Search results for "Structure-Activity Relationship"
showing 10 items of 743 documents
Chromatographic evaluation of the toxicity in fish of pesticides
2004
Abstract Ecotoxicity assessment is essential before placing new chemical substances on the market. An investigation of the use of the chromatographic retention (log k) in biopartitioning micellar chromatography (BMC) as an in vitro approach to evaluate the toxicity in fish of pesticides (acute toxicity levels as pLC50) is proposed. A heterogeneous data set of 85 pesticides from six chemical families with available experimental fish toxicity data (ECOTOX database from U.S. Environmental Protection Agency (EPA)) was used. For pesticides exhibiting non-polar narcosis mechanism in fish (non-specific toxicity), more reliable models and precise pLC50 estimations are obtained from log k (quantitat…
Antiprotozoan lead discovery by aligning dry and wet screening: Prediction, synthesis, and biological assay of novel quinoxalinones
2014
Protozoan parasites have been one of the most significant public health problems for centuries and several human infections caused by them have massive global impact. Most of the current drugs used to treat these illnesses have been used for decades and have many limitations such as the emergence of drug resistance, severe side-effects, low-to-medium drug efficacy, administration routes, cost, etc. These drugs have been largely neglected as models for drug development because they are majorly used in countries with limited resources and as a consequence with scarce marketing possibilities. Nowadays, there is a pressing need to identify and develop new drug-based antiprotozoan therapies. In …
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 …
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…
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…
QSAR multi-target in drug discovery: a review.
2013
The main purpose of the present review is to summarize the most significant works up to date in the field of multi-target QSAR (mt-QSAR), in order to emphasize the importance that this technique has acquired over the last decade. Unlike traditional QSAR techniques, mt-QSAR permits to calculate the probability of activity of a given compound against different biological or pharmacological targets. In simple terms, a single equation for multiple outputs. To emphasize more the importance of the mt-QSAR in the field of drug discovery, we also present a novel mt-QSAR model, made on purpose by our research group, for the prediction of the susceptibility of Gram + and Gram - anaerobic bacteria.
Event-based criteria in GT-STAF information indices: theory, exploratory diversity analysis and QSPR applications
2012
Versatile event-based approaches for the definition of novel information theory-based indices (IFIs) are presented. An event in this context is the criterion followed in the "discovery" of molecular substructures, which in turn serve as basis for the construction of the generalized incidence and relations frequency matrices, Q and F, respectively. From the resultant F, Shannon's, mutual, conditional and joint entropy-based IFIs are computed. In previous reports, an event named connected subgraphs was presented. The present study is an extension of this notion, in which we introduce other events, namely: terminal paths, vertex path incidence, quantum subgraphs, walks of length k, Sach's subg…