Search results for "Quantitative structure"
showing 10 items of 192 documents
2D- and 3D-QSAR Models of Interaction between Flavor Compounds and beta-Lactoglobulin Using Catalyst and Cerius2
2004
The present paper describes an application of Catalyst to three aroma sets (35, 24 and 21 compounds respectively) to generate activities-based alignments, using the best significant generated hypotheses. The obtained Catalyst models confirmed the existence of at least two binding sites on the BLG.
Prediction of potential environmental toxicity of chemicals in <em>Lactuca sativa</em> seed germination using computational tools
2019
The main aim of the study was to develop quantitative structure-activity relationship (QSAR) models for the prediction of phytotoxicity effects of chemical compounds on the Lactuca sativa seeds germination. A database of 73 compounds, assayed against L. sativa and Dragon’s molecular descriptors are used to obtain a QSAR model for the prediction of the phytotoxicity. The model is carried out with QSARINS software and validated according to OECD principles. The best model showed good value for the determination coefficient (R2 = 0.917) and others parameters appropriate for fitting (s = 0.256 and RMSEtr= 0.236). The validation results confirmed that the model has good robustness and stability …
<strong>Predicting Proteasome Inhibition using Atomic Weighted Vector and Machine Learning</strong>
2018
Ubiquitin/Proteasome System (UPS) is a highly regulated mechanism of intracellular protein degradation and turnover. Through the concerted actions of a series of enzymes, proteins are marked for proteasomal degradation by being linked to the polypeptide co-factor, ubiquitin. The UPS participates in a wide array of biological functions such as antigen presentation, regulation of gene transcription and the cell cycle, and activation of NF-κB. Some researchers have applied QSAR method and machine learning in the study of proteasome inhibition (EC50(µmol/L)), such as: the analysis of proteasome inhibition prediction, in the prediction of multi-target inhibitors of UPP and in the prediction of p…
QSAR Analysis of Hypoglycemic Agents Using the Topological Indices
2001
The molecular topology model and discriminant analysis have been applied to the prediction of some pharmacological properties of hypoglycemic drugs using multiple regression equations with their statistical parameters. Regression analysis showed that the molecular topology model predicts these properties. The corresponding stability (cross-validation) studies performed on the selected prediction models confirmed the goodness of the fits. The method used for hypoglycemic 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 selection of new hypoglycemic agents, and we …
Modeling of interactions between xenobiotics and cytochrome P450 (CYP) enzymes
2015
The adverse effects to humans and environment of only few chemicals are well known. Absorption, distribution, metabolism, and excretion (ADME) are the steps of pharmaco/toxicokinetics that determine the internal dose of chemicals to which the organism is exposed. Of all the xenobiotic-metabolizing enzymes, the cytochrome P450 (CYP) enzymes are the most important due to their abundance and versatility. Reactions catalyzed by CYPs usually turn xenobiotics to harmless and excretable metabolites, but sometimes an innocuous xenobiotic is transformed into a toxic metabolite. Data on ADME and toxicity properties of compounds are increasingly generated using in vitro and modeling (in silico) tools.…
Modeling Natural Anti-Inflammatory Compounds by Molecular Topology
2011
One of the main pharmacological problems today in the treatment of chronic inflammation diseases consists of the fact that anti-inflammatory drugs usually exhibit side effects. The natural products offer a great hope in the identification of bioactive lead compounds and their development into drugs for treating inflammatory diseases. Computer-aided drug design has proved to be a very useful tool for discovering new drugs and, specifically, Molecular Topology has become a good technique for such a goal. A topological-mathematical model, obtained by linear discriminant analysis, has been developed for the search of new anti-inflammatory natural compounds. An external validation obtained with …
MADoSPRO: a new approach to molecular modelling studies on a series of DNA minor groove binders
2006
The aim of this work was devoted to develop a method to predict Delta G values for a series of minor groove binders. Starting from a matrix of docking dataset for 10 minor groove binders (known and not) to 20 DNA fragments, with various sequences, it was possible to analyze the interaction modes and to calculate the Delta G value for new derivatives through MADoSPRO procedure. The method allowed, through the QSPR analysis, to characterize the type of interactions in such complexes, that was demonstrated to be related to quantum chemical and electrostatic descriptors, in agreement with the information available in literature on the structural requirements of specific minor groove ligands. Mo…
A Multivariate Analysis of HIV-1 Protease Inhibitors and Resistance Induced by Mutation
2005
This paper describes the use of the multivariate statistical procedure principal component analysis as a tool to explore the inhibitory activity of classes of protease inhibitors (PIs) against HIV-1 viruses (wild type and more-frequent single mutants, V82A, V82F, and I84V) and against protease enzymes. The analysis of correlations between biological activity and molecular descriptors or similarity indexes allowed a reliable classification of the 51 derivatives considered in this study. The best results were obtained in the case of the I84V mutant for which a high number of predictions was achieved. On this basis, this statistical approach is proposed as a reliable method for the prediction …
Artificial neural network applied to the discrimination of antibacterial activity by topological methods
2000
Abstract A new topological method that makes it possible to discriminate the active and inactive molecules on the basis of their chemical structures is applied in the present study to the antibacterial agents. This method uses neural networks in which training algorithms are used as well as different concepts and methods of artificial intelligence with a suitable set of topological descriptors. It is possible to obtain a QSAR interpretation of the information contained in the network after the training has been carried out.
<strong>New tool useful for drug discovery validated through benchmark datasets</strong>
2018
Atomic Weighted Vectors (AWVs) are vectors that contain the codified information of molecular structures, which can apply to a set of Aggregation Operators (AOs) to calculate total and local molecular descriptors (MDs). This article presents an exploratory study of a new tool useful for drug discovery using different datasets, such as DRAGON and Sutherland’s datasets, as well as their comparison with other well-known approaches. In order to evaluate the performance of the tool, several statistics and QSAR/QSPR experiments were performed. Variability analyses are used to quantify the information content of the AWVs obtained from the tool, by the way of an information theory-based algorithm. …