DocumentCode :
2583405
Title :
Stochastic model of protease-ligand reactions
Author :
Anderson, Paul ; Raiford, Douglas ; Sweeney, Deacon ; Doom, Travis ; Raymer, Michael
Author_Institution :
Dept. of Comput. Sci. & Eng., Wright State Univ., Dayton, OH, USA
fYear :
2005
fDate :
19-21 Oct. 2005
Firstpage :
306
Lastpage :
310
Abstract :
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.
Keywords :
biochemistry; biology computing; enzymes; molecular biophysics; molecular configurations; physiological models; stochastic processes; X-ray crystallography; amino acid sequence; chemical modification; computational modeling; computational molecular biology; high-confidence structure prediction; largely hydrophobic membrane integral proteins; limited proteolysis; nuclear magnetic resonance; protease-ligand reactions; protein conformation; protein tertiary structure; rate constant prediction; stochastic model; Amino acids; Biological system modeling; Biology computing; Computational biology; Computational modeling; Nuclear magnetic resonance; Predictive models; Proteins; Sequences; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Bioengineering, 2005. BIBE 2005. Fifth IEEE Symposium on
Print_ISBN :
0-7695-2476-1
Type :
conf
DOI :
10.1109/BIBE.2005.52
Filename :
1544486
Link To Document :
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