Unknown

Dataset Information

0

Using in Vitro Evolution and Whole Genome Analysis To Discover Next Generation Targets for Antimalarial Drug Discovery.


ABSTRACT: Although many new anti-infectives have been discovered and developed solely using phenotypic cellular screening and assay optimization, most researchers recognize that structure-guided drug design is more practical and less costly. In addition, a greater chemical space can be interrogated with structure-guided drug design. The practicality of structure-guided drug design has launched a search for the targets of compounds discovered in phenotypic screens. One method that has been used extensively in malaria parasites for target discovery and chemical validation is in vitro evolution and whole genome analysis (IVIEWGA). Here, small molecules from phenotypic screens with demonstrated antiparasitic activity are used in genome-based target discovery methods. In this Review, we discuss the newest, most promising druggable targets discovered or further validated by evolution-based methods, as well as some exceptions.

SUBMITTER: Luth MR 

PROVIDER: S-EPMC5848146 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

altmetric image

Publications

Using in Vitro Evolution and Whole Genome Analysis To Discover Next Generation Targets for Antimalarial Drug Discovery.

Luth Madeline R MR   Gupta Purva P   Ottilie Sabine S   Winzeler Elizabeth A EA  

ACS infectious diseases 20180221 3


Although many new anti-infectives have been discovered and developed solely using phenotypic cellular screening and assay optimization, most researchers recognize that structure-guided drug design is more practical and less costly. In addition, a greater chemical space can be interrogated with structure-guided drug design. The practicality of structure-guided drug design has launched a search for the targets of compounds discovered in phenotypic screens. One method that has been used extensively  ...[more]

Similar Datasets

2011-10-31 | E-GEOD-32485 | biostudies-arrayexpress
| S-EPMC3473092 | biostudies-literature
2011-10-31 | GSE32485 | GEO
| S-EPMC5379905 | biostudies-literature
| S-EPMC8608365 | biostudies-literature
| S-EPMC5698296 | biostudies-literature
| S-EPMC3933208 | biostudies-other
| S-EPMC4588184 | biostudies-literature
2018-02-15 | ST001074 | MetabolomicsWorkbench
| S-EPMC6604616 | biostudies-literature