The Open Access Malaria Box: A Drug Discovery Catalyst for Neglected Diseases

Historically, one of the key problems in neglected disease drug discovery has been identifying new and interesting chemotypes. Phenotypic screening of the malaria parasite, Plasmodium falciparum has yielded almost 30,000 submicromolar hits in recent years. To make this collection more accessible, a collection of 400 chemotypes has been assembled, termed the Malaria Box. Half of these compounds were selected based on their drug-like properties and the others as molecular probes. These can now be requested as a pharmacological test set by malaria biologists, but importantly by groups working on related parasites, as part of a program to make both data and compounds readily available. In this paper, the analysis and selection methodology and characteristics of the compounds are described.

[1]  Tudor I. Oprea,et al.  Property distribution of drug-related chemical databases* , 2000, J. Comput. Aided Mol. Des..

[2]  Simon Townson,et al.  Integrated Dataset of Screening Hits against Multiple Neglected Disease Pathogens , 2011, PLoS neglected tropical diseases.

[3]  David S. Roos,et al.  Identification of Attractive Drug Targets in Neglected-Disease Pathogens Using an In Silico Approach , 2010, PLoS neglected tropical diseases.

[4]  M. Mota,et al.  The Next Opportunity in Anti-Malaria Drug Discovery: The Liver Stage , 2011, PLoS pathogens.

[5]  James R. Brown,et al.  Thousands of chemical starting points for antimalarial lead identification , 2010, Nature.

[6]  Dimitris K. Agrafiotis,et al.  Library Enhancement through the Wisdom of Crowds , 2011, J. Chem. Inf. Model..

[7]  J. Baird,et al.  Targeting the hypnozoite reservoir of Plasmodium vivax: the hidden obstacle to malaria elimination. , 2010, Trends in parasitology.

[8]  Bruce Russell,et al.  Artemisinin resistance in Plasmodium falciparum is associated with an altered temporal pattern of transcription , 2011, BMC Genomics.

[9]  Gerard J. P. van Westen,et al.  Proteochemometric modeling as a tool to design selective compounds and for extrapolating to novel targets , 2011 .

[10]  T. Wells,et al.  When is enough enough? The need for a robust pipeline of high-quality antimalarials. , 2010, Discovery medicine.

[11]  Richard J Maude,et al.  The last man standing is the most resistant: eliminating artemisinin-resistant malaria in Cambodia , 2009, Malaria Journal.

[12]  V. Avery,et al.  Development and Optimization of a Novel 384-Well Anti-Malarial Imaging Assay Validated for High-Throughput Screening , 2012, The American journal of tropical medicine and hygiene.

[13]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings , 1997 .

[14]  John P. Overington,et al.  Genomic-scale prioritization of drug targets: the TDR Targets database , 2008, Nature Reviews Drug Discovery.

[15]  Kelly Chibale,et al.  The state of the art in anti-malarial drug discovery and development. , 2011, Current topics in medicinal chemistry.

[16]  D R Flower,et al.  DISSIM: a program for the analysis of chemical diversity. , 1998, Journal of molecular graphics & modelling.

[17]  Weltgesundheitsorganisation.  World malaria report , 2005 .

[18]  Daniel J. Warner,et al.  Matched molecular pairs as a medicinal chemistry tool. , 2011, Journal of medicinal chemistry.

[19]  Yingyao Zhou,et al.  Imaging of Plasmodium Liver Stages to Drive Next-Generation Antimalarial Drug Discovery , 2011, Science.

[20]  S. Anzali,et al.  Discriminating between drugs and nondrugs by prediction of activity spectra for substances (PASS). , 2001, Journal of medicinal chemistry.

[21]  G. Bemis,et al.  The properties of known drugs. 1. Molecular frameworks. , 1996, Journal of medicinal chemistry.

[22]  Phenotypic Screens, Chemical Genomics, and Antimalarial Lead Discovery , 2011, PLoS pathogens.

[23]  E. Winzeler,et al.  The Activities of Current Antimalarial Drugs on the Life Cycle Stages of Plasmodium: A Comparative Study with Human and Rodent Parasites , 2012, PLoS medicine.

[24]  Francisco-Javier Gamo,et al.  Global phenotypic screening for antimalarials. , 2012, Chemistry & biology.

[25]  Michael C. Hutter,et al.  Gradual in Silico Filtering for Druglike Substances , 2008, J. Chem. Inf. Model..

[26]  Matthew E Welsch,et al.  Privileged scaffolds for library design and drug discovery. , 2010, Current opinion in chemical biology.

[27]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. , 2001, Advanced drug delivery reviews.

[28]  J. Burrows,et al.  The global pipeline of new medicines for the control and elimination of malaria , 2012, Malaria Journal.

[29]  Anang A. Shelat,et al.  Chemical genetics of Plasmodium falciparum , 2010, Nature.

[30]  John P. Overington,et al.  ChEMBL: a large-scale bioactivity database for drug discovery , 2011, Nucleic Acids Res..

[31]  M. Gilson,et al.  Public domain databases for medicinal chemistry. , 2012, Journal of medicinal chemistry.

[32]  G. Rishton.  Reactive compounds and in vitro false positives in HTS , 1997 .

[33]  J. Baell,et al.  New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. , 2010, Journal of medicinal chemistry.

[34]  Brian Hudson,et al.  Strategic Pooling of Compounds for High-Throughput Screening , 1999, J. Chem. Inf. Comput. Sci..

[35]  W. Patrick Walters,et al.  A guide to drug discovery: Designing screens: how to make your hits a hit , 2003, Nature Reviews Drug Discovery.