In drug discovery, compound promiscuity and selectivity refers to the ability of drug compounds to bind to several different- (promiscuous) or only one main target (selective). An important distinction here is that promiscuity is defined as specific interactions with multiple biological targets (polypharmacology) rather than a number of non-specific targets. At first glance, you might expect drugs to be designed to be as selective as possible, only hitting one biological target necessary to treat the disease and therefore reduce the chance of any side effects. This paradigm of single-target specificity has been challenged over the past two decades. Even between scientists in the drug discovery field, compound promiscuity is still a controversial topic. The field has increasingly paid attention to the topic of polypharmacology and studies have shown many pharmaceutically relevant compounds, including approved drugs to derive their biological activity from polypharmacology [1-3].
One large issue when evaluating compound promiscuity is Data incompleteness. Since it is almost impossible to fully screen drugs for activity against all possible targets, the full breadth of drug promiscuity of existing compounds is not complete. Estimates place the average number of interaction targets for drugs to 3-13 targets which is an extremely large spectrum. [4-6] This data has led part of the field to completely reject the single-target hypothesis and turn the idea around to suggest that drugs should generally be promiscuous.[6] However, given the uncertainty and added complexity that stems from working with promiscuous compounds, it is understandable that the topic remains divisive.
One extremely interesting trend in drug discovery is the development of relative compound promiscuity throughout the drug discovery process as shown in Figure 1 [7].
This graph is why I decided to blog about this topic. It is a very good argument for the promiscuity hypothesis. It shows the tendency of chemists to design their lead compounds to be more specific which explains the dip in promiscuity at stage 2. However, (given the promiscuity hypothesis is correct) compounds that aren’t promiscuous aren’t as promising as drug candidates and are therefore not taken forward in the discovery process which leads to an increase in promiscuity up to the approved drugs that are the most promiscuous in the cycle. Whether this is a case of survivorship bias where only promiscuous compounds make good drugs or another underlying trend would be an interesting question to answer.
If you want to learn more about the trends in drug discovery concerning compound promiscuity then I highly recommend the review by Hu et al.[7] that has some nice metadata like the above figure to show broader trends in the industry.
Citations
[1] Paolini GV, Shapland RH, van Hoorn WP, Mason JS, Hopkins AL (2006) Global mapping of pharmacological space. Nat Biotechnol 24: 805-815.
[2] Boran AD, Iyengar R (2010) Systems approaches to polypharmacology and drug discovery. Curr Opin Drug Discov Devel 13: 297-309.
[3] Mestres, J.; Gregori-Puigjané , E.; Valverde, S.; Solé , R. V. The Topology of Drug-Target Interaction Networks: Implicit Dependence on Drug Properties and Target Families. Mol. Biosyst. 2009, 5, 1051−1057.
[4] Gilberg, E.: Bajorath, J. Recent Progress in Structure-Based Evaluation of Compound Promiscuity. ACS Omega 2019, 4, 2758−2765.
[5] Mestres, J.; Gregori-Puigjané , E.; Valverde, S.; Solé , R. V. The Topology of Drug-Target Interaction Networks: Implicit Dependence on Drug Properties and Target Families. Mol. Biosyst. 2009, 5, 1051−1057.
[6] Mestres, J.; Gregori-Puigjane, E.; Valverde, S.; Sole, R. V. Data Completeness − The Achilles Heel of Drug-Target Networks. Nat. Biotechnol. 2008, 26, 983−984.
[7] Hu, Y.: Gupta-Ostermann, D.: Bajorath, J. Exploring Compound Promiscuity Patterns and Multi-target Activity Spaces. Comput Struct Biotec. 2014, 9: e201401003.
