Literature DB >> 29934887

The OECD QSAR Toolbox Starts Its Second Decade.

Terry W Schultz1, Robert Diderich2, Chanita D Kuseva3, Ovanes G Mekenyan4.   

Abstract

The OECD QSAR Toolbox is a computer software designed to make pragmatic qualitative and quantitative structure-activity relationship methods-based predictions of toxicity, including read-across, available to the user in a comprehensible and transparent manner. The Toolbox, provide information on chemicals in structure-searchable, standardized files that are associated with chemical and toxicity data to ensure that proper structural analogs can be identified. This chapter describes the advantages of the Toolbox, the aims, approach, and workflow of it, as well as reviews its history. Additionally, key functional elements of it use are explained and features new to Version 4.1 are reported. Lastly, the further development of the Toolbox, likely needed to transform it into a more comprehensive Chemical Management System, is considered.

Entities:  

Keywords:  Adverse outcome pathways; Chemical category; Data gap filling; OECD QSAR Toolbox; Weight of evidence

Mesh：

Substances：

Year:  2018        PMID： 29934887     DOI： 10.1007/978-1-4939-7899-1_2

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN： 1064-3745


  8 in total

1.  Integrating publicly available information to screen potential candidates for chemical prioritization under the Toxic Substances Control Act: A proof of concept case study using genotoxicity and carcinogenicity.

Authors:  Grace Patlewicz; Jeffry L Dean; Catherine F Gibbons; Richard S Judson; Nagalakshmi Keshava; Leora Vegosen; Todd M Martin; Prachi Pradeep; Anita Simha; Sarah H Warren; Maureen R Gwinn; David M DeMarini
Journal:  Comput Toxicol       Date:  2021-11-01

2.  Evaluation of Existing QSAR Models and Structural Alerts and Development of New Ensemble Models for Genotoxicity Using a Newly Compiled Experimental Dataset.

Authors:  Prachi Pradeep; Richard Judson; David M DeMarini; Nagalakshmi Keshava; Todd M Martin; Jeffry Dean; Catherine F Gibbons; Anita Simha; Sarah H Warren; Maureen R Gwinn; Grace Patlewicz
Journal:  Comput Toxicol       Date:  2021-05-01

3.  Computational discovery of small drug-like compounds as potential inhibitors of SARS-CoV-2 main protease.

Authors:  Alexander M Andrianov; Yuri V Kornoushenko; Anna D Karpenko; Ivan P Bosko; Alexander V Tuzikov
Journal:  J Biomol Struct Dyn       Date:  2020-07-14

4.  BRADSHAW: a system for automated molecular design.

Authors:  Darren V S Green; Stephen Pickett; Chris Luscombe; Stefan Senger; David Marcus; Jamel Meslamani; David Brett; Adam Powell; Jonathan Masson
Journal:  J Comput Aided Mol Des       Date:  2019-10-21       Impact factor: 3.686

5.  Derivation of New Threshold of Toxicological Concern Values for Exposure via Inhalation for Environmentally-Relevant Chemicals.

Authors:  Mark D Nelms; Grace Patlewicz
Journal:  Front Toxicol       Date:  2020-10-16

6.  Clustering a Chemical Inventory for Safety Assessment of Fragrance Ingredients: Identifying Read-Across Analogs to Address Data Gaps.

Authors:  Mihir S Date; Devin O'Brien; Danielle J Botelho; Terry W Schultz; Daniel C Liebler; Trevor M Penning; Daniel T Salvito
Journal:  Chem Res Toxicol       Date:  2020-05-06       Impact factor: 3.739

Review 7.  In silico prediction of toxicity and its applications for chemicals at work.

Authors:  Kyung-Taek Rim
Journal:  Toxicol Environ Health Sci       Date:  2020-05-14

8.  Defining the Human-Biota Thresholds of Toxicological Concern for Organic Chemicals in Freshwater: The Proposed Strategy of the LIFE VERMEER Project Using VEGA Tools.

Authors:  Diego Baderna; Roberta Faoro; Gianluca Selvestrel; Adrien Troise; Davide Luciani; Sandrine Andres; Emilio Benfenati
Journal:  Molecules       Date:  2021-03-30       Impact factor: 4.411
  8 in total

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