Differentiation between two-state and multi-state folding proteins based on sequence.
Prediction of protein-folding rates follows different rules in two-state and multi-state kinetics. The prerequisite for the prediction is to recognize the folding kinetic pathway of proteins. Here, we use the logistic regression and support vector machine to discriminate between two-state and multi-state folding proteins. We find that chain length is sufficient to accurately recognize multi-state proteins. There is a transition boundary between two kinetic models. Protein folds with multi-state kinetics, if its length is larger than 112 residues. The logistic prediction from amino acid composition shows that the kinetic pathway of folding is closely related to amino acid volume. Small amino acids make two-state folding easier, and vice versa. However, cysteine, alanine, arginine, lysine, histidine, and methionine do not conform to this rule.
Huang
Ji-Tao
JT
State Key Laboratory of Elemento-Organic Chemistry, College of Chemistry, Nankai University, Tianjin 300071, China.
Cheng
Jin-Pei
JP
D000595:Amino Acid Sequence; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D020539:Sequence Analysis, Protein
D011506:Proteins