Publication details
Tunnel detection in protein structures using sampling-based motion planning
| Authors | |
|---|---|
| Year of publication | 2017 |
| Type | Article in Proceedings |
| Conference | Robot Motion and Control (RoMoCo), 2017 11th International Workshop on |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1109/RoMoCo.2017.8003911 |
| Field | Informatics |
| Keywords | Protein;tunnel;motion planning;molecular dynamics |
| Description | Proteins are involved in many biochemical processes. Behavior and properties of proteins as well as other bio-macromolecules is influenced by internal void space such as tunnels or cavities. Tunnels are paths leading from an active site inside the protein to its surface. Knowledge about tunnels and their evolution in time provides an insight into protein properties (e.g., stability). Motion planning methods, especially sampling-based techniques like Rapidly Exploring Random Tree (RRT), can be used to find the tunnels by sampling the corresponding configuration space. Void space of proteins is however very limited, which may decrease ability of RRT to find a solution due to the narrow passage problem. In this paper, we propose to generate the random samples around a subset of vertices of Voronoi Diagram of the atoms. The subset is maintained automaticaly to support generation of samples on multiple paths of VD simultaneously. |