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have created a therapy. But once again the chal- lenge is very often protein-protein interactions and often these surfaces do not have big pockets or clefts for a small molecule to bind into. The ques- tion is still out as to how to do this. CRISPR may provide a potential answer. Recently Salk scientists have adapted the CRISPR mechanism to modulate expression of genes – rather than knock them out (DOI: https://doi.org/10.1016/j.cell.2018.02.033). They have done this by utilising a defective Cas9 which cannot cleave but can still target the gene specificity by the appropriate guide RNA. Thus, there is the ability to turn genes off and on at the transcriptional level, which enables a number of key experiments that drug developers have been wishing for – the ability to modulate components of a protein complex without having to clone all the genes involved. This next round of CRISPR reagents will have a profound effect on how we look at altering gene expression with the abilities for turning genes on or off or to potentially disrupt a translation of a portion of a protein (DOI: https://doi.org/10.1016/j.cell.2017.10.025). By removing specific domains of proteins, we can bet- ter learn the full potential of drugging them and hopefully zero in on the regions or interactions that are critical.


Genetic modalities Genetics is often the route chosen for target identi- fication and validation, a result of Genome-Wide Association Studies (GWAS) linking certain genetic variants or mutations to a disease condition or having a direct biomarker in the gene causing the disease. While we utilise the results of genome- wide sequencing data and incorporate gene expres- sion data within the rationale for pursuing drug discovery efforts of specific pathways and proteins, the use of genetics to aid in finding a cure is often left behind. Compensatory mutations that can res- cue the original mutation is an area of genetics that has been the focus in model organisms for quite some time. Its possible application to drug devel- opment adds another avenue to consider when searching for a disease modifying drug. Can a drug against a protein in another pathway solve/prevent the condition caused by the original mutation? A similar approach has been harnessed in drug devel- opment for cancers – synthetic lethality, or in the dug development world, chemical lethality – as a means of selectively destroying cancer cells. In this case the cancer cells have a mutation which in part is responsible for their phenotype. When this muta- tion is combined with another mutation (which also by itself has no effect on the cell) the cell is


Drug Discovery World Spring 2018


doomed – hence being synthetic lethal. Finding compounds that cause this effect are a potential source of new drugs and a new mechanism of action for treating cancers. If two mutations can work together to provide lethality, could the reverse not also be true – synthetic health. This approach would seek non-related mutations which cure the phenotypic disease or at least slow it down. This strategy could also be used in drug combination types of approaches and creation of chimeric compounds.


Death of a dogma: CDS and ORFs In the world of big data, it is often useful to remind ourselves as to how data is being analysed and ask ourselves to go back and visit the bioinformatics’ algorithms applied and the curated data generated. What was relevant and cutting edge then, may not be so now with our ever-expanding knowledge base. Years ago, this fault was demonstrated in the RNA world as we became aware of siRNA’s being important in both gene regulation and mRNA sta- bility/translation and more recently with exosomal RNA, RNA transported via exosomes to other cells and snoRNAs. Now we see the same with proteins. In the early


days of genomics and bioinformatics, one mRNA coding sequence (CDS) was considered to be asso- ciated with only one protein-coding gene. But now we know that eukaryotic mRNAs contain not a single refCDS but usually several ORFs. The single CDS dogma has artificially limited our view of the coding capacity of mRNAs and has prevented the discovery of alternative proteins despite some clues in the literature over the years. Functional relationships between reference and alternative proteins expressed from the same gene may help identify a new layer of regulation of protein activ- ity. Previously, the definition of a protein was clas- sically defined as a stretch of 100+ amino acids with a start and stop codon, with some minor variations. The algorithm has broadly been used to ‘identify’ the number of proteins in the genome of just about every organism sequenced. Of course, variations of these parameters have been made but back in the 80s, with the limited knowl- edge available, it made sense. However, today it is becoming increasingly apparent that one has to closely look at our definition of a protein. Spearheaded out of the University of Sherbrooke by the Roucou lab (www.roucoulab.com), the Alt-Prot analysis of the genome has lowered the requirement of a protein to 30 amino acids. The protein coding potential of eukaryotic mRNAs has surely been underestimated (see


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