Literature DB >> 19231313

Novel web-based tools combining chemistry informatics, biology and social networks for drug discovery.

Moses Hohman1, Kellan Gregory, Kelly Chibale, Peter J Smith, Sean Ekins, Barry Bunin.   

Abstract

A convergence of different commercial and publicly accessible chemical informatics, databases and social networking tools is positioned to change the way that research collaborations are initiated, maintained and expanded, particularly in the realm of neglected diseases. A community-based platform that combines traditional drug discovery informatics with Web2.0 features in secure groups is believed to be the key to facilitating richer, instantaneous collaborations involving sensitive drug discovery data and intellectual property. Heterogeneous chemical and biological data from low-throughput or high-throughput experiments are archived, mined and then selectively shared either just securely between specifically designated colleagues or openly on the Internet in standardized formats. We will illustrate several case studies for anti-malarial research enabled by this platform, which we suggest could be easily expanded more broadly for pharmaceutical research in general.

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Year:  2009        PMID: 19231313     DOI: 10.1016/j.drudis.2008.11.015

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  45 in total

1.  Bottlenecks caused by software gaps in miRNA and RNAi research.

Authors:  Sean Ekins; Ron Shigeta; Barry A Bunin
Journal:  Pharm Res       Date:  2012-02-24       Impact factor: 4.200

2.  Time for cooperation in health economics among the modelling community.

Authors:  Renée J G Arnold; Sean Ekins
Journal:  Pharmacoeconomics       Date:  2010       Impact factor: 4.981

3.  Finding promiscuous old drugs for new uses.

Authors:  Sean Ekins; Antony J Williams
Journal:  Pharm Res       Date:  2011-05-24       Impact factor: 4.200

4.  App-etite for change.

Authors:  Wendy A Warr
Journal:  J Comput Aided Mol Des       Date:  2014-12-17       Impact factor: 3.686

5.  Identification of novel activators of constitutive androstane receptor from FDA-approved drugs by integrated computational and biological approaches.

Authors:  Caitlin Lynch; Yongmei Pan; Linhao Li; Stephen S Ferguson; Menghang Xia; Peter W Swaan; Hongbing Wang
Journal:  Pharm Res       Date:  2012-10-23       Impact factor: 4.200

6.  Combining cheminformatics methods and pathway analysis to identify molecules with whole-cell activity against Mycobacterium tuberculosis.

Authors:  Malabika Sarker; Carolyn Talcott; Peter Madrid; Sidharth Chopra; Barry A Bunin; Gyanu Lamichhane; Joel S Freundlich; Sean Ekins
Journal:  Pharm Res       Date:  2012-04-04       Impact factor: 4.200

7.  Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.

Authors:  Sean Ekins; Robert C Reynolds; Hiyun Kim; Mi-Sun Koo; Marilyn Ekonomidis; Meliza Talaue; Steve D Paget; Lisa K Woolhiser; Anne J Lenaerts; Barry A Bunin; Nancy Connell; Joel S Freundlich
Journal:  Chem Biol       Date:  2013-03-21

8.  Essential metabolites of Mycobacterium tuberculosis and their mimics.

Authors:  Gyanu Lamichhane; Joel S Freundlich; Sean Ekins; Niluka Wickramaratne; Scott T Nolan; William R Bishai
Journal:  mBio       Date:  2011-02-01       Impact factor: 7.867

9.  Are bigger data sets better for machine learning? Fusing single-point and dual-event dose response data for Mycobacterium tuberculosis.

Authors:  Sean Ekins; Joel S Freundlich; Robert C Reynolds
Journal:  J Chem Inf Model       Date:  2014-07-17       Impact factor: 4.956

10.  Human immunodeficiency virus protease inhibitors interact with ATP binding cassette transporter 4/multidrug resistance protein 4: a basis for unanticipated enhanced cytotoxicity.

Authors:  Yu Fukuda; Kazumasa Takenaka; Alex Sparreboom; Satish B Cheepala; Chung-Pu Wu; Sean Ekins; Suresh V Ambudkar; John D Schuetz
Journal:  Mol Pharmacol       Date:  2013-06-17       Impact factor: 4.436

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