Most physics based simulations of protein docking and related problems are seen to have very high time and space requirements. For example, a naive implementation of protein docking would require 6 degrees of freedom to be matched, leading to at least O( N⁶ ) time complexity for N grid points. The grids inherently will need O( n³ ) space requirements for a cube of side n.

There exist many previous works on protein docking, which improve the trivial bounds by using other representations like Fourier and Spherical Harmonics, Wavelets etc. At CCV, we are trying to develop new algorithms based on hierarchical grids which would prove to be extremely space and time efficient compared to the previous algorithms.

We are mainly focusing on the more difficult problem of protein docking of flexible molecules. proteins are seen to be extremely flexible and dynamic in nature. Atomic fluctuations, side chain and loop motions, helix motions, disassociations and associations, and folding and unfolding are some of the motions commonly seen.

Some of the guidelines we use in our decisions are

• Visualization and correct representation of the three dimensional structure of proteins ( which could be dynamic in time ) helps scientists in discovery and exploration of new techniques for different problems including protein docking.
• Flexible models are a better representation for protein interactions than rigid body structures
• Animation of models, where bonds are classified according to the number and range of degrees of freedoms is needed to perform adaptive simulations.
• User interaction in choosing configurations,  initial conditions for docking by allowing representations which can be steered through visualization is important.

There are two different approaches to animation which can be taken

• Skeletal based animation
• Volumetric animation

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