Biomedical subjects

Reino Laatikainen

Publications and source records attributed to Reino Laatikainen.

13 recordsLinked to original sources

PubMed2007

1H NMR metabonomics of plasma lipoprotein subclasses: elucidation of metabolic clustering by self-organising maps.

(1)H NMR spectra of plasma are known to provide specific information on lipoprotein subclasses in the form of complex overlapping resonances. A combination of (1)H NMR and self-organising map (SOM) analysis was applied to investigate if automated characterisation of subclass-related metabolic interactions can be achieved. To reliably assess the intrinsic capability of (1)H NMR for resolving lipoprotein subclass profiles, sum spectra representing the pure lipoprotein subclass part of actual plasma were simulated with the aid of experimentally derived model signals for 11 distinct lipoprotein subclasses. Two biochemically characteristic categories of spectra, representing normolipidaemic and metabolic syndrome status, were generated with corresponding lipoprotein subclass profiles. A set of spectra representing a metabolic pathway between the two categories was also generated. The SOM analysis, based solely on the aliphatic resonances of these simulated spectra, clearly revealed the lipoprotein subclass profiles and their changes. Comparable SOM analysis in a group of 69 experimental (1)H NMR spectra of serum samples, which according to biochemical analyses represented a wide range of lipoprotein lipid concentrations, corroborated the findings based on the simulated data. Interestingly, the choline-N(CH(3))(3) region seems to provide more resolved clustering of lipoprotein subclasses in the SOM analyses than the methyl-CH(3) region commonly used for subclass quantification. The results illustrate the inherent suitability of (1)H NMR metabonomics for automated studies of lipoprotein subclass-related metabolism and demonstrate the power of SOM analysis in an extensive and representative case of (1)H NMR metabonomics.

Choline↗

PubMed2006

The inherent accuracy of 1H NMR spectroscopy to quantify plasma lipoproteins is subclass dependent.

Proton NMR spectroscopy as a means to quantify lipoprotein subclasses has received wide clinical interest. The experimental part is a fast routine procedure that contrasts favourably to other lipoprotein measurement protocols. The difficulties in using (1)H NMR, however, are in uncovering the subclass specific information from the overlapping data. The NMR-based quantification has been evaluated only in relation to biochemical measures, thereby leaving the inherent capability of NMR rather vague due to biological variation and diversity among the biochemical experiments. Here we will assess the use of (1)H NMR spectroscopy of plasma per se. This necessitates data for which the inherent parameters, namely the shapes and areas of the (1)H NMR signals of the subclasses are available. This was achieved through isolation and (1)H NMR experiments of 11 subclasses--VLDL1, VLDL2, IDL, LDL1, LDL2, LDL3, HDL(2b), HDL(2a), HDL(3a), HDL(3b) and HDL(3c)--and the subsequent modelling of the spectra. The subclass models were used to simulate biochemically representative sets of spectra with known subclass concentrations. The spectral analyses revealed 10-fold differences in the quantification accuracy of different subclasses by (1)H NMR. This finding has critical significance since the usage of (1)H NMR methodology in the clinical arena is rapidly increasing.

Computer Simulation↗

PubMed2006

beta-Amyloid infusion results in delayed and age-dependent learning deficits without role of inflammation or beta-amyloid deposits.

beta-Amyloid (Abeta) polypeptide plays a critical role in the pathogenesis of Alzheimer's disease (AD), which is characterized by progressive decline of cognitive functions, formation of Abeta deposits and neurofibrillary tangles, and loss of neurons. Increased genetic production or direct intracerebral administration of Abeta in animal models results in Abeta deposition, gliosis, and impaired cognitive functions. Whether aging renders the brain prone to Abeta and whether inflammation is required for Abeta-induced learning deficits is unclear. We show that intraventricular infusion of Abeta1-42 results in learning deficits in 9-month-old but not 2.5-month-old mice. Deficits that become detectable 12 weeks after the infusion are associated with a slight reduction in Cu,Zn superoxide dismutase activity but do not correlate with Abeta deposition and are not associated with gliosis. In rats, Abeta infusion induced learning deficits that were detectable 6 months after the infusion. Approximately 20% of the Abeta immunoreactivity in rats was associated with astrocytes. NMR spectrum analysis of the animals cerebrospinal fluid revealed a strong reduction trend in several metabolites in Abeta-infused rats, including lactate and myo-inositol, supporting the idea of dysfunctional astrocytes. Even a subtle increase in brain Abeta1-42 concentration may disrupt normal metabolism of astrocytes, resulting in altered neuronal functions and age-related development of learning deficits independent of Abeta deposition and inflammation.

