ProtPOS: a python package for the prediction of protein preferred orientation on a surface

Area of Science:

• Computational biology
• Biophysics
• Materials science

Background:

• Atomistic molecular dynamics (MD) simulations are vital for understanding protein-surface interactions in biotechnology.
• Accurate simulation of protein adsorption requires predicting favorable protein orientations at the surface.
• Current methods may lack efficiency or flexibility in determining these orientations.

Purpose of the Study:

• To introduce ProtPOS, a novel Python package for predicting low-energy protein orientations on surfaces.
• To provide a user-friendly tool that facilitates the setup of protein-surface adsorption simulations.
• To enable researchers to select appropriate force fields for their specific simulation systems.

Main Methods:

• ProtPOS integrates a rapid conformational sampling algorithm with GROMACS for energy calculations.
• The package utilizes atomistic molecular dynamics principles.
• It allows for the selection of user-defined force fields.

Main Results:

• ProtPOS successfully predicts low-energy protein orientations on various surfaces.
• The generated structural outputs are directly usable for subsequent simulation studies.
• The package offers a lightweight and accessible solution for orientation prediction.

Conclusions:

• ProtPOS enhances the efficiency and success rate of protein-surface adsorption simulations.
• It serves as a valuable tool for researchers in biotechnology and computational biophysics.
• The flexibility in force field selection makes ProtPOS adaptable to diverse research needs.