Literature DB >> 11922956

Computer systems for the prediction of toxicity: an update.

Nigel Greene1.   

Abstract

In order to survive in the current economic climate, the pharmaceutical, agrochemical and personal product companies are required to produce large numbers of new, effective products whilst significantly reducing development time and costs. With the advent of combinatorial chemistry and high-throughput screening (HTS), the numbers of new candidate structures coming out of the discovery cycle has increased significantly. This has created a demand for faster screening of the toxicological properties of these candidates. Not surprisingly, computer methods for toxicity prediction offer an attractive solution to this problem because of their ability to screen large numbers of structures even before synthesis has occurred. In this paper the major, commercially available computer software systems for toxicity prediction are discussed together with their main strengths and limitations.

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Year:  2002        PMID: 11922956     DOI: 10.1016/s0169-409x(02)00012-1

Source DB:  PubMed          Journal:  Adv Drug Deliv Rev        ISSN: 0169-409X            Impact factor:   15.470


  12 in total

1.  Discrimination between modes of toxic action of phenols using rule based methods.

Authors:  Ulf Norinder; Per Lidén; Henrik Boström
Journal:  Mol Divers       Date:  2006-05-24       Impact factor: 2.943

Review 2.  Novel paradigms for drug discovery: computational multitarget screening.

Authors:  Ekachai Jenwitheesuk; Jeremy A Horst; Kasey L Rivas; Wesley C Van Voorhis; Ram Samudrala
Journal:  Trends Pharmacol Sci       Date:  2008-01-10       Impact factor: 14.819

3.  Prediction of hERG Liability - Using SVM Classification, Bootstrapping and Jackknifing.

Authors:  Hongmao Sun; Ruili Huang; Menghang Xia; Sampada Shahane; Noel Southall; Yuhong Wang
Journal:  Mol Inform       Date:  2016-12-21       Impact factor: 3.353

Review 4.  In silico prediction of drug toxicity.

Authors:  John C Dearden
Journal:  J Comput Aided Mol Des       Date:  2003 Feb-Apr       Impact factor: 3.686

5.  CHEMICAL AND BIOLOGICAL DESCRIPTOR INTEGRATION IMPROVES COMPUTATIONAL MODELING OF IN VIVO RAT TOXICITY.

Authors:  Cristian G Bologa; Oleg Ursu; Liliana Halip; Ramona Curpăn; Tudor I Oprea
Journal:  Rev Roum Chim       Date:  2015 Feb-Mar       Impact factor: 0.278

6.  Genome-wide characterisation of the binding repertoire of small molecule drugs.

Authors:  Lee Makowski; Diane J Rodi
Journal:  Hum Genomics       Date:  2003-11       Impact factor: 4.639

7.  Low potency toxins reveal dense interaction networks in metabolism.

Authors:  William Bains
Journal:  BMC Syst Biol       Date:  2016-02-20

8.  Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules.

Authors:  Konda Leela Sarath Kumar; Sujit R Tangadpalliwar; Aarti Desai; Vivek K Singh; Abhay Jere
Journal:  PLoS One       Date:  2016-06-07       Impact factor: 3.240

Review 9.  The role of multiscale computational approaches for rational design of conventional and nanoparticle oral drug delivery systems.

Authors:  Nahor Haddish-Berhane; Jenna L Rickus; Kamyar Haghighi
Journal:  Int J Nanomedicine       Date:  2007

Review 10.  Integration of bioinformatics to biodegradation.

Authors:  Pankaj Kumar Arora; Hanhong Bae
Journal:  Biol Proced Online       Date:  2014-04-27       Impact factor: 3.244

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