Research Article
Distinguish protein decoys by Using a scoring function based on a new AMBER force field, short molecular dynamics simulations, and the generalized born solvent model
Mathew C. Lee,
Yong Duan,
Mathew C. Lee
Department of Chemistry and Biochemistry and Center of Biomedical Research Excellence in Structural and Functional Genomics, University of Delaware, Newark, Delaware
Search for more papers by this authorCorresponding Author
Yong Duan
Department of Chemistry and Biochemistry and Center of Biomedical Research Excellence in Structural and Functional Genomics, University of Delaware, Newark, Delaware
Department of Chemistry and Biochemistry and Center of Biomedical Research Excellence in Structural and Functional Genomics, University of Delaware, Newark, DE 19716===Search for more papers by this authorMathew C. Lee,
Yong Duan,
Mathew C. Lee
Department of Chemistry and Biochemistry and Center of Biomedical Research Excellence in Structural and Functional Genomics, University of Delaware, Newark, Delaware
Search for more papers by this authorCorresponding Author
Yong Duan
Department of Chemistry and Biochemistry and Center of Biomedical Research Excellence in Structural and Functional Genomics, University of Delaware, Newark, Delaware
Department of Chemistry and Biochemistry and Center of Biomedical Research Excellence in Structural and Functional Genomics, University of Delaware, Newark, DE 19716===Search for more papers by this authorAbstract
Recent works have shown the ability of physics-based potentials (e.g., CHARMM and OPLS-AA) and energy minimization to differentiate the native protein structures from large ensemble of non-native structures. In this study, we extended previous work by other authors and developed an energy scoring function using a new set of AMBER parameters (also recently developed in our laboratory) in conjunction with molecular dynamics and the Generalized Born solvent model. We evaluated the performance of our new scoring function by examining its ability to distinguish between the native and decoy protein structures. Here we present a systematic comparison of our results with those obtained with use of other physics-based potentials by previous authors. A total of 7 decoy sets, 117 protein sequences, and more than 41,000 structures were evaluated. The results of our study showed that our new scoring function represents a significant improvement over previously published physics-based scoring functions. Proteins 2004. © 2004 Wiley-Liss, Inc.
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