Minimal Python wrapper for the msms program

This is a Python wrapper for the msms command-line program developed by Dr. Michel F. Sanner. It can be used to compute triangulated solvent-excluded surfaces of molecules, as well as their solvent-accessible surface (SAS), solvent excluded surface (SES), and molecular volume.

Note: While this wrapper is under the MIT licence, msms is not. This is an independent project and not affiliated to the msms program. You can obtain msms from https://ccsb.scripps.edu/msms/. For more information about the algorithm, see:

Sanner, M. F., Olson A.J. & Spehner, J.-C. (1996). Reduced Surface: An Efficient Way to Compute Molecular Surfaces. Biopolymers 38:305-320.

Functionality

If you have msms installed on your computer, you can use this package as a Python interface for its basic functionality. Supported features include

• obtaining a triangulated surface based on atomic positions and radii.
• obtain the SAS, SES, and molecular volume.

Installation

The wrapper is a single file (msms/wrapper.py), which you can copy into one of your folders/projects. Alternatively, download this repository and run pip install ..

Usage

Use msms to compute the surface area of a unit sphere.

• The SES and SAS are analyical.
• The volume is numerical. In the case of a single sphere, it is always too small, but converges with high density.

xyz = [[0., 0., 0.]]
radii = [1.]
print('expected SES', 4*np.pi)
print('expected SAS', 4*np.pi * 2.5**2) # 2.5 = radius + probe_radius
print('expected volume', 4/3*np.pi)
msms.run_msms(xyz, radii, density=2).extract_ses_sas_vol()

Output:

expected SES 12.566370614359172
expected SAS 78.53981633974483
expected volume 4.1887902047863905

SizeDescriptors(ses=12.566, sas=78.54, volume=3.082)

Triangulated surfaces

• run_msms returns a MsmsOutput object.
• Convenience functions: get_vertex_positions, get_vertex_normals, and get_face_indices return numpy arrays with the most important data.
• structured numpy arrays: the .vertices and .faces attributes of MsmsOutput contain structured numpy arrays that contain basically all information in the .vert and .face files.

Further examples

See examples.ipynb