In silico toxicity as a tool for harm reduction: A study of new psychoactive amphetamines and cathinones in the context of criminal science. Issue 3 (May 2019)
- Record Type:
- Journal Article
- Title:
- In silico toxicity as a tool for harm reduction: A study of new psychoactive amphetamines and cathinones in the context of criminal science. Issue 3 (May 2019)
- Main Title:
- In silico toxicity as a tool for harm reduction: A study of new psychoactive amphetamines and cathinones in the context of criminal science
- Authors:
- Rodrigues, Caio Henrique Pinke
Bruni, Aline Thaís - Abstract:
- Abstract: The emergence of new psychoactive substances (NPS) has raised many issues in the context of law enforcement and public drug policies. In this scenario, interdisciplinary studies are crucial to the decision-making process in the field of criminal science. Unfortunately, information about how NPS affect people's health is lacking even though knowledge about the toxic potential of these substances is essential: the more information about these drugs, the greater the possibility of avoiding damage within the scope of a harm reduction policy. Traditional analytical methods may be inaccessible in the field of forensic science because they are relatively expensive and time-consuming. In this sense, less costly and faster in silico methodologies can be useful strategies. In this work, we submitted computer-calculated toxicity values of various amphetamines and cathinones 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 (SIMCA and PLS-DA) to evaluate how these two NPS groups behave. We studied how theoretical and experimental values are correlated by PLS regression. Although experimental data was available for a small amount of molecules, correlation values reproduced literature values. The in silico method efficiently provided information about the drugs. On the basis of our findings, the technical informationAbstract: The emergence of new psychoactive substances (NPS) has raised many issues in the context of law enforcement and public drug policies. In this scenario, interdisciplinary studies are crucial to the decision-making process in the field of criminal science. Unfortunately, information about how NPS affect people's health is lacking even though knowledge about the toxic potential of these substances is essential: the more information about these drugs, the greater the possibility of avoiding damage within the scope of a harm reduction policy. Traditional analytical methods may be inaccessible in the field of forensic science because they are relatively expensive and time-consuming. In this sense, less costly and faster in silico methodologies can be useful strategies. In this work, we submitted computer-calculated toxicity values of various amphetamines and cathinones 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 (SIMCA and PLS-DA) to evaluate how these two NPS groups behave. We studied how theoretical and experimental values are correlated by PLS regression. Although experimental data was available for a small amount of molecules, correlation values reproduced literature values. The in silico method efficiently provided information about the drugs. On the basis of our findings, the technical information presented here can be used in decision-making regarding harm reduction policies and help to fulfill the objectives of criminal science. Highlights: We calculate in silico toxicity for amphetamines and cathinones. Multivariate classification was used to evaluate data. In silico calculations were able to foresee the experimental behavior. This study has potential to be used in drug policies and contemplates the interdisciplinarity required by crime sciences. … (more)
- Is Part Of:
- Science & justice. Volume 59:Issue 3(2019)
- Journal:
- Science & justice
- Issue:
- Volume 59:Issue 3(2019)
- Issue Display:
- Volume 59, Issue 3 (2019)
- Year:
- 2019
- Volume:
- 59
- Issue:
- 3
- Issue Sort Value:
- 2019-0059-0003-0000
- Page Start:
- 234
- Page End:
- 247
- Publication Date:
- 2019-05
- Subjects:
- 4-MEC 4-Methylethcathinone -- ADMET Absorption, Distribution, Metabolism, Excretion, and Toxicity -- BZP Benzylpiperazine -- DAT Dopamine transporter -- GHB Gama-Hydroxybutyrate -- IC50 Concentration needed to inhibit 50% of a biological process -- LD50 Lethal Dose for 50% of the tested subjects -- LogD Distribution coefficient -- LogP Lipophilicity Coefficient -- MDPBP 3', 4'-Methylenedioxy-α-pyrrolidinobutyrophenone -- MDPV 3, 4-Methylenedioxypyrovalerone -- NET Norepinephrine transporter -- NPS New psychoactive substances -- OECD (Organization for Economic Co-operation and Development) -- PCA Principal Component Analysis -- pFPP para-Fluorophenylpiperazine -- PLS-DA Partial Least Square-Discriminant Analysis -- SERT Serotonin transporter -- SIMCA Soft Independent Modeling of Class Analogy -- TFMPP 3-Trifluoromethylphenylpiperazine
Forensic sciences -- Periodicals
Criminal investigation -- Periodicals
Forensic Medicine -- Periodicals
Jurisprudence -- Periodicals
Criminalistique -- Périodiques
Enquêtes criminelles -- Périodiques
Criminal investigation
Forensic sciences
Electronic journals
Periodicals
363.2505 - Journal URLs:
- http://www.forensic-science-society.org.uk/jnltop.html ↗
http://www.sciencedirect.com/science/journal/13550306 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/13550306 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/13550306 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.scijus.2018.11.006 ↗
- Languages:
- English
- ISSNs:
- 1355-0306
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8134.129500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11610.xml