Determining the Identity Nucleotides and the Energy of Binding of tRNAs to Their Aminoacyl-tRNA Synthetases Using a Simple Logistic Model.

ABSTRACT: This study showed that the predictor in logistic regression can be applied to estimating the Gibbs free energy of tRNAs' recognition of and binding to their aminoacyl-tRNA synthetases. Then, 24 linear logistic regression models predicting different classes of tRNAs loaded with a corresponding amino acid were trained in a machine learning classification method, reducing the misclassification error to zero. The models were based on minimal subsets of Boolean explanatory variables describing the favorite presence of nucleotides or nucleosides localized in the different parts of the tRNA. In 90% of cases, they agree with the components of the consensus strand in a class of tRNAs loaded by a given amino acid. According to the proposed theoretical model, the values of the free energy for the ent

SUBMITTER: Pawlowski PH 

PROVIDER: S-EPMC11509504 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature