We have defined the folding index of the RNA secondary structure and compared the value of this index obtained from a given RNA molecule with one from the random sequences with the same A, U, G, C ratio. The mRNA of the cytochrome c oxidase subunit II and cytochrome P450 from various species was analyzed. We found that the mRNA of these genes were more folded than the random sequences and the coding regions of these mRNA were as equally folded as the random sequences. This result suggests that the coding region of these mRNA has no more important secondary structure than have the random sequences with the same A, U, G, C ratio.

We present a new algorithm for the display of RNA secondary structure. The principle of the algorithm is entirely different from those currently in use in that our algorithm is ‘object oriented’ while currrent algorithms are ‘procedural’. The circular RNA molecule of chrysanthemum stunt viroid was used as input data for demonstrating the operation of the program. The major interest of this method will be found in its potential use in simulation graphics of RNA folding processes.

We have previously reported an algorithm (Yamamoto and Yoshikura, 1985) for the prediction of optimum and suboptimum RNA folding structures. The calculation data was presented as an 'information map'. However, the result was affected by the starting point of calculation. In this paper, we have improved the method so that the result will not be affected by the starting point. In addition, we present a method of converting the information map into a set of pictures of optimal and suboptimal molecular structures.

A vector diagram was devised for representation of protein structure. This was done by giving each nucleic acid triplet a corresponding vector, and expressing a protein as a set of vectors which were aligned in the order of peptide sequence. The magnitude of each vector was made to reflect the hydrophilicity of amino acid, and the direction of the vector was chosen so that similar amino acids had similar directions. The diagram not only shows the primary sequence but suggests the folding structure of proteins.

We present an algorithm for prediction of RNA secondary structures. The program consists of three parts: the first computes location and free energy of every possible stem-loop structure, the second computes probability of its formation, and the third lists the positions and free energies of all the stem-loops in the order of their probability sizes. The circular RNA molecule of chrysanthemum stunt viroid was used as an input data for demonstrating the operation of the program.