Aging↗

PubMed2005

Birch PR-10c interacts with several biologically important ligands.

PR-10c is a unique member of PR-10 proteins in birch, since it is the only one known to be post-translationally modified by glutathione and is not constitutively expressed in pollen. Both reduced and S-glutathiolated forms of PR-10c show low ribonuclease activity. However, the major function of the protein is apparently not yet resolved. Our protein-ligand interaction studies with saturation transfer difference (STD) NMR revealed that PR-10c interacts with several biologically important molecules, including cytokinin, flavonoid glycosides, sterols and emodin. Competition study with deoxycholate and kinetin revealed no statistically significant binding interference, indicating that these ligands have different binding sites in PR-10c. Ligand docking studies with a molecular model of PR-10c support the STD NMR results of ligand binding and binding epitopes, suggesting that there are three potential binding sites in PR-10c: two in the hydrophobic cavity and one in the glycine-rich loop. Our docking calculations suggested that only kinetin interacts with the glycine-rich loop, the binding occurring through its adenine moiety. Clear ligand specificity could be observed in the binding of nucleotide derivatives. S-glutathiolation of PR-10c did not affect kinetin binding. The present results suggest that birch PR-10c is a multifunctional protein, which has diverse roles in plant stress responses.

Betula↗

PubMed2004

Ligand intramolecular motions in ligand-protein interaction: ALPHA, a novel dynamic descriptor and a QSAR study with extended steroid benchmark dataset.

The role of intramolecular motions in ligand-macromolecule interactions has been explored by developing and validating ALPHA, a novel QSAR (quantitative structure-activity relationship) descriptor. It is based on the spectral exponents (alpha), which measure the degree of 1/f alpha noise of coordinate fluctuations in molecular dynamics (MD) simulations. ALPHA is the first truly 'dynamic' QSAR descriptor, i.e., it can be derived directly from an MD trajectory. The performance of ALPHA was tested in detail employing the CBG (corticosteroid binding globulin) affinity of 31 benchmark steroids, supplemented with 11 steroids as an external test set. The only fair (42-50%) correlations of ALPHA with static 3D and electronic descriptors mean that ALPHA forms an independent molecular property. Furthermore, inclusion of ALPHA in the SOMFA/ESP model improves the correlation coefficient from 0.86 to 0.91, and /delta/ave from 0.46 to 0.36 for the benchmark dataset. The predictive ability of ALPHA can be interpreted as indirect evidence of the dynamic contribution to ligand-macromolecule interactions. The physical background of ALPHA is discussed and the importance of molecular motions for biological activity is anticipated.

Ligands↗

PubMed2004

Does mercury promote lipid peroxidation? An in vitro study concerning mercury, copper, and iron in peroxidation of low-density lipoprotein.

In order to explore the observed association among mercury, atherosclerosis, and coronary heart disease, the effects of mercury, copper, and iron on the peroxidation of low-density lipoprotein (LDL) and on the enzymatic activities of glutathione peroxidase and myeloperoxidase were investigated in vitro. On the basis of our nuclear magnetic resonance (NMR) experiments, we conclude that mercury does not promote the direct nonenzymatic peroxidation of LDL, like copper and iron. In our enzyme measurements, mercury inhibited slightly myeloperoxidase, although not significantly in presence of LDL. Instead, inorganic mercury, but not methylmercury chloride, inhibited glutathione peroxidase effectively and copper even at 10 micromol/L, below physiological concentrations, doubled the inhibition rate. Copper and iron had no direct effect on glutathione peroxidase, but they both seem to activate production of HOCl by myeloperoxidase. We conclude here that, first, mercury and methylmercury do not promote direct lipid peroxidation, but that, second, a simultaneous exposure to high inorganic mercury, copper, and iron and low selenium concentrations can lead to a condition in which mercury promotes lipid peroxidations. This mechanism provides a plausible molecular-level explanation for the observed association between high body mercury content and atherosclerosis.

