title: Conventional NMA as a better standard for evaluating elastic network models.
abstract: Normal mode analysis (NMA) is an important tool for studying protein dynamics. Because of the complexity of conventional NMA that uses an all-atom model and a semi-empirical force field, many simplified NMA models have been developed, some of which are known as elastic network models. The quality of these simplified NMA models was assessed mostly by evaluating their predictions against experimental B-factors, and rarely by comparing them with the original NMA. In this work, we take the effort to create a publicly accessible dataset of proteins with their minimized structures, NMA modes, and mean-square fluctuations. Then, for the first time, we evaluate the quality of individual normal modes of several widely used elastic network models by comparing them with the conventional NMA. Our results demonstrate that the conventional NMA presents a better and more complete evaluation measure of the quality of elastic network models. This realization should be very helpful in improving current or designing new, higher quality elastic network models. Moreover, using the conventional NMA as the standard of evaluation, a number of interesting and significant insights into the elastic network models are gained.
authors.affiliation: Department of Computer Science, Iowa State University, Ames, Iowa, 50011.
authors.forename: Hyuntae
authors.initials: H
authors.lastname: Na
authors.forename: Guang
authors.initials: G
authors.lastname: Song
mesh_terms: D000465:Algorithms; D004548:Elasticity; D056004:Molecular Dynamics Simulation; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins
keywords: B-factors; elastic network model; mean-square fluctuations; normal mode analysis; protein dynamics