Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: UNIPROT:P06889 (Mol)
 630,302 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Resolution of binary mixtures of vitamin B12, methylcobalamin and B12 coenzyme with minimum sample pre-treatment and without analyte separation has been successfully achieved by methods of partial least squares algorithm with one dependent variable (PLS1), orthogonal signal correction/partial least squares (OSC/PLS), principal component regression (PCR) and hybrid linear analysis (HLA). Data of analysis were obtained from UV-vis spectra. The UV-vis spectra of the vitamin B12, methylcobalamin and B12 coenzyme were recorded in the same spectral conditions. The method of central composite design was used in the ranges of 10-80 mg L(-1) for vitamin B12 and methylcobalamin and 20-130 mg L(-1) for B12 coenzyme. The models refinement procedure and validation were performed by cross-validation. The minimum root mean square error of prediction (RMSEP) was 2.26 mg L(-1) for vitamin B12 with PLS1, 1.33 mg L(-1) for methylcobalamin with OSC/PLS and 3.24 mg L(-1) for B12 coenzyme with HLA techniques. Figures of merit such as selectivity, sensitivity, analytical sensitivity and LOD were determined for three compounds. The procedure was successfully applied to simultaneous determination of three compounds in synthetic mixtures and in a pharmaceutical formulation.
Spectrochim Acta A Mol Biomol Spectrosc 2008 Oct
PMID:Simultaneous determination of vitamin B12 and its derivatives using some of multivariate calibration 1 (MVC1) techniques. 1808 12

The criterion of success for the initial stages of a ligand-based drug-discovery project is dual. First, a set of suitable lead compounds has to be identified. Second, a level of a preliminary structure-activity relationship (SAR) of the identified ligands has to be established in order to guide the lead optimization toward a final drug candidate. This paper presents a combined approach to solving these two problems of ligand-based virtual screening and elucidation of SAR based on interplay between pharmacophore fingerprints and interpretation of PLS-discriminant analysis (PLS-DA) models. The virtual screening capability of the PLS-DA method is compared to group fusion maximum similarity searching in a test using four graph-based pharmacophore fingerprints over a range of 10 diverse targets. The PLS-DA method was generally found to do better than the Smax method. The GpiDAPH3 and PCH fingerprints proved superior to the TGT and TGD fingerprints. Examples of SAR elucidation based on PLS-DA model interpretation of model coefficients using a reversible pharmacophore fingerprint are given. In addition, we tested the hypothesis that feature combinations coming from the analysis of two-dimensional (2D) pharmacophore fingerprints could be used to elucidate a three-dimensional pharmacophore (Williams, C. Mol. Diversity 2006, 10 (3), 311-332). This test was performed by mapping of pharmacophore triplets found by the PLS-DA model to be important for activity onto relevant ligands aligned by the protein-binding site known from X-ray complexes. The result of this analysis assists in explaining the efficiency of 2D pharmacophore fingerprints as descriptors in virtual screening.
 ...
PMID:Combining pharmacophore fingerprints and PLS-discriminant analysis for virtual screening and SAR elucidation. 1828 62

In previous studies we have developed categorical QSAR models for predicting skin-sensitization potency based on 4D-fingerprint (4D-FP) descriptors and in vivo murine local lymph node assay (LLNA) measures. Only 4D-FP derived from the ground state (GMAX) structures of the molecules were used to build the QSAR models. In this study we have generated 4D-FP descriptors from the first excited state (EMAX) structures of the molecules. The GMAX, EMAX and the combined ground and excited state 4D-FP descriptors (GEMAX) were employed in building categorical QSAR models. Logistic regression (LR) and partial least square coupled logistic regression (PLS-CLR), found to be effective model building for the LLNA skin-sensitization measures in our previous studies, were used again in this study. This also permitted comparison of the prior ground state models to those involving first excited state 4D-FP descriptors. Three types of categorical QSAR models were constructed for each of the GMAX, EMAX and GEMAX datasets: a binary model (2-state), an ordinal model (3-state) and a binary-binary model (two-2-state). No significant differences exist among the LR 2-state model constructed for each of the three datasets. However, the PLS-CLR 3-state and 2-state models based on the EMAX and GEMAX datasets have higher predictivity than those constructed using only the GMAX dataset. These EMAX and GMAX categorical models are also more significant and predictive than corresponding models built in our previous QSAR studies of LLNA skin-sensitization measures.
J Comput Aided Mol Des
PMID:Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors. 1833 30

2D and 3D QSAR studies were applied on a set of 28 diarylpyrimidine derivatives to model and understand their HIV-1 reverse transcriptase (RT) inhibitory activities. Special cares were taken to build our set of molecules according to their bioactive conformations which is crucial to elaborate good QSAR models. 2D QSAR was performed using the heuristic method in CODESSA which had led to a linear model (R (2) = 0.928 and s (2) = 0.015) between the inhibitory activity and five descriptors. CoMFA and CoMSIA models were established using SYBYL package of programs. The better predictive ability of the CoMSIA model (q (2) = 0.730) over the CoMFA model (q (2) = 0.597) was assigned to the large contribution of hydrogen-bonding interactions to the inhibitory activity. CoMSIA physicochemical properties are in agreement with the 2D QSAR descriptors. The CoMSIA PLS contour surfaces were mapped to the binding pocket of the RT and showed that the results obtained by the 2D and 3D models are in respect with the protein environment. This link permitted us to validate our model and give important insights for the structure activity interpretations. These results will guide further structural modification and prediction of new HIV-1 RT inhibitors.
J Comput Aided Mol Des 2008 Nov
PMID:2D and 3D QSAR studies of diarylpyrimidine HIV-1 reverse transcriptase inhibitors. 1850 77

