Literature DB >> 17504185

Computer-assisted methods in chemical toxicity prediction.

C Gopi Mohan1, Tamanna Gandhi, Divita Garg, Ranajit Shinde.   

Abstract

In Silico predictive ADME/Tox screening of compounds is one of the hottest areas in drug discovery. To provide predictions of compound drug-like characteristics early in modern drug-discovery decision making, computational technologies have been widely accepted to develop rapid high throughput in silico ADMET analysis. It is widely perceived that the early screening of chemical entities can significantly reduce the expensive costs associated with late stage failures of drugs due to poor ADME/Tox properties. Drug toxic effects are broadly defined to include toxicity, mutagenicity, carcinogenicity, teratogenicity, neurotoxicity and immunotoxicity. Toxicity prediction techniques and structure-activity relationships relies on the accurate estimation and representation of physico-chemical and toxicological properties. This review highlights some of the freely and commercially available softwares for toxicity predictions. The information content can be utilized as a guide for the scientists involved in the drug discovery arena.

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Year:  2007        PMID: 17504185     DOI: 10.2174/138955707780619554

Source DB:  PubMed          Journal:  Mini Rev Med Chem        ISSN: 1389-5575            Impact factor:   3.862


  9 in total

1.  Development, validation, and use of quantitative structure-activity relationship models of 5-hydroxytryptamine (2B) receptor ligands to identify novel receptor binders and putative valvulopathic compounds among common drugs.

Authors:  Rima Hajjo; Christopher M Grulke; Alexander Golbraikh; Vincent Setola; Xi-Ping Huang; Bryan L Roth; Alexander Tropsha
Journal:  J Med Chem       Date:  2010-11-11       Impact factor: 7.446

2.  Weighted feature significance: a simple, interpretable model of compound toxicity based on the statistical enrichment of structural features.

Authors:  Ruili Huang; Noel Southall; Menghang Xia; Ming-Hsuang Cho; Ajit Jadhav; Dac-Trung Nguyen; James Inglese; Raymond R Tice; Christopher P Austin
Journal:  Toxicol Sci       Date:  2009-10-04       Impact factor: 4.849

3.  Stability-indicating HPLC-DAD/UV-ESI/MS impurity profiling of the anti-malarial drug lumefantrine.

Authors:  Mathieu Verbeken; Sultan Suleman; Bram Baert; Elien Vangheluwe; Sylvia Van Dorpe; Christian Burvenich; Luc Duchateau; Frans H Jansen; Bart De Spiegeleer
Journal:  Malar J       Date:  2011-02-28       Impact factor: 2.979

4.  Structural investigation of ginsenoside Rf with PPARγ major transcriptional factor of adipogenesis and its impact on adipocyte.

Authors:  Fayeza Md Siraj; Sathishkumar Natarajan; Md Amdadul Huq; Yeon Ju Kim; Deok Chun Yang
Journal:  J Ginseng Res       Date:  2014-10-31       Impact factor: 6.060

Review 5.  Ayurveda and in silico Approach: A Challenging Proficient Confluence for Better Development of Effective Traditional Medicine Spotlighting Network Pharmacology.

Authors:  Rashmi Sahu; Prashant Kumar Gupta; Amit Mishra; Awanish Kumar
Journal:  Chin J Integr Med       Date:  2022-09-12       Impact factor: 2.626

6.  A rapid stability-indicating, fused-core HPLC method for simultaneous determination of β-artemether and lumefantrine in anti-malarial fixed dose combination products.

Authors:  Sultan Suleman; Kirsten Vandercruyssen; Evelien Wynendaele; Matthias D'Hondt; Nathalie Bracke; Luc Duchateau; Christian Burvenich; Kathelijne Peremans; Bart De Spiegeleer
Journal:  Malar J       Date:  2013-04-30       Impact factor: 2.979

7.  Dual binding site and selective acetylcholinesterase inhibitors derived from integrated pharmacophore models and sequential virtual screening.

Authors:  Shikhar Gupta; C Gopi Mohan
Journal:  Biomed Res Int       Date:  2014-06-25       Impact factor: 3.411

Review 8.  Modeling to optimize terminal stem cell differentiation.

Authors:  G Ian Gallicano
Journal:  Scientifica (Cairo)       Date:  2013-02-11

Review 9.  Integration of bioinformatics to biodegradation.

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

  9 in total

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