The analysis of residue-residue contacts in protein structures can shed some light on our understanding of the folding and stability of proteins. In this paper, we study the statistical properties of long-range and short-range residue- residue contacts of 91 globular proteins using CSU software and analyze the importance of long-range contacts in globular protein structure. There are many short-range and long-range contacts in globular proteins, and it is found that the average number of long-range contacts per residue is 5.63 and the percentage of residue-residue contacts which are involved in long- range ones is 59.4%. In more detail, the distribution of long-range contacts in different residue intervals is investigated and it is found that the residues occurring in the interval range of 4-10 residues apart in the sequence contribute more long-range contacts to the stability of globular protein. The number of long-range contacts per residue, which is a measure of ability to form residue-residue contacts, is also calculated for 20 different amino acid residues. It is shown that hydrophobic residues (including Leu, Val, He, Met, Phe, Tyr, Cys and Trp) having a large number of long-range contacts easily form long-range contacts, while the hydrophilic amino acids (including Ala, Gly, Thr, His, Glu, Gln, Asp, Asn, Lys, Ser, Arg, and Pro) form long-range contacts with more difficulty. The relationship between the Fauchere-Pliska hydrophobicity scale (FPH) and the number of short-range and long-range contacts per residue for 20 amino acid residues is also studied. An approximately linear relationship between the Fauchere-Pliska hydrophobicity scale (FPH) and the number of long-range contacts per residue CL, is found and can be expressed as CL = a + b × FPH where a = 5.04 and b = 1.23. These results can help us to understand the role of residue-residue contacts in globular protein structure.
The characterization of long-range correlations and fractal properties of DNA sequences has proved to be a difficult though rewarding task mainly due to the mosaic character of DNA consisting of many patches of various lengths with different nucleotide constitutions. In this paper we investigate statistical correlations among different positions in DNA sequences using the two-dimensional DNA walk. The root-mean-square fluctuation F(l) is described by a power law. The autocorrelation function C(l), which is used to measure the linear dependence and periodicity, exists a power law of C(l) -τμ. We also calculate the mean-square distance ＜R2(l)＞ along the DNA chain, and it may be expressed as ＜R2(l)＞ - l r with 2 ＞γ＞ 1. Our investigations can provide some insights into long-range correlations in DNA sequences.
