Journal ArticleDOI
admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties.
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TLDR
An ADMET structure-activity relationship database that collects, curates, and manages available ADMET-associated properties data from the published literature, and provides a user-friendly interface to query a specific chemical profile, using either CAS registry number, common name, or structure similarity.Abstract:
Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties play key roles in the discovery/development of drugs, pesticides, food additives, consumer products, and industrial chemicals. This information is especially useful when to conduct environmental and human hazard assessment. The most critical rate limiting step in the chemical safety assessment workflow is the availability of high quality data. This paper describes an ADMET structure–activity relationship database, abbreviated as admetSAR. It is an open source, text and structure searchable, and continually updated database that collects, curates, and manages available ADMET-associated properties data from the published literature. In admetSAR, over 210 000 ADMET annotated data points for more than 96 000 unique compounds with 45 kinds of ADMET-associated properties, proteins, species, or organisms have been carefully curated from a large number of diverse literatures. The database provides a user-friendly interface to query a...read more
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Journal ArticleDOI
SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules
TL;DR: The new SwissADME web tool is presented that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar are presented.
Journal ArticleDOI
pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures
TL;DR: A novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development and performs as well or better than current methods.
Journal ArticleDOI
DrugBank 4.0: shedding new light on drug metabolism
Vivian Law,Craig Knox,Yannick Djoumbou,Timothy Jewison,An Chi Guo,Yifeng Liu,Adam Maciejewski,David Arndt,Michael Wilson,Vanessa Neveu,Alexandra Tang,Geraldine Gabriel,Carol Ly,Sakina Adamjee,Zerihun T. Dame,Beomsoo Han,You Zhou,David S. Wishart +17 more
TL;DR: The latest update of DrugBank, DrugBank 4.0, has been further expanded to contain data on drug metabolism, absorption, distribution, metabolism, excretion and toxicity (ADMET) and other kinds of quantitative structure activity relationships (QSAR) information.
Journal ArticleDOI
The neuroactive potential of the human gut microbiota in quality of life and depression
Mireia Valles-Colomer,Mireia Valles-Colomer,Gwen Falony,Gwen Falony,Youssef Darzi,Youssef Darzi,Ettje F. Tigchelaar,Jun Wang,Jun Wang,Raul Y. Tito,Raul Y. Tito,Raul Y. Tito,Carmen Schiweck,Alexander Kurilshikov,Marie Joossens,Marie Joossens,Cisca Wijmenga,Cisca Wijmenga,Stephan Claes,Lukas Van Oudenhove,Alexandra Zhernakova,Sara Vieira-Silva,Sara Vieira-Silva,Jeroen Raes,Jeroen Raes +24 more
TL;DR: Correlation of microbiome features with host quality of life and depression identified specific taxa and microbial pathways in two independent, large population cohorts, identifying links between microbial neuroactive potential and depression.
Journal ArticleDOI
ProTox-II: a webserver for the prediction of toxicity of chemicals.
TL;DR: ProTox-II is presented, a freely available webserver for in silico toxicity prediction for toxicologists, regulatory agencies, computational and medicinal chemists, and all users without login at http://tox.charite.de/protox_II.
References
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Journal ArticleDOI
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Journal ArticleDOI
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Journal ArticleDOI
ADMET in silico modelling: towards prediction paradise?
TL;DR: In this paper, the authors describe how in silico approaches will further increase our ability to predict and model the most relevant pharmacokinetic, metabolic and toxicity endpoints, thereby accelerating the drug discovery process.
Journal ArticleDOI
Antiherpesvirus drugs: a promising spectrum of new drugs and drug targets
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