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Applying PlayMolecule® CrypticScout in fragment screening experiments

Frequent users of PlayMolecule may already be familiar with CrypticScout [1], Acellera’s mixed solvent MD application for finding cryptic pockets and druggable sites in proteins, where the target protein is solvated in a water box with a molecular probe at a certain concentration. The molecular probes used are typically small and fragment-like, so that the binding kinetics to cryptic pockets are fast, and thus require less simulation time.

Today we want to present to you the updated version of CrypticScout, particularly aimed at fragment screening analysis. The application still performs the same mixed solvent simulations, but the posterior simulation analysis has been improved. CrypticScout’s previous analysis was limited to detecting only hotspots and open pockets, and it was not detailed enough to detect stable interactions between the protein and the molecular probes. We have redesigned the analysis pipeline in order to better detect those stable interactions. CrypticScout now looks for intervals of time during the simulation trajectory where a fragment molecule forms stable interactions with the protein. After that, all identified poses are ranked depending on residence time.

To showcase the power of CrypticScout’s new analysis protocol, we have prepared two examples, each one featuring one target protein and one fragment-like molecular probe. A fragment-screening is better done with several different molecular probes, but for the sake of simplicity we have limited today’s examples to only one fragment per target. The first example is HRAS, an oncogenic protein and common target for cancer therapies. More precisely, we have used a crystal structure of HRAS bound to GDP as a starting point (PDB: 4Q21). For the first example, more of a control, we used imidazopyridine as our fragment probe (which is very similar to guanine’s nucleobase). From the extracted poses coming from CrypticScout’s new analysis, we were able to detect a binding pose very similar to the GDP-bound pose.

In the second example, we used the crystal structure of Hsp90 bound to a Benzamide-based compound (PDB: 3D0B). Again, for simplicity, we chose benzamide as the fragment probe. Interestingly, this time we were not only able to identify the binding pose of the benzamide part of the compound, but also to locate the hydrophobic regions participating in the binding interaction.

You can check out the predicted poses, as well as the trajectories, in here. CrypticScout application is freely available at using public resources. For private installation, please get in touch with us at Acellera.

We look forward to receiving your comments on the new CrypticScout analysis!


  • [1] Martinez-Rosell, Gerard, et al. “PlayMolecule CrypticScout: Predicting Protein Cryptic Sites Using Mixed-Solvent Molecular Simulations.” Journal of Chemical Information and Modeling 60.4 (2020): 2314–2324.



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