Statistical potential for assessment and prediction of protein structures
University of California, San Francisco · NGM Biopharmaceuticals (United States) · +1 more institution
Abstract
Protein structures in the Protein Data Bank provide a wealth of data about the interactions that determine the native states of proteins. Using the probability theory, we derive an atomic distance-dependent statistical potential from a sample of native structures that does not depend on any adjustable parameters (Discrete Optimized Protein Energy, or DOPE). DOPE is based on an improved reference state that corresponds to noninteracting atoms in a homogeneous sphere with the radius dependent on a sample native structure; it thus accounts for the finite and spherical shape of the native structures. The DOPE potential was extracted from a nonredundant set of 1472 crystallographic structures. We tested DOPE and…
Citation impact
- FWCI
- 16.08
- Percentile
- 100%
- References
- 113
Authors
2Topics & keywords
- Decoy
- Native state
- Algorithm
- Set (abstract data type)
- Computer science
- RADIUS
- Protein structure
- Biological system