New Modalities, Technologies, and Partnerships in Probe and Lead Generation: Enabling a Mode-of-Action Centric Paradigm

Abstract

With the rise of novel biology and high potential target identification technologies originating from advances in genomics, medicinal chemists are progressively facing targets of increasing complexity and often unprecedented. Novel hit finding technologies, combined with a wider choice of drug modalities, has resulted in a unique repertoire of options to address these challenging targets and to identify suitable starting points for optimization. Furthermore, innovative solutions originating from a range of academic groups and biotech companies require new types of collaborative models to leverage and integrate them in the drug discovery process. This perspective provides a guide for medicinal chemists covering contemporary probe and lead generation approaches and discusses the strengths and limitations of each strategy. Moreover, the expansion of strategies to modulate proteins creates the opportunity of a modality-agnostic and mode-of-action centric hit finding paradigm.

Cellular response to small molecules that selectively stall protein synthesis by the ribosome

“…PF8503 belongs to a new family of compounds able to selectively inhibit the translation of target proteins by the human ribosome. Originally discovered as an orallyavailable small molecule inhibitor of PCSK9 production [9,10,29], this class of compound could eventually serve as as a new paradigm for designing therapeutics for "undruggable" proteins [2]. These compounds have the unique ability to bind inside the ribosome exit tunnel, allowing them to interact with the protein nascent chain and selectivally stall translation [12].…”

“…These compounds bind in the ribosome exit tunnel [12], Liaud et al 5 and seem to affect the trajectory of the growing nascent polypeptide chain in the exit tunnel as it is extended, thereby selectively stalling translation of a narrow spectrum of transcripts. Understanding the molecular basis for how these compounds selectively stall translation will be critical for the future design of transcript-specific translation inhibitors to target previously undruggable proteins [2]. However, designing new molecules as selective translation inhibitors to treat disease also necessitates a better understanding of how cells respond and adapt to compound-induced translational stalling.…”

AI Case Studies: Potential for Human Health, Space Exploration and Colonisation and a Proposed Superimposition of the Kubler-Ross Change Curve on the Hype Cycle

“…Reasons underlying factorial and comprise contributions from basic non translational science, clinical efficacy and safety, regulatory and commercial issues, together with the need to tackle increasingly challenging areas of human disease where the pathophysiology is often heterogeneous. Significant advances in screening [31], use of antibodies [32], [33] and generation of new modalities for targets previously thought as intractable [34], [35], phenome technologies applied to large samples sets and small volume sample size [36] mean that it is now possible to generate very large data sets designed to assist the selection of candidate drugs and their progression through lengthy and costly clinical trials. One critical part of the drug discovery process which underpins all downstream further drug development in both non-clinical and clinical phases based manual handling of potential new medical entities and to match appropriately designed drugs to the genotype and phenotype of the patient.…”

Harnessing the Space Environment for the Discovery and Development of New Medicines

“…This machine-based learning (MBL) approach has been successful in designing compounds that fall into two broad and opposing classes of differing melting temperatures, biased towards a range of lipophilicity and with differing values of pIC 50 directed against the Janus 2 non-receptor tyrosine kinase The system can be extended to multi-parameter optimization of compound properties in a concurrent manner and it may be possible to compress the classical lead identification and optimization phases, build into desired targets pharmacophores which may afford, for example radioprotection as standard while optimizing potency, selectivity, solubility, and DMPK parameters associated with drug-likeness. Progression of a candidate drug through clinical development is often without a complete understanding of the mechanism of action of the drug and recently scoring algorithms have been developed (Valeur and Jimonet 2018) and shown to be useful tools which integrate the overall project risk for progression and this has been termed the Platform of Evidence.…”