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.

Keywords: malaria; phenotypic screening; resistance; selections.

Figure 1

Plasmodium life cycle with chemically validated targets for chemotherapeutic intervention divided by the stages in which they have demonstrated antimalarial activity. Adapted with permission from Nilsson, S. K., Childs, L. M., Buckee, C., and Marti, M. (2015) Targeting Human Transmission Biology for Malaria Elimination. PLoS Pathog.11 (6), e1004871. DOI: 10.1371/journal.ppat.1004871 (ref (200)). Copyright 2015 Nilsson et al.

Figure 2

Overview of IVIEWGA process. (A) A clonal aliquot (obtained by limiting dilution in a microtiter plate) of a sensitive parent P. falciparum strain is cultured in triplicate and subjected to the selective pressure of an antimalarial compound using a slow ramping or pulse method. Upon successful generation of resistant parasite bulk cultures, clones are isolated using limiting dilution and retested for resistance. (B) Whole genome sequencing is performed using gDNA extracted from the parent and resistant clones. Bioinformatic analysis calls variants between the parent and resistant lines to determine which mutations confer resistance. Generally, mutations that arise in multiple, independently derived clones are prioritized for further validation, which may include structural modeling, molecular docking simulations, and/or reverse genetics techniques.

Figure 3

Antimalarial compounds grouped by targets as determined or supported by IVIEWGA studies. References are given in Table 1. SMILES for each compound are given in Table S1.