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Query: UNIPROT:P06889 (Mol)
 630,302 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Quantitative structure-activity analysis was carried out for in vitro inhibition of rat brain soluble catechol O-methyltransferase by a series (N = 99) of 1,5-substituted-3,4-dihydroxybenzenes using computational chemistry and multivariate PLS modelling of data sets. The molecular structural descriptors (N = 19) associated with the electronics of the catecholic ring and sizes of substituents were derived theoretically. For the whole set of molecules two separate PLS models have to be used. A PLS model with two significant (crossvalidated) model dimensions describing 82.2% of the variance in inhibition activity data was capable of predicting all molecules except those having the largest R1 substituent or having a large R5 substituent compared to the NO2 group. The other PLS model with three significant (crossvalidated) model dimensions described 83.3% of the variance in inhibition activity data. This model could not handle compounds having a small R5 substituent, compared to the NO2 group, or the largest R1 substituent. The predictive capability of these PLS models was good. The models reveal that inhibition activity is nonlinearly related to the size of the R5 substituent. The analysis of the PLS models also shows that the binding affinity is greatly dependent on the electronic nature of both R1 and R5 substituents. The electron-withdrawing nature of the substituents enhances inhibition activity. In addition, the size of the R1 substituent and its lipophilicity are important in the binding of inhibitors. The size of the R1 substituent has an upper limit. On the other hand, ionized R1 substituents decrease inhibition activity.
J Comput Aided Mol Des 1992 Jun
PMID:PLS modelling of structure-activity relationships of catechol O-methyltransferase inhibitors. 151 77

An experimental design based 3-D QSAR analysis using a combination of principal component and PLS analysis is presented and applied to human corticosteroid-binding globulin complexes. The predictive capability of the created model is good. The technique can also be used as guidance when selecting new compounds to be investigated.
J Comput Aided Mol Des 1990 Dec
PMID:Experimental design based 3-D QSAR analysis of steroid-protein interactions: application to human CBG complexes. 209 83

In this study we confirmed that combinations of toxic or detoxified endotoxin with muramyl dipeptide (MDP) induced much more necrosis of transplanted Meth A sarcoma in mice than toxic endotoxin alone. Detoxified endotoxin and MDP alone had little antitumor effects. We investigated whether these divergent antitumor effects could be related to histopathological changes in the white pulp of the spleen of Meth A sarcoma-bearing mice. Toxic endotoxin reduced the T:B cell compartment ratio in the splenic white pulp by increasing the size of the B-cell compartment while leaving the size of the T-cell dependent inner PALS unaffected. The number of the T-lymphocytes in this area, however, was reduced. The border of B-lymphocytes in the marginal zone was markedly narrowed and the number of marginal metallophils along the inner border of the marginal sinus was decreased. None of these changes were observed after treatment with detoxified endotoxin or MDP. Addition of MDP to either endotoxin did not change their effects. The histopathological changes in the lymphoid and non-lymphoid compartments of the splenic white pulp are apparently exclusively induced by toxic endotoxin. As the antitumor activity of both toxic and detoxified endotoxin combined with MDP are about equal and more powerful than the activity of toxic endotoxin alone, it is concluded that these antitumor effects cannot be related to changes in the white pulp of the spleen.
Virchows Arch B Cell Pathol Incl Mol Pathol 1986
PMID:In vivo effects of toxic and detoxified endotoxin alone or in combination with muramyl dipeptide on lymphoid and non-lymphoid cells in the spleen of Meth A sarcoma-bearing mice. 287 59

The steric descriptors commonly used in CoMFA--Lennard-Jones 6-12 potential-derived interaction energies calculated between a probe atom and the molecules under investigation--have been replaced by variables indicating the presence of an atom of a particular molecule in predefined volume elements (cubes) within the region enclosing the ensemble of superimposed molecules. The resulting 'atom indicator vectors' were used as steric fields in the subsequent PLS analyses, with and without inclusion of electrostatic Coulomb interaction-derived fields. Application of this method to five training sets (80 compounds each) and five test sets (60 compounds each), randomly selected from an ensemble of 256 dihydrofolate reductase inhibitors, leads to models of significantly higher consistency, as indicated by the cross-validated r2 values for the training sets and the predictive r2 values for the test sets.
J Comput Aided Mol Des 1995 Jun
PMID:Replacement of steric 6-12 potential-derived interaction energies by atom-based indicator variables in CoMFA leads to models of higher consistency. 756 73

Ten endogenous steroid hormones and metabolites were determined according to the screening procedure for anabolic steroids in spot urine samples from 105 healthy young male athletes (control samples) and 23 males that tested positive for anabolic steroids in the doping control (positive samples). The GC-MS peak areas for each sample were normalized to total area. Multivariate data analysis by Partial Least Square Regression (PLSR) and using a coded Y-variable (positive samples: +1 and control samples -1) allows projection of the most systematic profile structures into a 2D plot revealing a clear distinction between the control and misuser groups. The most important determinants of the location in the loading plot were the ratios of testosterone to epitestosterone and androsterone to etiocholanolone. The ratio between 11-beta-hydroxyandrosterone and 11-beta-hydroxy-etiocholanolone was less important, in accordance with the fact that anabolic-androgenic steroid intake primarily affects the excretion of testosterone from the testis and to a much lesser degree adrenal steroid genesis. We present a preliminary validation of this model (PLS1-DISCRIM) for analysing steroid profiles in doping control samples from several categories of athletes, some of which are suspected for drug misuse, and results from a one dose excretion study in healthy volunteers. Our findings suggest that use of multivariate PLS-regression may give valuable information about anabolic androgenic steroid misuse in sport. When appropriately calibrated, this methodology may delineate drug misusers directly from the screening procedure for anabolic steroids in spot urine tests.
J Steroid Biochem Mol Biol 1995 Jul
PMID:Chemometric evaluation of urinary steroid profiles in doping control. 763 20

