title: Refinement of the long-range order parameter in predicting folding rates of two-state proteins.
abstract: Long-range order (LRO) is one of the most successful descriptors in relating the three-dimensional structures of proteins with their folding rates. LRO highlights the importance of long-range contacts (residues that are far in sequence and closer in the 3D structure) in determining the folding rates of proteins across all structural classes of proteins. In this work, we have updated the data set of two-state folding proteins to examine the robustness of LRO parameter and to assess whether any refinements are required in defining the computation of LRO. LRO shows a better correlation (r = -0.85) for the increased dataset with a very small difference in distance cut-off compared to the old data set and reinforces the robustness of the parameter. When the dataset was grouped into three major structural classes, slight refinement of the parameter (distance of separation in space and sequence) gave better correlations. The corresponding correlation for the three structural classes are r = -0.92; sequence separation 23; spatial distance cut-off 5.5 A for all alpha structural class, r = -0.84; sequence separation 43; spatial distance cut-off 7 A for all beta structural class and r = -0.82; sequence separation 8; spatial distance cut-off 8 A for mixed class proteins. It is envisaged that during the process of protein folding, formation of long-range contacts beyond the above sequence separation limits may play a key role in determining the folding rates of proteins, and this aspect is discussed in the light of experimental studies on the formation of interresidue contacts and end-to-end loops in unfolded polypeptide chains.
authors: Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli 620 024, Tamil Nadu, India.
authors: B
authors: B
authors: Harihar
authors: S
authors: S
authors: Selvaraj
mesh_terms: D000465:Algorithms; D000818:Animals; D030562:Databases, Protein; D006801:Humans; D007700:Kinetics; D008958:Models, Molecular; D015233:Models, Statistical; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000145:classification; D012044:Regression Analysis
chemical_list: D011506:Proteins