The ratio of nonsynonymous substitution rate （Ka） to synonymous substitution rate （Ks） is widely used as an indicator of selective pressure at sequence level among different species, and diverse mutation models have been incorporated into several computing methods. We have previously developed a new γ-MYN method by capturing a key dynamic evolution trait of DNA nucleotide sequences, in consideration of varying mutation rates across sites. We now report a further improvement of NG, LWL, MLWL, LPB, MLPB, and YN methods based on an introduction of gamma distribution to illustrate the variation of raw mutation rate over sites. The novelty comes in two ways： （1） we incorporate an optimal gamma distribution shape parameter a into γ-NG, γ-LWL, γ-MLWL, γ-LPB, γ-MLPB, and γ-YN methods; （2） we investigate how variable substitution rates affect the methods that adopt different models as well as the interplay among four evolutional features with respect to Ka/Ks computations. Our results suggest that variable substitution rates over sites under negative selection exhibit an opposite effect on estimates compared with those under positive selection. We believe that the sensitivity of our new methods has been improved than that of their original methods under diverse conditions and it is advantageous to introduce novel parameters for Ka/Ks computation.
Rate-limiting enzymes, low rates of catalysis, are because of their relatively essential for flux control in metabolic pathways [1, 2]. They themselves are often extensively regulated, such as by transcription factors and post-translational modifications, and thus play the important role of linking metabolic pathways to gene expression regulatory networks and signal transduction networks. Identification and classification of rate-limiting enzymes and their regulators are the first steps towards understanding their roles in metabolic flux control.
