Search results for "structure-activity relationship"
showing 10 items of 743 documents
Discrimination and selection of new potential antibacterial compounds using simple topological descriptors.
2003
Abstract The aim of the work was to discriminate between antibacterial and non-antibacterial drugs by topological methods and to select new potential antibacterial agents from among new structures. The method used for antibacterial activity selection was a linear discriminant analysis (LDA). It is possible to obtain a QSAR interpretation of the information contained in the discriminant function. We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and selection of new antibacterial agents.
TOMOCOMD-CARDD descriptors-based virtual screening of tyrosinase inhibitors: evaluation of different classification model combinations using bond-bas…
2006
Abstract A new set of bond-level molecular descriptors (bond-based linear indices) are used here in QSAR (quantitative structure–activity relationship) studies of tyrosinase inhibitors, for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones. A database of 246 compounds was collected for this study; all organic chemicals were reported as tyrosinase inhibitors; they had great structural diversity. This dataset can be considered as a helpful tool, not only for theoretical chemists but also for other researchers in this area. The set used as inactive has 412 drugs with other clinical uses. Twelve LDA-based QSAR models were obtained, the first six us…
Structural, chemical topological, electrotopological and electronic structure hypotheses.
2003
The first important hypothesis in the prediction of properties of synthesized molecules is the structural hypothesis. In the study of drug-receptor interactions, the case where the three-dimensional structure of the receptor is known allows the application of molecular simulation and energy calculations to estimate the binding affinity for a proposed series of compounds. The chemical topological hypothesis permits the description of molecular structures without using concepts such as force or energy. These notions would not be as dominant as supposed since they should be able to be deduced from topology. Although topological descriptors are able to describe specific physicochemical properti…
A3 adenosine receptor: Homology modeling and 3D-QSAR studies
2012
Adenosine receptors (AR) belong to the superfamily of G-protein-coupled receptors (GPCRs). They are divided into four subtypes (A1, A2A, A2B, and A3) [1], and can be distinguished on the basis of their distinct molecular structures, distinct tissues distribution, and selectivity for adenosine analogs [2,3]. The hA3R, the most recently identified adenosine receptor, is involved in a variety of intracellular signaling pathways and physiological functions [4]. Expression of A3R was reported to be elevated in cancerous tissues [5], and A3 antagonists have been proposed for therapeutic treatments of cancer. The recent literature availability of crystal structure of hA2A adenosine receptor (PDB c…
IKK-β inhibitors: An analysis of drug–receptor interaction by using Molecular Docking and Pharmacophore 3D-QSAR approaches
2010
Abstract The IKK kinases family represents a thrilling area of research because of its importance in regulating the activity of NF-kB transcription factors. The discovery of the central role played by IKK-β in the activation of transcription in response to apoptotic or inflammatory stimuli allowed to considerate its modulation as a promising tool for the treatment of chronic inflammation and cancer. To date, several IKK-β inhibitors have been discovered and tested. In this work, an analysis of the interactions between different classes of inhibitors and their biological target was performed, through the application of Molecular Docking and Pharmacophore/3D-QSAR approaches to a set of 141 in…
Latest advances in molecular topology applications for drug discovery
2015
Molecular topology (MT) has emerged in recent years as a powerful approach for the in silico generation of new drugs. In the last decade, its application has become more and more popular among the leading research groups in the field of quantitative structure-activity relationships (QSAR) and drug design. This has, in turn, contributed to the rapid development of new techniques and applications of MT in QSAR studies, as well as the introduction of new topological indices.This review collates the main innovative techniques in the field of MT and provides a description of the novel topological indices recently introduced, through an exhaustive recompilation of the most significant works carri…
Non-stochastic quadratic fingerprints and LDA-based QSAR models in hit and lead generation through virtual screening: theoretical and experimental as…
2005
In order to explore the ability of non-stochastic quadratic indices to encode chemical information in antimalarials, four quantitative models for the discrimination of compounds having this property were generated and statistically compared. Accuracies of 90.2% and 83.3% for the training and test sets, respectively, were observed for the best of all the models, which included non-stochastic quadratic fingerprints weighted with Pauling electronegativities. With a comparative purpose and as a second validation experiment, an exercise of virtual screening of 65 already-reported antimalarials was carried out. Finally, 17 new compounds were classified as either active/inactive ones and experimen…
On the contribution of molecular topology to drug design and discovery.
2010
Abstract The role of molecular topology (MT) in the design and selection of new drugs is discussed. After an overview of the different in silico molecular design current technologies, the QSAR analysis is dealt in detail with particular emphasis in the use of topological indices as molecular descriptors. The results of the application of MT in drug design and discovery are described and finally a possible explanation is given about some of the key reasons explaining it's the extraordinary performance.
Advances in the molecular modeling and quantitative structure–activity relationship-based design for antihistamines
2013
Nowadays the use of antihistamines (AH) is increasing steadily. These drugs are able to act on a variety of pathological conditions of the organism. A number of computer-aided (in silico) approaches have been developed to discover and develop novel AH drugs. Among these methods stand the ones based on drug-receptor docking, thermodynamics, as well as the quantitative structure-activity relationships (QSAR).This review collates the most recent advances in the use of computer approaches for the search and characterization of novel AH drugs. Within the QSAR methods, particular attention will be paid to those based on molecular topology (MT) because of their demonstrated efficacy in discovering…
Computational Methods in Developing Quantitative Structure-Activity Relationships (QSAR): A Review
2006
Virtual filtering and screening of combinatorial libraries have recently gained attention as methods complementing the high-throughput screening and combinatorial chemistry. These chemoinformatic techniques rely heavily on quantitative structure-activity relationship (QSAR) analysis, a field with established methodology and successful history. In this review, we discuss the computational methods for building QSAR models. We start with outlining their usefulness in high-throughput screening and identifying the general scheme of a QSAR model. Following, we focus on the methodologies in constructing three main components of QSAR model, namely the methods for describing the molecular structure …