Animals↗

PubMed2002

Correlative motions and memory effects in molecular dynamics simulations of molecules: principal components and rescaled range analysis suggest that the motions of native BPTI are more correlated than those of its mutants.

In this work MD simulations of the native bovine pancreatic trypsin inhibitor (BPTI) and 16 mutants were done in vacuum in order to study memory effects in the mutants using principal component analysis (PCA) and the rescaled range analysis (Hurst exponents). Both PCA and the rescaled range analysis support our previous proposition, based on PCA of lysozyme, that the motions of a native protein are more correlated than those of mutants. The methods are compared, the nature and applications of the rule and the role of the long-range correlations in MD time series (i.e. memory) are discussed in the context of collective motions.

Algorithms↗

PubMed2002

Stability and amino acid preferences of type VIII reverse turn: the most common turn in peptides?

Free energies of the alpha(r)beta and betabeta conformations of 14 tetrapeptides, based on the sequence SALN and protein X-ray structures, were calculated using molecular dynamics simulations and MM-PBSA calculations. The alphaalpha conformations of five of the tetrapeptides were also studied. SALN has been earlier shown by molecular dynamics simulations and NMR spectroscopy to have a tendency to form an alpha(r)beta turn. The gas-phase energy of the molecular mechanical force field (CHARMM), the electrostatic and non-polar solvation free energies and solute entropies were used to explain the free energy differences of the alphaalpha, betabeta and alpha(r)beta conformations of the peptides. The alpha(r)beta conformation of SALN and SATN was predicted to be slightly more stable than the extended conformation (betabeta), in agreement with experimental results. The SALN mutants SAIN, SAVN, SATN, SSIN and MSHV, were also predicted to be potential alpha(r)beta turn-forming peptides. We report also revised positional potentials for the type VIII turn, based on a non-homologous set of protein structures. This protein databank analysis confirms the main results of the earlier analyses and reveals several new amino acid residues with a significant positional preference. The results of this work led us to suggest that the alpha(r)beta turn may be the most common turn type in peptides. Such turns may be readily formed in aqueous solution and thereby play important roles in the protein folding process by serving as an initiation point for structure formation.

Algorithms↗

PubMed2002

Isolation and identification of Aspergillus fumigatus mycotoxins on growth medium and some building materials.

Genotoxic and cytotoxic compounds were isolated and purified from the culture medium of an indoor air mold, Aspergillus fumigatus. One of these compounds was identified as gliotoxin, a known fungal secondary metabolite. Growth of A. fumigatus and gliotoxin production on some building materials were also studied. Strong growth of the mold and the presence of gliotoxin were detected on spruce wood, gypsum board, and chipboard under saturation conditions.

Air Pollutants↗

PubMed2002

Antioxidant and antitumor effects of hydroxymatairesinol (HM-3000, HMR), a lignan isolated from the knots of spruce.

The antioxidant properties of hydroxymatairesinol (HM-3000) were studied in vitro in lipid peroxidation, superoxide and peroxyl radical scavenging, and LDL-oxidation models in comparison with the known synthetic antioxidants Trolox (a water-soluble vitamin E derivative), butylated hydroxyanisol (BHA) and butylated hydroxytoluene (BHT). On a molar basis HM-3000 was a more effective antioxidant than Trolox in all assays and more effective than BHT or BHA in lipid peroxidation and superoxide scavenging test. The in vivo antioxidative effect (evaluated as the weight gain of C57BL/6J mice fed an alpha-tocopherol-deficient diet) of HM-3000 (500 mg/kg per day) was comparable to that of DL-alpha-tocopherol (766 mg/kg per day). The antitumor activity of HM-3000 was studied in dimethylbenz[a]anthracene (DMBA)-induced rat mammary cancer. HM-3000 had a statistically significant inhibitory effect on tumor growth. Prevention of tumor formation was also evaluated in the Apc(Min) mice model, which develops intestinal polyps spontaneously. HM-3000 was given in diet at 30 mg/kg per day and decreased the formation of polyps and prevented beta-catenin accumulation into the nucleus, the pathophysiological hallmark of polyp formation in this mouse model. In short-term toxicity studies (up to 28 days) HM-3000 was essentially non-toxic when given p.o. to rats and dogs (daily doses up to 2000 and 665 mg/kg, respectively); HM-3000 was shown to be well absorbed (> 50% of the dose) and rapidly eliminated. In human studies HM-3000 has been given in single doses up to 1350 mg to healthy male volunteers without treatment-related adverse events. Rapid absorption from the gastrointestinal tract and partial metabolism to enterolactone in humans was demonstrated. In summary, HM-3000 is a safe, novel enterolactone precursor lignan with antioxidant and antitumor properties.

