A Stochastic model to estimate the time taken for Protein-Ligand Docking

Abstract— Quantum mechanics and molecular dynamic simulation provide important insights into structural configurations and molecular interaction data today. To extend this atomic/molecular level capability to system level understanding, we propose an “in silico” stochastic event based simulation technique. This simulation characterizes the time domain events as random variables represented by probabilities. This random variable is called the execution time and is different for different biological functions (e.g. the protein-ligand docking time). The simulation model requires fast computational speed and we need a simple transformation of the energy plane dynamics of the molecular behavior to the information plane. We use a variation of the collision theory model to get this transformation. The velocity distribution and energy threshold are the two parameters that capture the effects of the energy dynamics within the cell in our model. We use this technique to approximately dete...

• Type: Conference
• Year: 2006
• Where: CIBCB
• Authors: Preetam Ghosh, Samik Ghosh, Kalyan Basu, Sajal K. Das, Simon Daefler
• Keywords: CIBCB 2006, Model, Molecular Dynamic Simulation, Random Variable