Improving the efficacy-safety balance of polypharmacology in multi-target drug discovery

Abstract

Polypharmacology has emerged as an essential paradigm for modern drug discovery process. Multiple lines of evidence suggest that agents capable of modulating multiple targets in a selective manner may offer also improved balance between therapeutic efficacy and safety compared to single-targeted agents. Areas covered: Herein, the authors review the recent progress made in experimental and computational strategies for addressing the critical challenges with rational discovery of selective multi-targeted agents within the context of polypharmacological modelling. Specific focus is placed on multi-targeted mono-therapies, although examples of combinatorial polytherapies are also covered as an important part of the polypharmacology paradigm. The authors focus mainly on anti-cancer treatment applications, where polypharmacology is playing a key role in determining the efficacy-toxicity trade-off of multi-targeting strategies. Expert opinion: Even though it is widely appreciated that complex polypharmacological interactions can contribute both to therapeutic and adverse side-effects, systematic approaches for improving this balance by means of integrated experimental-computational strategies are still lacking. Future developments will be needed for comprehensive collection and harmonization of systems-wide target selectivity data, enabling better utilization and control for multi-targeted activities in the drug development process. Additional areas of future developments include model-based strategies for drug combination screening and improved pre-clinical validation options with animal models.

Genome-wide off-targets of drugs: risks and opportunities

“…We argue that a careful dissection of parameters quantifying efficacy, toxicity, and synergy of multi-targeting mono-and combinatorial therapies in pre-clinical model systems, such as PDOs, is critical for developing safe and effective therapeutic regimens for cancers and other diseases. In addition to the in vitro or ex vivo model systems, there is also a need for flexible computational platforms that can speed up the early investigation of both the therapeutic and toxic effects of small molecules before entering into lengthy and costly animal or clinical studies (Ravikumar and Aittokallio 2018). Such in silico tools and databases should be computationally efficient to allow their implementation into an HTS pipeline, and easily usable also by non-computational researchers, to enable their wide application among the drug screening community.…”

Predicting target profiles with confidence as a service using docking scores

“…Determining ligand-target binding is a vital part of the drug discovery process [ 1 ]. A ligand can bind to multiple target proteins [ 2 ] and may cause off-target effects [ 3 , 4 ]. Knowing the off-target effects of drugs can be beneficial especially in the initial stages of drug discovery.…”

Modelling bioactivities of combinations of whole extracts of edibles with a simplified theoretical framework reveals the statistical role of molecular diversity and system complexity in their mode of action and their nearly certain safety

“…They hold promises for overcoming safety and efficacy pitfalls of single compound based therapeutic intervention [ 5 – 7 ]. Combinations of isolated synthetic or natural chemicals raises many safety issues, and for novel chemical entities, medicinal chemistry and regulatory bottlenecks are foreseeable [ 8 , 9 ]. A polypharmacological alternative to combinations of drugs and/or purified natural compounds may be found in the use of (extracts of) whole edibles and mixes thereof, which form readily available complex mixes of natural compounds [ 10 ].…”