• Maria Denk

Flagging Problematic Compounds in Drug Discovery

Updated: Oct 20

Why poorly behaved compounds can mislead you in your projects

In drug discovery, compounds are predominantly synthesized and characterized in organic solvents, while their biological activity is tested exclusively in aqueous media. Drugs behave differently when they are dissolved in organic solvents versus aqueous media. If not examined early-on, misbehaving compounds may lead to misleading structure activity relationships (SAR) and potential delays in drug discovery programs. Hence, characterizing a compound’s physicochemical properties in aqueous media is crucial—its solution behavior can have a significant impact on chemical, biochemical, pharmacological and in vivo activities.

What exactly is compound behavior/solution behavior?

Compound behavior (CB) investigates the types of nano-entities formed when a compound is dissolved, typically in an aqueous solution. It is not unusual for compounds to be fully soluble in dimethylsulfoxide (DMSO) but not in aqueous buffers. Highlighted in Ayotte et al., compounds take on a multi-phase equilibrium when they are in an aqueous media, which may comprise a mixture of lone molecules, self-associating aggregate states, and solid phases[1].

Figure 1: Overview of the multiphase equilibria compounds may take when dissolved in aqueous media. Figure modified from Ayotte et al. [1].

To summarize, when a molecule is dissolved in an aqueous solution it can take on one or more of many forms as highlighted in the figure above. A compound with good solution behavior is one that is fully soluble—i.e. all molecules are monomeric (alone) and tumble freely in solution. When a proton NMR spectrum is taken in an aqueous solution, these molecules usually have sharp peaks. Compounds with poor compound behaviors can be divided into two main categories 1) aggregators and 2) insoluble compounds/precipitators. Abnormal NMR spectra are observed in both of these cases: these range from spectra with unusually small and/or broad signals to those with virtually no signals due to extensive proton NMR signal broadening.

So, what is the difference between a poorly soluble compound and an aggregate?

Poorly soluble compounds may escape the solution by forming a precipitate either instantly or over time—these compounds are often easy to detect by visual inspection. Due to limited solubility, the proton NMR signals in the spectra of these compounds may either be virtually non-existent due to significant signal broadening or may be very small if the compound is at least partially soluble.

On the other hand, aggregates are self-associating entities, which can range from dimers to small multimers to larger self-associated particles like micelles or colloids. Aggregators may appear to be soluble by visual inspection: there is no visible precipitate formed. However, when an NMR spectrum of an aggregating compound is taken, the resonances may range from unexpectedly small and/or broad signals to virtually no signals at all. The appearance and shape of the NMR peaks can be correlated to the size of the aggregate.

Why should I care about aggregation?

Figure 2: Analysis of 124 compounds to investigate a potential association between aggregation and promiscuity. Data adapted from this article[2].

Here, an aggregator is defined as a compound with abnormal spectral observations using NMR spectroscopy and a well-behaved compound is one with normal spectral trends. A promiscuous compound is defined as one that inhibits >50% at 10 µM in 3 or more off-target assays, and a non-promiscuous one as one that inhibits >50% at 10 µM in 2 or less off target assays. A) Breakdown of the 124 compounds tested for the association between aggregators and promiscuous compounds and B) Correlation between aggregation status and promiscuity for 124 compounds based on A)

It should be noted that 97% of drugs tested in oncology clinical trials never advance to receive FDA approval, with lack of efficacy and dose-limiting toxicities being the most common causes of failure[3]. Toxic outcomes can result from unintended interactions with proteins other than the target. A recent study showed that many of the failed oncological drug-candidates targeted non-essential proteins for cancer proliferation and the primary mechanism of cell death was through off-target effects[3].

Aggregates are one of the primary sources of off-target pharmacological effects and can give rise to false positives in screening and binding studies [2]. In a 2013 publication, LaPlante and co-authors analyzed 124 compounds by NMR spectroscopy and by off-target pharmacological assays to investigate any correlation between aggregating compounds and promiscuity[2]. It was found that there was an 84% agreement between a compound’s behavior and promiscuity: aggregating compounds were more likely to be promiscuous, and non-aggregators were less likely to be promiscuous.

Ignoring the solution behavior properties of compounds during their design and discovery may lead to misinterpretation of their effects on a specific target and may be an invitation to future off-target effects. Bringing “misbehaved compounds” from an early to a later-stage of a discovery program is sometimes a source of years of misled research. Hence, it is crucial to flag these compounds and de-prioritize them to avoid the costly advancement of potentially promiscuous and toxic drugs. The solution behavior of a drug-candidate can have a massive influence on how successful, specific, and efficacious it may be as a drug.

How is aggregation detected?

Part of the challenge of assessing aggregates is that they do not get caught by typical methods of testing solubility such as HPLC, or by simple visual inspection. There are assays where detergents are added to “de-aggregate” a problematic compound to confirm aggregation. However, we have found that not all aggregates are sensitive to detergents, hence it may not be an all-encompassing method. Thus, it is important to use a combination of methods that can detect all types of aggregators.

On the other hand, NMR spectroscopy can be a simple, and all-encompassing method to detect and/or flag the potential existence of aggregates. Since NMR investigates the relaxation parameters of molecules which are directly related to tumbling time, one can probe a compound’s state in solution using specific experiments. From a simple 1D experiment in buffer, one can estimate the real concentration of the entity in solution and check for potential aggregation by looking at the peak intensity/shape. With other more advanced NMR assays, properties such as dynamics, tumbling time and much more can be revealed and utilized for characterization of a compound’s oligomeric-state and its behavior in solution.

There are various state-of-the art methods that NMX uses to examine compound aggregation, which will be discussed in a future blogpost. To help your drug discovery efforts, we offer a variety of services to characterize aggregation by NMR which can be found here. If you have any questions about our services to assess compound behavior or this blog post, or suggestions for future blog posts, please use the contact form to get in touch with us.


(1) Ayotte, Y.; Marando, V. M.; Vaillancourt, L.; Bouchard, P.; Heffron, G.; Coote, P. W.; Larda, S. T.; LaPlante, S. R. Exposing Small-Molecule Nanoentities by a Nuclear Magnetic Resonance Relaxation Assay. J. Med. Chem. 2019, 62 (17), 7885–7896. https://doi.org/10.1021/acs.jmedchem.9b00653.

(2) LaPlante, S. R.; Aubry, N.; Bolger, G.; Bonneau, P.; Carson, R.; Coulombe, R.; Sturino, C.; Beaulieu, P. L. Monitoring Drug Self-Aggregation and Potential for Promiscuity in Off-Target In Vitro Pharmacology Screens by a Practical NMR Strategy. J. Med. Chem. 2013, 56 (17), 7073–7083. https://doi.org/10.1021/jm4008714.

(3) Lin, A.; Giuliano, C. J.; Palladino, A.; John, K. M.; Abramowicz, C.; Yuan, M. L.; Sausville, E. L.; Lukow, D. A.; Liu, L.; Chait, A. R.; Galluzzo, Z. C.; Tucker, C.; Sheltzer, J. M. Off-Target Toxicity Is a Common Mechanism of Action of Cancer Drugs Undergoing Clinical Trials. Sci. Transl. Med. 2019, 11 (509), eaaw8412. https://doi.org/10.1126/scitranslmed.aaw8412.