title: Application of long-range order to predict unfolding rates of two-state proteins.
abstract: Predicting the experimental unfolding rates of two-state proteins and models describing the unfolding rates of these proteins is quite limited because of the complexity present in the unfolding mechanism and the lack of experimental unfolding data compared with folding data. In this work, 25 two-state proteins characterized by Maxwell et al. (Protein Sci 2005;14:602–616) using a consensus set of experimental conditions were taken, and the parameter long-range order (LRO) derived from their three-dimensional structures were related with their experimental unfolding rates ln(k(u)). From the total data set of 30 proteins used by Maxwell et al. (Protein Sci 2005;14:602–616), five slow-unfolding proteins with very low unfolding rates were considered to be outliers and were not included in our data set. Except all beta structural class, LRO of both the all-alpha and mixed-class proteins showed a strong inverse correlation of r = -0.99 and -0.88, respectively, with experimental ln(k(u)). LRO shows a correlation of -0.62 with experimental ln(k(u)) for all-beta proteins. For predicting the unfolding rates, a simple statistical method has been used and linear regression equations were developed for individual structural classes of proteins using LRO, and the results obtained showed a better agreement with experimental results.
authors.affiliation: Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli, Tamilnadu, India.
authors.forename: B
authors.initials: B
authors.lastname: Harihar
authors.forename: S
authors.initials: S
authors.lastname: Selvaraj
mesh_terms: D007700:Kinetics; D011489:Protein Denaturation; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins