Search results for "Quantitative structure–activity relationship"
showing 10 items of 158 documents
Atom-based 3D-chiral quadratic indices. Part 2: prediction of the corticosteroid-binding globulinbinding affinity of the 31 benchmark steroids data s…
2005
A quantitative structure-activity relationship (QSAR) study to predict the relative affinities of the steroid 'benchmark' data set to the corticosteroid-binding globulin (CBG) is described. It is shown that the 3D-chiral quadratic indices closely correlate with the measured CBG affinity values for the 31 steroids. The calculated descriptors were correlated with biological data through multiple linear regressions. Two statistically significant models were obtained when non-stochastic (R = 0.924 and s = 0.46) as well as stochastic (R = 0.929 and s = 0.46) 3D-chiral quadratic indices were used. A leave-one-out (LOO) approach to model validation is used here; the best results obtained in the cr…
Protein linear indices of the ‘macromolecular pseudograph α-carbon atom adjacency matrix’ in bioinformatics. Part 1: Prediction of protein stability …
2005
Abstract A novel approach to bio-macromolecular design from a linear algebra point of view is introduced. A protein’s total (whole protein) and local (one or more amino acid) linear indices are a new set of bio-macromolecular descriptors of relevance to protein QSAR/QSPR studies. These amino-acid level biochemical descriptors are based on the calculation of linear maps on R n [ f k ( x m i ) : R n → R n ] in canonical basis. These bio-macromolecular indices are calculated from the kth power of the macromolecular pseudograph α-carbon atom adjacency matrix. Total linear indices are linear functional on R n . That is, the kth total linear indices are linear maps from R n to the scalar R [ f k …
New qsar models for polyhalogenated aromatics
1994
Electronic properties of polychlorinated dibenzo p dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), polychlorinated biphenyls (PCBs), and polychlorinated diphenyl ethers (PCDEs) were calculated using the semi-empirical AM1 method The calculated electronic descriptors — the energy of the lowest unoccupied molecular orbital (ELUMO), the energy of the highest occupied molecular orbital (EHOMO), the ELUMO-EHOMO gap (dE), and molecular polarizability — are related to the Ah receptor binding affinity values of PCDDs, PCDFs, and PCBs and immunotoxicity values for PCDEs The quantitative structure activity relationships (QSARs) based on chlorine substitution patterns were also constructed, an…
New set of 2D/3D thermodynamic indices for proteins. A formalism based on "Molten Globule" theory
2010
Abstract We define eight new macromolecular indices, and several related descriptors for proteins. The coarse grained methodology used for its deduction ensures its fast execution and becomes a powerful potential tool to explore large databases of protein structures. The indices are intended for stability studies, predicting Φ -values, predicting folding rate constants, protein QSAR/QSPR as well as protein alignment studies. Also, these indices could be used as scoring function in protein-protein docking or 3D protein structure prediction algorithms and any others applications which need a numerical code for proteins and/or residues from 2D or 3D format.
Discrimination and Molecular Design of New Theoretical Hypolipaemic Agents Using the Molecular Connectivity Functions
2000
The molecular topology model and discriminant analysis have been applied to the prediction and QSAR interpretation of some pharmacological properties of hypolipaemic drugs using multivariable regression equations with their statistical parameters. Regression analysis showed that the molecular topology model predicts these properties. The corresponding stability (cross-validation) studies done on the selected prediction models confirmed the goodness of the fits. The method used for hypolipaemic activity selection was a linear discriminant analysis (LDA). We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and design of new hypolip…
QSAR methods for the discovery of new inflammatory bowel disease drugs
2013
Inflammatory bowel disease (IBD) represents an important class of chronic gastrointestinal tract disease. And although there are already several useful treatments to reduce and control the symptoms, there is still no cure. One drug discovery technique used is the computer-aided (in silico) discovery approach which has largely demonstrated efficacy. Computational techniques, when used in combination with traditional drug discovery methodology, greatly increase the chance of drug discovery in a sustainable and economical fashion.This review aims to provide the most recent and important advances of in silico IBD drug discovery. While this review is mainly focused on QSAR methods, especially th…
Predicting antitrichomonal activity: A computational screening using atom-based bilinear indices and experimental proofs
2006
Existing Trichomonas vaginalis therapies are out of reach for most trichomoniasis people in developing countries and, where available, they are limited by their toxicity (mainly in pregnant women) and their cost. New antitrichomonal agents are needed to combat emerging metronidazole-resistant trichomoniasis and reduce the side effects associated with currently available drugs. Toward this end, atom-based bilinear indices, a new TOMOCOMD-CARDD molecular descriptor, and linear discriminant analysis (LDA) were used to discover novel, potent, and non-toxic lead trichomonacidal chemicals. Two discriminant functions were obtained with the use of non-stochastic and stochastic atom-type bilinear in…
Dragon method for finding novel tyrosinase inhibitors: Biosilico identification and experimental in vitro assays
2006
QSAR (quantitative structure-activity relationship) studies of tyrosinase inhibitors employing Dragon descriptors and linear discriminant analysis (LDA) are presented here. A data set of 653 compounds, 245 with tyrosinase inhibitory activity and 408 having other clinical uses were used. The active data set was processed by k-means cluster analysis in order to design training and prediction series. Seven LDA-based QSAR models were obtained. The discriminant functions applied showed a globally good classification of 99.79% for the best model Class=-96.067+1.988 x 10(2)X0Av +9 1.907 BIC3 + 6.853 CIC1 in the training set. External validation processes to assess the robustness and predictive pow…
Multi-target QSPR assemble of a Complex Network for the distribution of chemicals to biphasic systems and biological tissues
2008
Abstract Chemometrics, that based prediction on the probability of chemical distribution to different systems, is highly important for physicochemical, environmental, and life sciences. However, the amount of information is huge and difficult to analyze. A multi-system partition Complex Network (MSP-CN) may be very useful in this sense. We define MSP-CNs as large graphs composed by nodes (chemicals) interconnected by arcs if a pair of chemicals have similar partition in a given system. Experimental quantification of partition in many systems is expensive, so we can use a Quantitative Structure–Partition Relationship (QSPR) model. Unfortunately, with classic QSPR we need to use one model for…
Molecular topology as a novel approach for drug discovery
2012
Molecular topology (MT) has emerged in recent years as a powerful approach for the in silico generation of new drugs. One key part of MT is that, in the process of drug design/discovery, there is no need for an explicit knowledge of a drug's mechanism of action unlike other drug discovery methods.In this review, the authors introduce the topic by explaining briefly the most common methodology used today in drug design/discovery and address the most important concepts of MT and the methodology followed (QSAR equations, LDA, etc.). Furthermore, the significant results achieved, from this approach, are outlined and discussed.The results outlined herein can be explained by considering that MT r…