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A new set of energy values to predict the secondary structures in RNA molecules has been derived through a multiple-step refinement procedure. It achieves more than 80% success in predicting the cloverleaf pattern in tRNA (200 sequences tested) and more than 60% success in predicting the consensus folding of 5S RNA (100 sequences). Improvements in our initial program for predicting secondary structures, based on the principle of the "incompatibility islets" made possible the work on 5S RNA. The program was speeded up by introducing a dynamic grouping of the islets into three disjoint blocks. The novel features in the energy model include i) an evaluation of the contribution of odd pairs according to their position within a segment ii) a penalty for internal loops related to their dissymmetry iii) a bonus for bulge loops when the two terminal paired bases at the junction point are both pyrimidines.

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A population of bacteria growing in a nonlimiting medium includes mutator bacteria and transient mutators defined as wild-type bacteria which, due to occasional transcription or translation errors, display a mutator phenotype. A semiquantitative theoretical analysis of the steady-state composition of an Escherichia coli population suggests that true strong genotypic mutators produce about 3 x 10(-3) of the single mutations arising in the population, while transient mutators produce at least 10% of the single mutations and more than 95% of the simultaneous double mutations. Numbers of mismatch repair proteins inherited by the offspring, proportions of lethal mutations and mortality rates are among the main parameters that influence the steady-state composition of the population. These results have implications for the experimental manipulation of mutation rates and the evolutionary fixation of frequent but nearly neutral mutations (e.g., synonymous codon substitutions).

An alternative method for deriving rate equations in enzyme kinetics is presented. An enzyme is followed as it moves along the various pathways allowed by the reaction scheme. The times spent in various sections of the scheme and the pathway probabilities are computed, using simple rules. (5,6): If one starts with a population of A molecules and watches their evolution, one finds (i) that for any t(Ao --Ai) = 1/(k1+ k2 + . . . + kn). [2] It is independent of the state of arrival. Note also that p = kit. The general idea in the method I shall develop is to take one enzyme and follow its fate as it progresses along the reaction scheme. The time spent on a pathway is obtained by adding (with an adequate weighting) the relaxation times. The rate is obtained by computing, for various sections of the reaction scheme, (i) the probability that a molecule of product is formed, and (ii) the time spent by the enzyme in the considered section. Times and probabilities are then concatenated over larger and larger sections.