Quantitative structure-activity relationships (QSARs) for 16 azoxy compounds with antifungal activity have been studied by the combined approach of a partial least-squares method and factorial design. The PLS model equation suggested the structural requirements of two substituents. R1 and R2, for the antifungal activity. The sterically bulky and hydrophobic R1 substituents and electron-withdrawing R2 substituents are favorable for the activity. We propose candidate compounds which are more potent than the compounds based on QSAR data. In this study, we show that the chemometric approach is a powerful tool for QSAR studies and drug design.
J Comput Aided Mol Des 1994 Aug
PMID:Chemometric QSAR studies of antifungal azoxy compounds. 781 96

A series of non-peptide angiotensin II receptor antagonists was investigated with the aim of developing a 3D QSAR model using comparative molecular field analysis descriptors and approaches. The main goals of the study were dictated by an interest in methodologies and an understanding of the binding requirements to the AT1 receptor. Consistency with the previously derived activity models was always checked to contemporarily test the validity of the various hypotheses. The specific conformations chosen for the study, the procedures invoked to superimpose all structures, the conditions employed to generate steric and electrostatic field values and the various PCA/PLS runs are discussed in detail. The effect of experimental design techniques to select objects (molecules) and variables (descriptors) with respect to the predictive power of the QSAR models derived was especially analysed.
J Comput Aided Mol Des 1996 Dec
PMID:A 3D QSAR CoMFA study of non-peptide angiotensin II receptor antagonists. 900 90

Recently, the multilinear PLS algorithm was presented by Bro and later implemented as a regression method in 3D QSAR by Nilsson et al. In the present article a well-known set of (S)-N-[(1-ethyl-2-pyrrolidinyl)methyl]-6-methoxybenzamides, with affinity towards the dopamine D2 receptor subtype, was utilised for the validation of the multilinear PLS method. After exhaustive conformational analyses on the ligands, the active analogue approach was employed to align them in their presumed pharmacologically active conformations, using (-)-piquindone as a template. Descriptors were then generated in the GRID program, and 40 calibration compounds and 18 test compounds were selected by means of a principal component analysis in the descriptor space. The final model was validated with different types of cross-validation experiments, e.g. leave-one-out, leave-three-out and leave-five-out. The cross-validated Q2 was 62% for all experiments, confirming the stability of the model. The prediction of the test set with a predicted Q2 of 62% also established the predictive ability. Finally, the conformations and the alignment of the ligands in combination with multilinear PLS, obviously, played an important role for the success of our model.
J Comput Aided Mol Des 1998 Jan
PMID:A multiway 3D QSAR analysis of a series of (S)-N-[(1-ethyl-2-pyrrolidinyl)methyl]-6-methoxybenzamides. 957 91

Comparative molecular field analysis has been applied to a data set of thermolysin inhibitors. Fields expressed in terms of molecular similarity indices (CoMSIA) have been used instead of the usually applied Lennard-Jones- and Coulomb-type potentials (CoMFA). Five different properties, assumed to cover the major contributions responsible for ligand binding, have been considered: steric, electrostatic, hydrophobic, and hydrogen-bond donor or acceptor properties. The statistical evaluation of the field properties by PLS analysis reveals a similar predictive potential to CoMFA. However, significantly improved and easily interpretable contour maps are obtained. The features in these maps intuitively suggest where to modify a molecular structure in terms of physicochemical properties and functional groups in order to improve its binding affinity. They can also be interpreted with respect to the known structural protein environment of thermolysin. Most of the highlighted regions in the maps are mirrored by features in the surrounding environment required for binding. Using the derived correlation model, different members of a combinatorial library designed for thermolysin inhibition have been scored for affinity. The results obtained demonstrate the prediction power of the CoMSIA method.
J Comput Aided Mol Des 1999 Jan
PMID:Comparative molecular similarity index analysis (CoMSIA) to study hydrogen-bonding properties and to score combinatorial libraries. 1008 95

The EVA structural descriptor, based upon calculated fundamental molecular vibrational frequencies, has proved to be an effective descriptor for both QSAR and database similarity calculations. The descriptor is sensitive to 3D structure but has an advantage over field-based 3D-QSAR methods inasmuch as structural superposition is not required. The original technique involves a standardisation method wherein uniform Gaussians of fixed standard deviation (sigma) are used to smear out frequencies projected onto a linear scale. The smearing function permits the overlap of proximal frequencies and thence the extraction of a fixed dimensional descriptor regardless of the number and precise values of the frequencies. It is proposed here that there exist optimal localised values of sigma in different spectral regions; that is, the overlap of frequencies using uniform Gaussians may, at certain points in the spectrum, either be insufficient to pick up relationships where they exist or mix up information to such an extent that significant correlations are obscured by noise. A genetic algorithm is used to search for optimal localised sigma values using crossvalidated PLS regression scores as the fitness score to be optimised. The resultant models were then validated against a previously unseen test set of compounds and through data scrambling. The performance of EVA_GA is compared to that of EVA and analogous CoMFA studies; in the latter case a brief evaluation is made of the effect of grid resolution upon the stability of CoMFA PLS scores particularly in relation to test set predictions.
J Comput Aided Mol Des 2000 Jan
PMID:Evaluation of the EVA descriptor for QSAR studies: 3. The use of a genetic algorithm to search for models with enhanced predictive properties (EVA_GA). 1070 22


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