Animals↗

PubMedDate not supplied

Evaluation of a novel electronic eigenvalue (EEVA) molecular descriptor for QSAR/QSPR studies: validation using a benchmark steroid data set.

A novel electronic eigenvalue (EEVA) descriptor of molecular structure for use in the derivation of predictive QSAR/QSPR models is described. Like other spectroscopic QSAR/QSPR descriptors, EEVA is also invariant as to the alignment of the structures concerned. Its performance was tested with respect to the CBG (corticosteroid binding globulin) affinity of 31 benchmark steroids. It appeared that the electronic structure of the steroids, i.e., the "spectra" derived from molecular orbital energies, is directly related to the CBG binding affinities. The predictive ability of EEVA is compared to other QSAR approaches, and its performance is discussed in the context of the Hammett equation. The good performance of EEVA is an indication of the essential quantum mechanical nature of QSAR. The EEVA method is a supplement to conventional 3D QSAR methods, which employ fields or surface properties derived from Coulombic and van der Waals interactions.

Quantitative Structure-Activity Relationship↗

PubMedDate not supplied

FLUFF-BALL, a template-based grid-independent superposition and QSAR technique: validation using a benchmark steroid data set.

The Flexible Ligand Unified Force Field (FLUFF) is a molecular mechanistic superposition algorithm utilizing a template structure, on top of which the ligand(s) are superimposed. FLUFF enables a flexible semiautomatic superimposition in which the ligand and the template are allowed to seek the best common conformation, which can then be used to predict the biological activity by Boundless Adaptive Localized Ligand (BALL). In BALL, the similarity of the electrostatic and van der Waals volumes of the template and ligand is evaluated using the template-based coordinate system which makes the FLUFF-BALL invariant as to the rotations and translations of the global coordinate system. When tested using the CBG (corticosteroid binding globulin) affinities of 31 benchmark steroids, the FLUFF-BALL technique produced results comparable to standard 3D-QSAR methods. Supplementary test calculations were performed with five additional data sets. Due to its high level of automation and high throughput, the FLUFF-BALL is highly suitable for use in drug design and in scanning of large molecular libraries.

Algorithms↗

PubMedDate not supplied

Comparing the performance of FLUFF-BALL to SEAL-CoMFA with a large diverse estrogen data set: from relevant superpositions to solid predictions.

In this work a template-based molecular mechanistic superposition algorithm FLUFF (Flexible Ligand Unified Force Field) and an accompanying local coordinate QSAR method BALL (Boundless Adaptive Localized Ligand) are validated against the benchmark techniques SEAL (Steric and Electrostatic Alignment) and CoMFA (Comparative Molecular Field Analysis) using a large diverse set of 245 xenoestrogens extracted from the EDKB (Endocrine Disruptor Knowledge Base) maintained by NCTR (National Centre for Toxicological Research). The results indicate that FLUFF is capable of generating relevant superpositions not only for BALL but also for CoMFA, as both techniques give predictive QSAR models. When the BALL and CoMFA methods are compared, it is clear that the BALL algorithm met or even exceeded the results of the standard 3D-QSAR method CoMFA using alignments either from the tailor-made superposition technique FLUFF or the reference method SEAL. The FLUFF-BALL method can be easily automated, and it is computationally light, providing thus a good computational "sieve" capable of fast screening of large molecule libraries.

Algorithms↗