A new method orthogonal projection to latent structures (O-PLS) combined with artificial neural networks is investigated for non-destructive determination of Ampicillin powder via near-infrared (NIR) spectroscopy. The modern NIR spectroscopy analysis technique is efficient, simple and non-destructive, which has been used in chemical analysis in diverse fields. Be a preprocessing method, O-PLS provides a way to remove systematic variation from an input data set X not correlated to the response set Y, and does not disturb the correlation between X and Y. In this paper, O-PLS pretreated spectral data was applied to establish the ANN model of Ampicillin powder, in this model, the concentration of Ampicillin as the active component was determined. The degree of approximation was employed as the selective criterion of the optimum network parameters. In order to compare the OPLS-ANN model, the calibration models that using first-derivative and second-derivative preprocessing spectra were also designed. Experimental results showed that the OPLS-ANN model was the best.
Spectrochim Acta A Mol Biomol Spectrosc 2009 Jan
PMID:Orthogonal projection to latent structures combined with artificial neural networks in non-destructive analysis of Ampicillin powder. 1867 96

Comparative molecular surface analysis (CoMSA) with robust IVE-PLS variable elimination if tested for the benchmark CBG steroid series provides highly predictive RI 3D QSAR models, but failed however to model the activity of sulforaphane (SP) activators of quinone reductase. The application of the SP poses obtained from multipose molecular docking to model the RD IVE-PLS CoMSA resulted in a predictive form. This model indicated lipophilic potential as the activity determinant. The individual molecular surface areas of the highest contribution to the SP activity was identified and visualized by CoMSA contour plots.
J Mol Model 2009 Jan
PMID:Receptor independent and receptor dependent CoMSA modeling with IVE-PLS: application to CBG benchmark steroids and reductase activators. 1893 85

A 3D QSAR analysis has been performed on a series of 67 benzodiazepine analogues reported as gamma-secretase inhibitors using molecular field analysis (MFA), with G/PLS to predict steric and electrostatic molecular field interaction for the activity. The MFA study was carried out using a training set of 54 compounds. The predictive ability of model developed was assessed using a test set of 13 compounds (r(2) pred as high as 0.729). The analyzed MFA model has demonstrated a good fit, having r(2) value of 0.858 and cross validated coefficient, r(2)cv value as 0.790. The analysis of the best MFA model provided insight into possible modification of the molecules for better activity.
J Mol Model 2009 Apr
PMID:Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of various benzodiazepine analogues of gamma-secretase inhibitors. 1906

A series of 7-hydroxy, 8-hydroxy and 7,8-dihydroxy synthetic chromone derivatives was evaluated for their DPPH free radical scavenging activities. A training set of 30 synthetic chromone derivatives was subject to three-dimensional quantitative structure-activity relationship (3D-QSAR) studies using molecular field analysis (MFA). The substitutional requirements for favorable antioxidant activity were investigated and a predictive model that could be used for the design of novel antioxidants was derived. Regression analysis was carried out using genetic partial least squares (G/PLS) method. A highly predictive and statistically significant model was generated. The predictive ability of the developed model was assessed using a test set of 5 compounds (r(2) (pred) = 0.924). The analyzed MFA model demonstrated a good fit, having r(2) value of 0.868 and cross-validated coefficient r(2) (cv) value of 0.771.
Int J Mol Sci 2008 Mar
PMID:3D-QSAR investigation of synthetic antioxidant chromone derivatives by molecular field analysis. 1932 46

Quantitative relationships between molecular structure and p56(lck) protein tyrosine kinase inhibitory activity of 50 flavonoid derivatives are discovered by MLR and GA-PLS methods. Different QSAR models revealed that substituent electronic descriptors (SED) parameters have significant impact on protein tyrosine kinase inhibitory activity of the compounds. Between the two statistical methods employed, GA-PLS gave superior results. The resultant GA-PLS model had a high statistical quality (R(2) = 0.74 and Q(2) = 0.61) for predicting the activity of the inhibitors. The models proposed in the present work are more useful in describing QSAR of flavonoid derivatives as p56(lck) protein tyrosine kinase inhibitors than those provided previously.
Int J Mol Sci 2008 Sep
PMID:QSAR study of p56(lck) protein tyrosine kinase inhibitory activity of flavonoid derivatives using MLR and GA-PLS. 1932 36

A series of 3-hydroxypyridine-4-one and 3-hydroxypyran-4-one derivatives were subjected to quantitative structure-antimicrobial activity relationships (QSAR) analysis. A collection of chemometrics methods, including factor analysis-based multiple linear regression (FA-MLR), principal component regression (PCR) and partial least squares combined with genetic algorithm for variable selection (GA-PLS) were employed to make connections between structural parameters and antimicrobial activity. The results revealed the significant role of topological parameters in the antimicrobial activity of the studied compounds against S. aureus and C. albicans. The most significant QSAR model, obtained by GA-PLS, could explain and predict 96% and 91% of variances in the pIC(50) data (compounds tested against S. aureus) and predict 91% and 87% of variances in the pIC(50) data (compounds tested against C. albicans), respectively.
Int J Mol Sci 2008 Dec
PMID:QSAR study of antimicrobial 3-hydroxypyridine-4-one and 3-hydroxypyran-4-one derivatives using different chemometric tools. 1933 84


<< Previous 1 2 3 4 5 6 7 8 9 10 Next >>