Stochastic Model of Protease-Ligand Reactions

Prediction of protein tertiary structure based on amino acid sequence is one of the most challenging open questions in computational molecular biology. The two most common experimental methods for determining protein structure, X-ray crystallography and nuclear magnetic resonance (NMR) are both relatively expensive and time consuming processes. Further, some proteins (such as largely hydrophobic membrane integral proteins) are resistant to crystallization. Thus, computational approaches for determination of protein conformation are an attractive alternative to experimental procedures. While many such algorithms exist, none can yet achieve the same accuracy and reliability as experimental structure determination techniques. The objective of this research is to combine experimental evidence with computational modeling for high-confidence structure prediction. Limited proteolysis and chemical modification data is used to drive the modeling process towards physically realizable structures. Here we present a stochastic simulation of a limited proteolysis experiment that models the behavior of a protease-ligand reaction at an abstracted molecular level. The results of this simulation will be used to validate rate constant prediction methods that will then be used for the selection and refinement of candidate models for computational structure determination