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Journal ArticleDOI

In silico toxicity as a tool for harm reduction: A study of new psychoactive amphetamines and cathinones in the context of criminal science.

TL;DR: Computer-calculated toxicity values of various amphetamines and cathinones are submitted to an unsupervised multivariate analysis, namely Principal Component Analysis (PCA), and to the supervised techniques Soft Independent Modeling of Class Analogy and Partial Least Square-Discriminant Analysis to evaluate how these two NPS groups behave.
About: This article is published in Science & Justice.The article was published on 2019-05-01. It has received 3 citations till now. The article focuses on the topics: Poison control.
Citations
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Journal ArticleDOI
TL;DR: In this article , the analytical applicability of single ion-selective membranes (ISMs) and potentiometric sensor array to distinguish and detect cathinone derivatives was demonstrated.
Abstract: This work demonstrates the analytical applicability of single ion-selective membranes (ISMs) and potentiometric sensor array to distinguish and detect cathinone derivatives. Potentiometric data from ISMs based on cation exchanger and varying content of calix[4]arene derivative were processed by principal component analysis (PCA). Such a combination of methods allowed discriminating various individual synthetic cathinones and their recognition from the mixture comprising primary amines (substituted amphetamines+aminoindane). Analytical parameters of ISM containing 1wt % of calix[4]arene derivative were sufficient to detect 1.0×10−4 mol.l−1 1-(4-fluorophenyl)-2-(ethylamino)butan-1-one and 2-(methylamino)-1-phenylbutan-1-one (buphedrone) in both model and saliva samples.

1 citations

References
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Book ChapterDOI
13 Nov 2018

21 citations

Journal ArticleDOI
TL;DR: The present review is intended to critically describe the capabilities of I-Lab service,as well as its limitations and to provide some examples of its use.
Abstract: Introduction. Prediction of the properties and structure of the chemical substances is one of the ultimate goals of Computational Chemistry. Although ab initio and semi-empirical methods are speeding progress toward this goal, for now bench chemists will have to rely on faster and computationally affordable empirical methods to fulfill their practical needs. Many software developers now offer a variety of prediction tools and databases for the chemist with a PC. Unfortunately, substantial cost and reasonable skepticism toward new commercial products may be preventing many practicing chemists from using these software packages. Fortunately, the Internet revolution brings us an alternative. An Internet-based service would give instant access to property prediction programs and databases on known compounds. A user would have the choice to pay-per-prediction or to subscribe to one or more services for a defined period of time. It would be no longer necessary to purchase the software package and install frequent updates. Service could run on virtually any platform and would require comparatively small storage capacity and clock speed. Interactive Laboratory (I-Lab) from ACD Labs (http:// www.acdlabs.com/ilab) is exactly this kind of service. The present review is intended to critically describe the capabilities of I-Lab service,as well as its limitations and to provide some examples of its use. Installation and Capabilities. After opening an account, a user has two options to access the service: Java applet or Windows application. Java applet is available for anyone who uses Netscape 4.5, Internet Explorer 5.0, or any later version. It does not require installation and opens at a click on the web page. I found no technical glitches when testing the service on Linux/Alpha with Netscape 4.73 and on Windows 2000/PIII with IE 5.5, Netscape 4.7, and (my personal favorite) lightweight browser Enigma 3.6. 1 Optionally, the user can download the applet locally for faster start-up, but I did not find this necessary. After a two-dimensional molecular structure is sketched in the applet window it can be idealized, imported to the webpage, and converted into SMILES description. 2 With one click on the menu a request is submitted to the I-Lab server and progress is displayed. During off-peak hours the calculation and download of the results usually takes less than a minute. Network jams during regular business hours made my experience less enjoyable. Windows users have also an option to install ChemSketch. It comes in three parts, which are available for free download …

14 citations

Journal ArticleDOI
TL;DR: Estimation of interaction of drug-like compounds with antitargets is important for the assessment of possible toxic effects during drug development and the creation of (Q)SAR models was created by GUSAR software using quantitative neighborhoods of atoms (QNA), multilevel neighborhoods of atomic descriptors, and self-consistent regression.
Abstract: Estimation of interaction of drug-like compounds with antitargets is important for the assessment of possible toxic effects during drug development. Publicly available online databases provide data on the experimental results of chemical interactions with antitargets, which can be used for the creation of (Q)SAR models. The structures and experimental Ki and IC50 values for compounds tested on the inhibition of 30 antitargets from the ChEMBL 20 database were used. Data sets with Ki and IC50 values including more than 100 compounds were created for each antitarget. The (Q)SAR models were created by GUSAR software using quantitative neighbourhoods of atoms (QNA), multilevel neighbourhoods of atoms (MNA) descriptors and self-consistent regression. The accuracy of (Q)SAR models was validated by the 5-fold cross-validation procedure. The balanced accuracy was higher for qualitative SAR models (0.80 and 0.81 for Ki and IC50 values, respectively) than for quantitative QSAR models (0.73 and 0.76 for Ki and IC50 values, respectively). In most cases sensitivity was higher for SAR models than for QSAR models, but specificity was higher for QSAR models. The mean R2 and RMSE were 0.64 and 0.77 for Ki values and 0.59 and 0.73 for IC50 values, respectively. The number of compounds falling within the applicability domain was higher for SAR models than for the test sets.

14 citations

Journal ArticleDOI
TL;DR: The in silico procedure adopted herein can predict the infrared values and provides valuable information about unknown substances and could help to create an effective tool to identify unknown psychoactive substances.

8 citations

Journal ArticleDOI
TL;DR: In this article, a dataset of three drug classes (acids, bases, and neutrals) with LD50 values in mice was analyzed to investigate a possible connection between high plasma protein binding and acute toxicity.
Abstract: Preclinical Research A dataset of three drug classes (acids, bases, and neutrals) with LD50 values in mice was analysed to investigate a possible connection between high plasma protein binding and acute toxicity. Initially, it was found that high plasma protein binding was associated with toxicity for acids and neutrals, but after compensating for differences in lipophilicity, plasma protein binding was found not to be associated with toxicity. The therapeutic index established by the quotient between mouse LD50 and the defined daily dose was unaffected by both lipophilicity and plasma protein binding.

8 citations