Search results for "Virtual Screening"
showing 10 items of 102 documents
Molecular dynamics, dynamic site mapping, and highthroughput virtual screening on leptin and the Ob receptor as anti-obesity target.
2014
Body weight control is a mechanism finely regulated by several hormonal, metabolic, and nervous pathways. The leptin receptor (Ob-R) is crucial for energy homeostasis and regulation of food uptake. Leptin is a 16 kDa hormone that is mainly secreted by fat cells into the bloodstream, and under normal circumstances, circulating levels are proportionate to the fat body mass. Sensing of elevated leptin levels by the hypothalamic neurocircutry activates a negative feedback loop resulting in reduced food intake and increased energy expenditure. Decreased concentrations lead to opposite effects. Therefore rational design of leptin agonists constitute an appealing challenge in the battle against ob…
Information Theoretic Entropy for Molecular Classification: Oxadiazolamines as Potential Therapeutic Agents
2013
In this review we present algorithms for classification and taxonomy based on information entropy, followed by structure-activity relationship (SAR) models for the inhibition of human prostate carcinoma cell line DU-145 by 26 derivatives of N-aryl-N-(3-aryl-1,2,4-oxadiazol-5-yl)amines (NNAs). The NNAs are classified using two characteristic chemical properties based on different regions of the molecules. A table of periodic properties of inhibitors of DU-145 human prostate carcinoma cell line is obtained based on structural features from the amine moiety and from the oxadiazole ring. Inhibitors in the same group and period of the periodic table are predicted to have highly similar propertie…
An Experimental Toolbox for Structure‐Based Hit Discovery for P. aeruginosa FabF, a Promising Target for Antibiotics
2021
Abstract FabF (3‐oxoacyl‐[acyl‐carrier‐protein] synthase 2), which catalyses the rate limiting condensation reaction in the fatty acid synthesis II pathway, is an attractive target for new antibiotics. Here, we focus on FabF from P. aeruginosa (PaFabF) as antibiotics against this pathogen are urgently needed. To facilitate exploration of this target we have set up an experimental toolbox consisting of binding assays using bio‐layer interferometry (BLI) as well as saturation transfer difference (STD) and WaterLOGSY NMR in addition to robust conditions for structure determination. The suitability of the toolbox to support structure‐based design of FabF inhibitors was demonstrated through the …
Computational Identification of Chemical Compounds with Potential Activity against Leishmania amazonensis using Nonlinear Machine Learning Techniques.
2019
Leishmaniasis is a poverty-related disease endemic in 98 countries worldwide, with morbidity and mortality increasing daily. All currently used first-line and second-line drugs for the treatment of leishmaniasis exhibit several drawbacks including toxicity, high costs and route of administration. Consequently, the development of new treatments for leishmaniasis is a priority in the field of neglected tropical diseases. The aim of this work is to develop computational models those allow the identification of new chemical compounds with potential anti-leishmanial activity. A data set of 116 organic chemicals, assayed against promastigotes of Leishmania amazonensis, is used to develop the the…
Targeting the Class A Carbapenemase GES-5 via Virtual Screening
2020
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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…
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…
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…
Application of molecular topology to the prediction of the antimalarial activity of a group of uracil-based acyclic and deoxyuridine compounds.
2008
A topological-mathematical model has been arranged to search for new derivatives of deoxyuridine and related compounds acting as antimalarials against Plasmodium falciparum. By using linear discriminant and multilinear regression analysis a model with two functions was capable to predict adequately the IC(50) for each compound of the training and test series. After carrying out a virtual screening based upon such a model, new structures potentially active against P. falciparum are proposed.
Efficient virtual screening using multiple protein conformations described as negative images of the ligand-binding site.
2010
The protein structure-based virtual screening is typically accomplished using a molecular docking procedure. However, docking is a fairly slow process that is limited by the available scoring functions that cannot reliably distinguish between active and inactive ligands. In contrast, the ligand-based screening methods that are based on shape similarity identify the active ligands with high accuracy. Here, we show that the usage of negative images of the ligand-binding site, together with shape comparison tools, which are typically used in ligand-based virtual screening, improve the discrimination of active molecules from inactives. In contrast to ligand-based shape comparison, the negative …