Internal:GPCD

Introduction

Cavities are structural features of proteins and they are often important for drug discovery and design. There are different kinds of cavities, including pockets, voids, tunnels, and channels. The types of cavities are listed in more detail in figure 1.

Figure 1: The basic types of protein cavities [1]

1. Void: A cavity that looks like internal "hole" in a protein with no connection to the surface.

2. Cleft: A pocket that looks like a small "dent" in the surface of a protein. Can also be found as part of a tunnel or channel.

3. Invagination: A pocket that looks like a "cove". It has a small opening on the surface of a protein and leads to a larger interior. Can also be found as part of a tunnel or after a cleft.

4. Tunnel: A pocket that has an opening on the surface of a protein and leads to somewhere in the interior. Has no opening on the other side.

5. Channel: A cavity that has an opening on one side of the surface of a protein and leads to another opening in another location on the surface of the protein.

Of course, the types of cavities listed in figure 1 are only the basic ones. Combinations of these are also possible as shown in figure 2.

Figure 2: Combination types of protein cavities [1]

There are several methods for detecting protein cavities. There are sphere based methods, grid based methods, grid-and-sphere based methods, surface based methods, grid-and-surface based methods, time-varying methods, GPU based methods, consensus based methods, and finally tessellation based methods. These algorithms are shown in more detail in figure 3. Tessellation based methods mainly rely on Voronoi tessellation. Some methods rely on weighted Voronoi tessellation because of its ability to more accurately represent the volume of atoms. The Voronoi tessellation in these methods is computed from a set of points representing the atomic centers of the underlying protein.

Figure 3: A hierarchy of protein cavity detection algorithms [1]

References

[1] APA Simões, T., Lopes, D., Dias, S., Fernandes, F., Pereira, J., Jorge, J., Bajaj, C., & Gomes, A. (2017). Geometric Detection Algorithms for Cavities on Protein Surfaces in Molecular Graphics: A Survey. Computer graphics forum : journal of the European Association for Computer Graphics, 36(8), 643–683. https://doi.org/10.1111/cgf.13158