the second and third complementarity-determining region of the TcR beta chain, and the third complementarity-determining region of the alpha chain) covering the peptide; the alpha 1 and alpha 2 loops covering the MHC alpha 1 helix; the alpha 2 loop interacting with residues on the MHC beta sheet; and the beta 1 and (part of) the beta 2 loops covering the alpha 2 MHC helix. More specifically, our findings include the following. (1) A highly conserved histidine residue in the first complementarity-determining region of the TcR beta chain (beta:CDR1) points outward and interacts with highly conserved side-chains on the MHC alpha 2 helix. (2) The amino-terminal portion of the beta 2 loop interacts with the carboxyl portion of the peptide. A particularly important interaction is K4 of the loop interacting with E8 of the peptide. (3) Charged side-chains of the 11-residue TcR alpha 2 loop interact with conserved charged side-chains at positions 44, 58, 61 and 68 on the MHC. (4) The TcR beta 3 loop interacts with the amino-terminal part of the peptide, up through position 4. (5) the TcR alpha 3 loop interacts with the central portion of the peptide and stacks against the beta 2 loop. (6) Because of the interaction between the beta 2 loop and the peptide, and stacking of beta 2 on alpha 3, alpha 3 gene and V beta gene selection can be correlated. (7) Using the topology of the recently solved TcR alpha chain we predict that the alpha 2 loop interacts with the loop on the MHC beta sheet floor, which encompasses residues 42 to 44.

Free energy mapping of class I MHC molecules and structural determination of bound peptides.

Free energy maps of the binding site are constructed for class I major histocompatibility complex (MHC) proteins, by rotating and translating amino acid probes along the cleft, and performing a side-chain conformational search at each position. The free energy maps are used to determine favorable residue positions that are then combined to form docked peptide conformations. Because the generic backbone structural motif of peptides bound to class I MHC is known, the mapping is restricted to appropriate regions of the site, but allows for the sometimes substantial variations in backbone and side-chain conformations. In a test demonstrating the quality of predictions for a known MHC site using only a rotational and conformational search, we started from the crystal structure of the HIV-1 gp120/HLA-A2 complex, and predicted the HLA-A2 bound structures of peptides from the influenza matrix protein, the HIV-1 reverse transcriptase, and the human T cell leukemia virus. The calculated peptides are at 1.6, 1.3, and 1.4 A all-atom RMSDs from their respective crystal structures (Madden DR, Garboczi DN, Wiley DC, 1993). A further test, which also included a local translational search, predicted structures across MHCs. In particular, we obtained the Kb/SEV-9 complex (Fremont DH et al., 1992, Science 257:919-927) starting with the complex between HLA-B27 and a generic peptide (Madden DR, Gorga JC, Strominger JL, Wiley DC, 1991, Nature (Lond) 353:321-325), with an all-atom RMSD of 1.2 A, indicating that the docking procedure is essentially as effective for predictions across MHCs as it is for determinations within the same MHC, although at substantially greater computational cost. The requirements for further improvement in accuracy are identified and discussed briefly.

Toward computational determination of peptide-receptor structure.

We introduce a method for docking small flexible ligands of the size of dipeptides and phosphocholine and test it against crystallographic complexes. We then show how the method can be used as the basis for a strategy for solving the much more difficult problem of docking fully flexible peptides in the 8-10-residue size range. After developing the method we apply it to peptide-MHC class I systems and find that the predictions are in accord with biological and crystallographic data.