Using Solid Angles to Detect Protein Docking Regions by CUDA Parallel Algorithms

A novel approach based on solid angles and CUDA parallel technologies for detection of protein docking regions is proposed in this paper. A key feature of a solid angle reveals the geometrical characteristics of protein surface structures and provides an efficient criterion for identifying the anchor amino acids on surface regions. These solid angles as well as several corresponding physical properties facilitate rapid evaluation on matching shape complementary from two interactive proteins. According to the performance of the proposed algorithms on enzyme-inhibitor protein complexes, the retrieved and clustered potential docking regions and the counterpart of centralized anchor amino acids can be effectively determined. Most of identified candidate regions on protein surfaces reveal either with concave or convex characteristics, and the results conform to the regular conditions of protein docking phenomena with respect to enzyme-inhibitor complexes. More importantly, the main goal of this paper not only identifies possible protein docking regions by evaluating solid angle characteristics, but also provides a feasible and efficient way to identify possible binding regions by employing the CUDA parallel computing architecture. The system evaluation has shown that the proposed algorithms achieved an accuracy rate of 62.85% for identifying possible docking regions on two interacted proteins and an average of one-half saving in running time requirements by incorporating CUDA parallel algorithms.