Results 261 to 270 of about 114,349,436 (308)
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In silico Prediction of Chemical Ames Mutagenicity
Journal of Chemical Information and Modeling, 2012Mutagenicity is one of the most important end points of toxicity. Due to high cost and laboriousness in experimental tests, it is necessary to develop robust in silico methods to predict chemical mutagenicity. In this paper, a comprehensive database containing 7617 diverse compounds, including 4252 mutagens and 3365 nonmutagens, was constructed. On the
Congying Xu +7 more
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In Silico Prediction of Oral Bioavailability
2007Preclinical predictive models of human oral bioavailability would be of considerable benefit to pharmaceutical product development. Identification of potentially orally bioavailable compounds may assist in candidate selection, or compounds with poor projected bioavailability may be identified early, saving potential late failure and, thus ...
Turner, Joseph +1 more
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In Silico Prediction of Permeability Coefficients
2021In silico simulations of biological systems are of the significant importance to obtain insights on specific processes that experimental protocols have difficulty to elucidate. More particularly, and to ensure that a given molecule is able to reach its cellular target, the development of computational methods able to quickly estimate the cellular ...
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In Silico Prediction of Drug Properties
Current Medicinal Chemistry, 2009Drug design has become inconceivable without the assistance of computer-aided methods. In this context in silico was chosen as designation to emphasize the relationship to in vitro and in vivo testing. Nowadays, virtual screening covers much more than estimation of solubility and oral bioavailability of compounds.
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Comparison of In Silico Models for Prediction of Mutagenicity
Journal of Environmental Science and Health, Part C: Environmental Carcinogenesis and Ecotoxicology Reviews, 2013Using a dataset with more than 6000 compounds, the performance of eight quantitative structure activity relationships (QSAR) models was evaluated: ACD/Tox Suite, Absorption, Distribution, Metabolism, Elimination, and Toxicity of chemical substances (ADMET) predictor, Derek, Toxicity Estimation Software Tool (T.E.S.T.), TOxicity Prediction by Komputer ...
Todd Martin +2 more
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Machine Learning for In Silico ADMET Prediction
2021ADMET (absorption, distribution, metabolism, excretion, and toxicity) describes a drug molecule's pharmacokinetics and pharmacodynamics properties. ADMET profile of a bioactive compound can impact its efficacy and safety. Moreover, efficacy and safety are considered some of the major causes of clinical attrition in the development of new chemical ...
Lei, Jia, Hua, Gao
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In silico prediction of drug toxicity
Journal of Computer-Aided Molecular Design, 2003It is essential, in order to minimise expensive drug failures due to toxicity being found in late development or even in clinical trials, to determine potential toxicity problems as early as possible. In view of the large libraries of compounds now being handled by combinatorial chemistry and high-throughput screening, identification of putative ...
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In Silico Methods for Toxicity Prediction
2012The principles and uses of (Q)SAR models and expert systems for predicting toxicity and the biotransformation of foreign chemicals (xenobiotics) are described and illustrated for some key toxicity endpoints, with examples from the published literature.
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In Silico Prediction of RNA Secondary Structure
2017The secondary structure of an RNA molecule represents the base-pairing interactions within the molecule and fundamentally determines its overall structure. In this chapter, we overview the main approaches and existing tools for predicting RNA secondary structures, as well as methods for identifying noncoding RNAs from genomic sequences or RNA ...
Tahi, Fariza +2 more
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In Silico Target Prediction for Small Molecules
2018Drugs modulate disease states through their actions on targets in the body. Determining these targets aids the focused development of new treatments, and helps to better characterize those already employed. One means of accomplishing this is through the deployment of in silico methodologies, harnessing computational analytical and predictive power to ...
Ryan Byrne, Gisbert Schneider
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