Abstract
Promiscuous inhibition due to aggregate formation has been recognized as a major concern in drug discovery campaigns. Here, we report some aggregators identified in a virtual screening (VS) protocol to search for inhibitors of human ecto-5′-nucleotidase (ecto-5′-NT/CD73), a promising target for several diseases and pathophysiological events, including cancer, inflammation and autoimmune diseases. Four compounds (A, B, C and D), selected from the ZINC-11 database, showed IC50 values in the micromolar range, being at the same time computationally predicted as potential aggregators. To confirm if they inhibit human ecto-5′-NT via promiscuous mechanism, forming aggregates, enzymatic assays were done in the presence of 0.01% (v/v) Triton X-100 and an increase in the enzyme concentration by 10-fold. Under both experimental conditions, these four compounds showed a significant decrease in their inhibitory activities. To corroborate these findings, turbidimetric assays were performed, confirming that they form aggregate species. Additionally, aggregation kinetic studies were done by dynamic light scattering (DLS) for compound C. None of the identified aggregators has been previously reported in the literature. For the first time, aggregation and promiscuous inhibition issues were systematically studied and evaluated for compounds selected by VS as potential inhibitors for human ecto-5′-NT. Together, our results reinforce the importance of accounting for potential false-positive hits acting by aggregation in drug discovery campaigns to avoid misleading assay results.
Highlights
Virtual screening (VS) and high-throughput screening (HTS) approaches have been well established as the main techniques for identification of bioactive compounds as potential drug candidates from large chemical libraries [1,2,3,4], showing significant success rates
To search for novel potential human ecto-5′-NT inhibitors, a virtual screening (VS) consisting of two consecutive filters was performed
Aggregation kinetic studies were done, for one of model consists of five chemical features: one aromatic ring, one hydrogen bond donor and three them,hydrogen by dynamic light scattering (DLS)
Summary
Virtual screening (VS) and high-throughput screening (HTS) approaches have been well established as the main techniques for identification of bioactive compounds as potential drug candidates from large chemical libraries [1,2,3,4], showing significant success rates. Currently it is well recognized that many screened hits are further recognized as not truly actives against their specific biological targets [5,6,7,8] These compounds, usually termed “false hits” or “false positives”, act by a variety of mechanisms, including covalent protein reactivity, redox cycling, absorbance and/or fluorescence assay interference, membrane disruption, metal complexation, decomposition in assay buffers and formation of aggregates [8,9,10]. Their activities do not depend on specific interactions. Compounds classified in the literature as “aggregators” are usually not suitable as drug candidates and their early identification can contribute to save time and money in drug discovery projects [5,6,12]
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