1. Introduction
1.3 Target identification in drug discovery
Target identification includes identification of the target pathways and actual molecular interactors such as proteins, even though the exact difference between these two levels of targets is often difficult to distinguish. There are two main approaches to identify the target pathways and interactors of drug-like compounds: genetic interaction methods and direct biochemical methods that are backed up by computational inference methodology. Biochemical methods are considered the most straightforward. They include identification of the interacting protein by attaching a cross-linker to the molecule, perform a ―fishing‖ procedure, subsequent washing and purification of the covalent complex. Next stage includes labeling of identified protein or small molecule of interest, followed by a step of incubation of the protein with the small molecule and direct measurements of binding (Burdine and Kodadek 2004). Computational inference methodology may be used for generation of target hypothesis by pattern recognition analysis of the small molecule and referenced protein targets (Weinstein, Myers et al. 1997, Young, Bender et al. 2008).
The hypothesis is afterwards confirmed experimentally by measuring molecular interactions in
Hypothesis for the mechanism of action can be generated by analysis of changes in gene expression patterns in the presence or absence of compound. This approach allows the identification of potential target pathways, which in turn can be narrowed down to molecular targets with the use of a combination of in silico, biochemical and genetic methodology.
Determining bacterial targets involves selection of mutants, either arising spontaneously or induced by mutagenesis, that are resistant to the compound and identification of the affected gene via sequencing.
Naturally, target identification approaches are not mutually exclusive; the majority of drug discovery campaigns use a combination of biochemical and genetic methods to maximize precision of target hypothesis. Generally, integration of multiple complementary approaches is required to fully solve the problem of target identification.
1.3.1 Genetic interaction and genomic methods for drug target discovery Drug discovery based on genetic or genomic methods relies on manipulations with DNA and RNA that affects the whole in vivo system. Hypothetical targets are generated by exploring phenotypes of genetically altered organisms. Researchers use gene knockouts, RNAi (Boutros and Ahringer 2008) and small molecules with the known activity to change the functional activity of supposed targets. For example, a knockdown that phenocopies a compound‘s effect suggests involvement of the depleted gene product in the compound‘s mechanism of action and demonstrates potential chemical-genetic interactions (Fig. 1.6a). The absence of a clear target hypothesis may be compensated by generation of multiple weak target hypothesis and their subsequent approval/disproval.
Yeast is an example of well-known model with established genetics methods for target identification. In yeast, interactions of small-molecule with specific genetic loci can be revealed by generation of recombinant strains by mating. The method involves subsequent analysis of the recombinant strains that are resistant or sensitive to specific small molecule (Perlstein, Ruderfer et al. 2007) (Fig.1.6b). Patterns of polymorphisms indicate potential genetic targets. Another approach includes transformation of the clones with molecularly barcoded libraries of open reading frames. Clones fitness is analyzed with the use of microarrays to detect small molecule-resistance or increased sensitivity (Pierce, Fung et al. 2006).
The use of the yeast and other model organisms may not be effective, since direct translation to human biology may not always be achieved due to lack of conservation of some genetics pathways involved in pathology. Development of modern genetic engineering methods such as CRISPR-derived technology may be beneficial to studies of drugs mechanism of action in mammalian systems.
Figure 1.6. Illustrations of yeast genomic methods for target-identification and mechanism-of-action studies. (a) A panel of viable single-gene deletions is tested for small-molecule sensitivity;
mechanisms are interpreted by comparing interactions to double-knockout strains. (b) Different strains of diploid yeast are mated to form F1 recombinants, and meiotic progeny are subjected to small molecules;
segregation frequencies allow mapping of small-molecule sensitivity to genetic loci. (c) A recessive small molecule–resistant mutant is transformed with a wild-type open reading frame library; transformants obtaining a wild-type copy of the mutant gene are selectively sensitive to small molecules, quantified by microarray (Schenone, Dancik et al. 2013).
Another genetics-based technique for target identification includes comparison of results from small-molecule and perturbations by RNAi. The technique is similar to generation of knockouts but in this case gene expression is altered by the use of RNAi. Identified similarities of phenotypes between small-molecules and RNAis indicate the possible mechanisms of action.
RNAi screenings can be established on a genome-wide scale in order to find analogous phenotypes between small molecules and RNAi. (Fig. 1.7a) Once primary data are obtained, a set of RNAi reagents can be narrowed down for the precise indication of pathway members involved in phenotypic changes. (Fig. 1.7b) (Guertin, Guntur et al. 2006). Identification of the exact molecular targets can be then facilitated by the use of biochemical and in silico methods.
The advantages of RNAi methods include the ability to detect phenotypic changes in a more physiologically relevant environment using mammalian cells. However, genetic perturbations cannot always phenocopy the effect of a small molecule (Knight and Shokat 2007) due to the risk of genetic compensation or multiple effects generated by the small molecule.
Additionally, the drug might not always photocopy a functional knockdown; instead, it might titrate molecular interactions and induce a dominant negative effect.
Figure 1.7. Illustration of RNAi based for methods of target identification and mechanisms of action studies. a) In one implementation, phenotypes from genome-wide RNAi are compared to those induced by a small molecule of interest; phenocopy of the small-molecule effect by RNAi provides evidence that the gene product is a small-molecule target. (b) When prior evidence suggests a particular target pathway, focused sets of RNA reagents can help to generate mechanistic hypotheses (Schenone, Dancik et al. 2013).
Finally, analysis of gene expression profiles to determine a compound‘s mechanism of action blurs the line between genetic techniques and computational approaches. For example, a recent study used transcription profiling data from the Connectivity Map (Lamb, Crawford et al.
2006) and described a weighting scheme to classify and order lists of genes across various cell lines in an attempt to develop a prototype ranking list (Iorio, Bosotti et al. 2010). Such an approach has its limits, since it relies on accurately annotated activities of small-molecules, but the continuously growing datasets of gene profiling will facilitate the merge of genetic and bioinformatical methods.