Cryo-EM for Small Molecules Discovery, Design, Understanding, and Application

Abstract

We present a perspective of our view of the application of cryoelectron microscopy (cryo-EM) to structure-based drug design (SBDD). We discuss the basic needs and requirements for SBDD, the current state of cryo-EM, and the challenges that need to be overcome for this technique to reach its full potential in facilitating the process of drug discovery.

Keywords: automation; cryo-EM; structure-based drug discovery.

Figure 1:

Schematic representation of the drug discovery and development process. The areas in the R&D process where structural information can be used are highlighted. In the Target ID space, one structure may be sufficient to identify the target binding site and characterize its mechanism. During the Hit ID stage, a few structures may be required to structurally characterize the lead compounds identified during screening. If a robust structural system is in place, X-ray can be used to run fragment screening campaigns. The heaviest request for structural data happens at the Lead ID/Opt stage, in which several iterations (from compound synthesis to structure/acitivity to SBDD back to synthesis) may happen in few weeks.

Figure 2.

Timeline for CryoEM structure determination. The figure shows the timeline from data collection to a 2.5Å structure for a well behaved aldolase sample (unpublished results, Ed Eng et al.. NYSBC). Steps from data collection to particle picking are almost all fully automated and require minimal user input (Suloway, et al., 2005) (Lander, et al., 2009). Reconstruction was carried out with Cryosparc (Punjani, et al., 2017).

Figure 3.

Sample preparation. The figure shows a comparison between a grid vitrified using a standard plunger (top) and a grid prepared using SpotItOn (Jain, et al., 2012) (Razinkov, et al., 2016), bottom. In the grid vitrified with the standard plunger the ice distribution is highly variable across the grid, and identification of suitable areas for data collection can be a lengthy process. In the SpotItOn grid, one single narrow strip of very uniform ice is visible and almost every square in the stripe is available for data collection.

Figure 4:

Analysis of EM maps deposited in the EMDB. Left: trend of released maps achieving given resolution levels (as of December 2017). Right: as of December 2017, 645 maps at a resolution of 4 Å or better were deposited in the EMDB (red shaded area). These included 69 maps better than 3 Å and 12 at a resolution greater than 2.5 Å. During January 2018, 27 maps better than 4 Å and 6 better than 3.0 Å were added to the EMDB.

Figure 5:

Using cryoEM structures to guide structure based drug design. A) Density for the antimalaria mefloquine as visualized in the 3.2 Å cryoEM map (Panel A and B were generated with PyMol, from map EMD-8576 and PDB 5UMD). B) The structure revealed an empty pocket within the ligand binding site (red circle). C) Structure guided design of modified mefloquine, with the piperidine replaced by a larger substituents, resulted in derivatives with a ~2-fold fold potency enhancement towards the parasite (Wong, et al., 2017).