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Fueling Open‐Source Drug Discovery: 177 Small‐Molecule Leads against Tuberculosis
Author(s) -
Ballell Lluís,
Bates Robert H.,
Young Rob J.,
AlvarezGomez Daniel,
AlvarezRuiz Emilio,
Barroso Vanessa,
Blanco Delia,
Crespo Benigno,
Escribano Jaime,
González Rubén,
Lozano Sonia,
Huss Sophie,
SantosVillarejo Angel,
MartínPlaza José Julio,
Mendoza Alfonso,
RebolloLopez María José,
RemuiñanBlanco Modesto,
Lavandera José Luis,
PérezHerran Esther,
GamoBenito Francisco Javier,
GarcíaBustos José Francisco,
Barros David,
Castro Julia P.,
Cammack Nicholas
Publication year - 2013
Publication title -
chemmedchem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.817
H-Index - 100
eISSN - 1860-7187
pISSN - 1860-7179
DOI - 10.1002/cmdc.201200428
Subject(s) - drug discovery , antimycobacterial , computational biology , tuberculosis , mycobacterium tuberculosis , open source , drug , phenotypic screening , small molecule , biology , bioinformatics , medicine , pharmacology , computer science , genetics , phenotype , software , pathology , gene , programming language
Abstract With the aim of fuelling open‐source, translational, early‐stage drug discovery activities, the results of the recently completed antimycobacterial phenotypic screening campaign against Mycobacterium bovis BCG with hit confirmation in M. tuberculosis H37Rv were made publicly accessible. A set of 177 potent non‐cytotoxic H37Rv hits was identified and will be made available to maximize the potential impact of the compounds toward a chemical genetics/proteomics exercise, while at the same time providing a plethora of potential starting points for new synthetic lead‐generation activities. Two additional drug‐discovery‐relevant datasets are included: a) a drug‐like property analysis reflecting the latest lead‐like guidelines and b) an early lead‐generation package of the most promising hits within the clusters identified.