A New Method for Protein Conformation Prediction Using Robotics Methods

Proteins are the most abundant organic components of human body and in many ways the most important. They naturally perform their essential functions by conformation between two major positions called native and denatured configurations [1]. The computationally efficient prediction of this conformation is one of the most challenging scientific problems of the present century. To fully understand the biological performance of proteins, ability of precise prediction of their native configuration is of quite importance which can be followed by protein design and its applications in Bio-Nanorobotics, Drug design, etc [2].The goal of this research is modeling and simulation of proteins native configuration from an arbitrary position using current methods in robotics which might be computationally more efficient than the alternative methods such as molecular dynamics.In this way first of all a direct kinematics algorithm is needed and the method used here is the Zero Reference Position Notation (ZRPN) developed by Gupta [3]. Forces, torques and the global energy of the molecules are calculated using Amber force field [4]. And finally a common robotic method is used to model the bonds as revolute joints and computing their equivalent torques which will perform the conformation.