Bioinformatics methods can considerably aid clinical research, providing very useful insights and predictions working at the molecular level in fields like Virtual Screening, Molecular Dynamics and Protein Folding. However, the successful application of such methods is drastically limited by the computational resources required, particularly, whenever they deal with accurate biophysical models. A leading example of this computational issue is the calculation of the solvent accessible surface area (SASA).

We present a novel method called MURCIA (Molecular Unburied Rapid Calculation of Individual Areas) that takes advantage of the last generation of massively parallel Graphics Processing Units (GPUs) to considerably enhance SASA calculations. Up to the moment, MURCIA is one of the fastest methods available in a wide range of molecular sizes (tested with up to millions of atoms), and also provide a good framework for the acceleration of the visualization of molecular surfaces in standard molecular graphics programs.



  • You need a NVIDIA CUDA capable device in order to execute MURCIA.
  • You must have the NVIDIA driver for your graphic card installed.
  • You must have NVIDIA CUDA Toolkit installed.
  • You must have NVIDIA CUDA SDK installed under your home folder: $(HOME)/NVIDIA_GPU_Computing_SDK.
  • In, you can download the packages you need.
  • Please visit NVIDIA CUDA GPU Computing documentation in:

and follow its installation instructions.

Once you have CUDA installed, just go to the main MURCIA folder and type “make”. The MURCIA executable will be placed in .bin/murcia.



Zhang, Q., Wang, J., Guerrero, G.D., Cecilia, J.M., García, J.M., Li, Y., Pérez-Sánchez, H. and Hou, T., 2013. Accelerated conformational entropy calculations using graphic processing units. Journal of chemical information and modeling53(8), pp.2057-2064.