Selecting a target for settingup the drug discovery path is a tough decision and often this choice is based on borrowed and incomplete knowledge from the literature In many cases this has led to serious challenges in the late stages of clinical trials dealing with patients In most cases these drug discovery programmes are missing the consideration of human disease biology complexity At least this is haunting the community in one such disease area neuro drug discovery The lack of relevant biological models that are close to real disease and our insufficient knowledge about the targets are the two serious mountains to climb and require building highly integrated working models These challenges are driving the change in our thinking ie moving away from single targetbased biased studies to clinically relevant unbiased phenotypic programmes and ask for different thinking strategies to making a progress on this tough journey
It is common knowledge that drug discovery is a tough business to be in, and requires constant questioning as well as refining of ongoing strategies. In this game, the early days were rewarding for those employing the classical approaches that rely upon identifying the target, and building a programme around these well-established target(s), to produce novel drug candidates for a variety of biological disorders (see Figure 1).In recent years, the failure of some of the expensive late stage clinical trials are beginning to question our classical approach in this arena. For example, in 2016, the drug candidate LMTX for Alzheimer’s, could not stand successful in a large phase III clinical trial, although it may still show some promise for patients suffering from Alzheimer’s disease. This expensive clinical trial dealt with nearly 900 patients who had moderate symptoms of Alzheimer’s disease.
Is the target really true and dependable, and is it worth building a time and money-consuming programme around? Typically, in our early days, the acceptance of the target(s) was taken in the absence of complex human machinery as well as diversity. In many challenging disease areas, such as cancer and neurological disorders, our classical thinking of chasing single isolated target(s) is beginning to haunt us; at the same time, it is also forcing us seriously to question our presently practiced drug discovery approaches. In general, the acceptance of a given biological target for setting-up the drug discovery path is based on partial information or biased thinking that is commonly associated with the target. In many cases, the clinical validity of the biological targets in the context of "patient information" is generally missing. Our quest to develop the next generation of drugs for neurological disorders is also badly missing this. It is now well-accepted that the lack of relevant models closely representing the brain disorders are some of the major limiting factors in this area. Overcoming these challenges will allow development of new research models that utilise, for example, patient-derived, induced pluripotent stem cells and the generation of neurons from these cells for further studies.
The drug discovery community has been trained to think about the isolated target(s) and then seeking the structural information which further sets the stage for building the medicinal chemistry programme. In general, this approach utilises well-accepted medicinal chemistry rules for obtaining small molecule candidates (for example, Lipinski rule of 5). Then came the post-genomic era: with a message that proteins do not function in isolation, and rather, are a part of complex networks, commonly known as signalling pathways (see Figure 2). In general, these pathways are composed of highly complex and dynamic, multiple, protein-to-protein interactions to induce biological functions. It is also now well-accepted that these pathways are highly organised in normal functions and their subsequent de-regulation leads to various disease states. Not only is it necessary to know enough about these pathways, our biological question(s) should also be well-aligned, keeping in mind the relevance of complex human machinery. More and more our quest to address clinically-relevant biological questions is becoming the backbone of the modern drug arena. This is a major paradigm shift for all of us; it is also forcing us to create novel approaches that are out of the box and develop highly integrated research models. A typical small molecule chemical arsenal that was the hall mark of classical enzyme pocket-based drug discovery may not be challenging enough to undertake complex biological targets dealing with multiple protein-protein interactions. Newer approaches are needed to access compounds that are capable of modulating large surface area-based interactions, and this alone is creating a huge challenge for the next generation, medicinal chemistry community.
Moving on from the single isolated target(s) that are usually undertaken in drug discovery programmes, we are now beginning to appreciate the power of clinically-relevant, un-biased, functional biological screens leading the discovery of novel chemical probes which can lead to establishing the drug discovery path (see Figure 3).One of the key advantages in this approach is the use of the patient (for example, in cancer and neurological disorders) as the source of developing functional biological screens to address specific questions. In doing so, one tries to keep the biases aside (to reaching the information about the target at early stages) while developing screening assays. The goal here is to discover novel small molecules exhibiting specific phenotypic biological effects; serious efforts are then placed for collecting the information of the biological target(s) being affected / modulated by a specific small molecule.
Given the complexity of diseases such as cancer and neurological disorders, it is naive to consider a single biological target a safe starting point for the drug discovery. Cancer can be considered as a combination of several diseases; in general, several components of the cells/signalling pathways get de-regulated. This can further vary from patient to patient. The thought of having a magic bullet taking care of several de-regulated processes in this course of action is asking too much from a single small molecule. It is not known when we will be seeing the finish line of the personalised cancer medicine. It will be a long and tough road to cover before enjoying the fruit of these highly specialised ‘next generation’ medicines. On the positive side, however, the accessibility of patient-derived cancer samples in developing some of these modern drug discovery approaches is highly encouraging. The day is not too far when we start seeing the benefits of all this progress impacting the cancer patient population. That being said, the neurological disorders present much higher degree of challenges compared to other diseases. As the scientific community comes up with clinicallyrelevant models in brain disorders drug discovery and further exploration of their applications in phenotypic screening of novel functional small molecules, we might be able to produce better outcomes
in curing patients in the long run.
With the discovery of novel chemical probes through these unbiased clinically-relevant functional screens, narrowing down our understanding for providing information on targets modulated by small molecules can be highly intense and a time consuming exercise. Making progress on this tough journey requires working with several different skill-sets, such as genomic and CRISPR-Cas9 tools, target pull-out studies, small molecule-target binding information by protein NMR, SPR, and X-ray studies. This is almost the reverse of what we have been trained to do in the drug discovery culture, over the years. The newer approaches require working with patients as the starting point and seeking information on biological targets (in addition to our ability to observing their modulation by small molecule approaches) are key to developing clinically-relevant drug discovery programmes.
A recent publication from Roche titled "Molecular Phenotyping Combines Molecular Information, Biological Relevance, and Patient Data to Improve Productivity of Early Drug Discovery" is a testimony to this emerging, no-target centric-based research model that deeply involves unbiased, phenotypic screen(s).
Building new research models that are inclusive of different skill-sets ranging from genomic/CRISPR-Cas9 science, clinically-relevant signalling pathway biology, phenotypic screens, and modern synthetic approaches, is expected to lead the way on this tough journey. As we progress on this road, our ability to embrace different skillsets for addressing challenging disease biology-related questions would go far in making this tough journey enjoyable and beneficial to human kind. This water remains to be tested in coming years.