Statistical mechanical approach for predicting the transition to non-B DNA structures in supercoiled DNA.
Supercoiling causes global twist of DNA structure and the supercoiled state has wide influence on conformational transition. A statistical mechanical approach was made for prediction of the transition probability to non-B DNA structures under torsional stress. A conditional partition function was defined as the sum over all possible states of the DNA sequence with basepair 1 and basepair n being in B-form helix and a recurrence formula was developed which expressed the partition function for basepair n with those for less number of pairs. This new definition permits a quick enumeration of every configuration of secondary structures. Energetic parameters of all conformations concerned, involving B-form, interior loop, cruciform and Z-form, were included in the equation. The probability of transition to each non-B conformation could be derived from these conditional partition functions. For treatment of effects of superhelicity, supercoiling energy was considered, and a twist of each conformation was determined to minimize the supercoiling energy. As the twist itself affects the transition probability, the whole scheme of equations was solved by renormalization technique. The present method permits a simultaneous treatment of several types of conformations under a common torsional stress. A set of energetic parameters of DNA secondary structures has been chosen for calculation. Some DNA sequences were submitted to the calculation, and all the sequences that we submitted gave stable convergence. Some of them have been investigated the critical supercoil density for the transition to non-B DNA structures. Even though the reliability of the set of parameters was not enough, the prediction of secondary structure transition showed good agreement with reported observation. Hence, the present algorithm can estimate the probability of local conformational change of DNA under a given supercoil density, and also be employed to predict some specific sequences in which conformational change is sensitive to superhelicity.
Katsura
S
S
Department of Chemical Engineering, Faculty of Engineering, University of Tokyo, Japan.
Makishima
F
F
Nishimura
H
H
D000465:Algorithms; D010584:Bacteriophage phi X 174 / Q000235:genetics; D001483:Base Sequence; D004269:DNA, Bacterial / Q000737:chemistry; D004278:DNA, Superhelical / Q000737:chemistry*; D004279:DNA, Viral / Q000737:chemistry; D003627:Data Interpretation, Statistical; D008969:Molecular Sequence Data; D009690:Nucleic Acid Conformation; D010957:Plasmids
D004269:DNA, Bacterial; D004278:DNA, Superhelical; D004279:DNA, Viral