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Combining virtual and high-throughput screening in the discovery of new cruzain inhibitors


Cruzain's importance as a therapeutic target for Chagas Disease has been well established, and there is a continuous effort to find inhibitors for this cysteine protease. Here I describe the use of both virtual and high throughput screening, followed by medicinal chemistry optimization, to identify and diversify inhibitors of cruzain.

In the first study, reported in Chapter 1, virtual screening of the ZINC lead-like database led to the identification of two novel scaffolds of non-covalent cruzain inhibitors. Medicinal chemistry optimization of the most potent hit (Ki = 64 µM) resulted in a SAR series that included nanomolar inhbitors. However, more detailed studies on the most potent compounds revealed that they were aggregators. This study demonstrates for the first time an SAR due to aggregation. It is therefore a warning on the danger of considering SAR as definitive evidence for a specific mechanism of inhibition.

Chapters 2-4 describe a collaboration with the NIH Chemical Genomics Center. We prospectively docked their 197,861 compound library, while they experimentally tested it versus cruzain by HTS. By running this side to side comparison, we were able to determine the main sources of false positives in HTS, to optimize a series of covalent reversible inhibitors found by HTS, and to evaluate in detail the false positives and false negatives from docking. Furthermore, five classes of non-covalent inhibitors were found, three of which were predicted by top scores in the dock ranked library. This study therefore indicates the potential for using virtual screening results to prioritize HTS hits.

The work described here led to the identification of seven new classes of non covalent and one class of potent covalent reversible cruzain inhibitors. In addition, two high resolution crystal structures of this enzyme in complex with the new inhibitors were solved. Finally, this work highlights important lessons on the danger of simply interpreting SAR data, the false positives than can arise from HTS and docking, and the false negatives derived from docking.

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