From linked open data to molecular interaction: studying selectivity trends for ligands of the human serotonin and dopamine transporter

Zdrazil, Barbara; Hellsberg, Eva; Viereck, Michael; Ecker, Gerhard

doi:10.1039/c6md00207b

Cited by 11 publications

(13 citation statements)

References 52 publications

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“…This example shows the impact of substituting various functional groups at different positions on existing cathinone molecular scaffolds. For example, four types of chemical scaffold for cathinones were identified by Zdrazil, Hellsberg, Viereck, and Ecker () highlighting structural variations including substituents of the nitrogen atom, the aromatic ring and the keto group carbon. These variations have been shown to affect selectivity at DAT and SERT (Figure ; Zdrazil et al, ).…”

Section: Resultsmentioning

confidence: 99%

Intended and unintended use of cathinone mixtures

Guirguis

Corkery

Stair

et al. 2017

Human Psychopharmacology

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Introduction Cathinones are one of the most popular categories of new psychoactive substances (NPS) consumed. Cathinones have different pharmacological activities and receptor selectivity for monoamine transporters based on their chemical structures. They are incorporated into NPS mixtures and used with other NPS or ‘traditional’ drugs. Cathinone use represents significant health risks to individuals and is a public health burden. Methods Evidence of poly‐NPS use with cathinones, seizure information, and literature analyses results on NPS mixtures was systematically gathered from online database sources, including Google Scholar, Scopus, Bluelight, and Drugs‐Forum. Results and discussion Results highlight the prevalence of NPS with low purity, incorporation of cathinones into NPS mixtures since 2008, and multiple members of the cathinone family being present in individual UK‐seized samples. Cathinones were identified as adulterants in NPS marketed as being pure NPS, drugs of abuse, branded products, herbal blends, and products labelled “not for human consumption.” Toxicity resulting from cathinone mixtures is unpredictable because key attributes remain largely unknown. Symptoms of intoxication include neuro‐psychological, psychiatric, and metabolic symptoms. Proposed treatment includes holistic approaches involving psychosocial, psychiatric and pharmacological interventions. Conclusion Raising awareness of NPS, education, and training of health care professionals are paramount in reducing harms related to cathinone use.

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Section: Resultsmentioning

confidence: 99%

Intended and unintended use of cathinone mixtures

Guirguis

Corkery

Stair

et al. 2017

Human Psychopharmacology

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“…Kalliokoski et al [38] have shown that the error introduced by mixing IC 50 data from different assays only adds a moderate amount of noise when comparing different measurements of the same compound-target pairs. Moreover, such intravariabilities (same compound target pair, same bioactivity endpoint, different assays) seem to be in the same range as intervariabilities (same compound target pair, different bioactivity endpoints, different assays) as we have successfully demonstrated for IC 50 and K i measurements of human serotonin and dopamine transporter ligands [11]. Thus, even when mixing IC 50 with K i data, the error introduced might be tolerable, depending on the final granularity that shall be achieved and the usage of the dataset (i.e.…”

Section: From Manual Extraction and Curation Of Literature Data To (Smentioning

confidence: 94%

“…With the idea that certain molecular features might trigger selectivity, two other phylogenetically related transporters of interest to our group, the human serotonin (hSERT) and dopamine transporters (hDAT), served for a combined data mining/in silico modeling study [11]. Data was extracted solely from the public domain for this case study, but cutoffs for the separation of actives and inactives were tailored according to targets and bioactivity endpoints (K i and IC 50 ).…”

Section: From Manual Extraction and Curation Of Literature Data To (Smentioning

confidence: 99%

“…Additionally, public–private initiatives facilitate close collaborations between academia and industry, giving access to proprietary data in order to develop and test novel computational methods on them. Thus, academic CADD is increasingly looking into topics which benefit from the unprecedented access to data, such as phenotypic annotations, in silico tools to facilitate drug repurposing, translational and precision medicine and provides computational solutions there, such as tailored workflows [11–13]. In this contribution we seek to demonstrate how all these developments influenced our (the Pharmacoinformatics Research Group at the Department of Pharmaceutical Chemistry, University of Vienna) way of approaching challenging research questions (Fig.…”

Section: Introductionmentioning

confidence: 99%

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Empowering pharmacoinformatics by linked life science data

Goldmann

Zdrazil

Digles

et al. 2016

J Comput Aided Mol Des

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With the public availability of large data sources such as ChEMBLdb and the Open PHACTS Discovery Platform, retrieval of data sets for certain protein targets of interest with consistent assay conditions is no longer a time consuming process. Especially the use of workflow engines such as KNIME or Pipeline Pilot allows complex queries and enables to simultaneously search for several targets. Data can then directly be used as input to various ligand- and structure-based studies. In this contribution, using in-house projects on P-gp inhibition, transporter selectivity, and TRPV1 modulation we outline how the incorporation of linked life science data in the daily execution of projects allowed to expand our approaches from conventional Hansch analysis to complex, integrated multilayer models.Electronic supplementary materialThe online version of this article (doi:10.1007/s10822-016-9990-4) contains supplementary material, which is available to authorized users.

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“…[45][46][47][48][49][50][51][52][53] There are also few QSAR studies involving these molecules. 28,[54][55][56][57][58][59][60][61][62][63][64][65] In view of this scenario, the present study has sought to obtain a QSAR model that can assess the potential risk of amphetamine-type substances on the basis of the common structure of amphetamines and cathinones. To evaluate this possibility, we have studied a set of 26 derivatives with in vitro measured activity against NET.…”

Section: Introductionmentioning

confidence: 99%

In silico Risk Assessment Studies of New Psychoactive Substances Derived from Amphetamines and Cathinones

Melo¹,

Martins²,

Rodrigues³

et al. 2020

J. Braz. Chem. Soc.

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The amount and variety of new psychoactive substances (NPS) are expanding, and there are difficulties in assessing their risks. In this regard, in silico methods are potentially useful to predict NPS properties faster and at a lower cost. In this work a quantitative structure-activity relationship (QSAR) model was used to verify the risk of drugs derived from amphetamines and cathinones. A dataset of 26 derivatives with in vitro affinity for norepinephrine transporter (NET) was selected. To ensure reproducibility of the results, only geometric molecular descriptors (AM1 (Austin model 1) level) obtained from the platform ChemDes and ordered predictors selection (OPS) were used. The model presents good internal statistics (n = 23; coefficient of determination (R 2) = 0.914). The small number of samples was divided into seven training sets (n = 17) and seven test sets (n = 6). The average R 2 pred = 0.754 showed that the model has good predictive capacity. Based on the tests, this model can accurately predict the risk range of three previously selected derivatives: methedrone (low), ethcathinone (medium), and methamphetamine (high), even when only data referring to NET are employed. We used these data to create a simple free program in Java that focuses on the risk assessment of recreational drugs belonging to this class of compounds.

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From linked open data to molecular interaction: studying selectivity trends for ligands of the human serotonin and dopamine transporter

Abstract: Retrieval of consistent SAR data sets is a challenging task. Combining integrated open data sources with workflow tools allows studying selectivity trends of compound series.

Cited by 11 publications

References 52 publications

Intended and unintended use of cathinone mixtures

Intended and unintended use of cathinone mixtures

Empowering pharmacoinformatics by linked life science data

In silico Risk Assessment Studies of New Psychoactive Substances Derived from Amphetamines and Cathinones

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