The study of interactions between DNA and PcrA DNA helicase by using targeted molecular dynamic simulations

Interplay between Position-Dependent Codon Usage Bias and Hydrogen Bonding at the 5' End of ORFeomes

Codon usage bias exerts control over a wide variety of molecular processes. The positioning of synonymous codons within coding sequences (CDSs) dictates protein expression by mechanisms such as local translation efficiency, mRNA Gibbs free energy, and protein cotranslational folding. In this work, we explore how codon usage affects the position-dependent content of hydrogen bonding, which in turn influences energy requirements for unwinding double-stranded DNA (dsDNA). We categorized codons according to their hydrogen bond content and found differential effects on hydrogen bonding encoded by codon variants. The specific positional disposition of codon variants within CDSs creates a ramp of hydrogen bonding at the 5' end of the ORFeome in Escherichia coli CDSs occupying the first position of operons are subjected to selective pressure that reduces their hydrogen bonding compared to internal CDSs, and highly transcribed CDSs demand a lower maximum capacity of hydrogen bonds per codon, suggesting that the energetic requirement for unwinding the dsDNA in highly transcribed CDSs has evolved to be minimized in E. coli Subsequent analysis of over 14,000 ORFeomes showed a pervasive ramp of hydrogen bonding at the 5' end in Bacteria and Archaea that positively correlates with the probability of mRNA secondary structure formation. Both the ramp and the correlation were not found in Fungi The position-dependent hydrogen bonding might be part of the mechanism that contributes to the coordination between transcription and translation in Bacteria and Archaea A Web-based application to analyze the position-dependent hydrogen bonding of ORFeomes has been developed and is publicly available (https://juanvillada.shinyapps.io/hbonds/).IMPORTANCE Redundancy of the genetic code creates a vast space of alternatives to encode a protein. Synonymous codons exert control over a variety of molecular and physiological processes of cells mainly through influencing protein biosynthesis. Recent findings have shown that synonymous codon choice affects transcription by controlling mRNA abundance, mRNA stability, transcription termination, and transcript biosynthesis cost. In this work, by analyzing thousands of Bacteria, Archaea, and Fungi genomes, we extend recent findings by showing that synonymous codon choice, corresponding to the number of hydrogen bonds in a codon, can also have an effect on the energetic requirements for unwinding double-stranded DNA in a position-dependent fashion. This report offers new perspectives on the mechanism behind the transcription-translation coordination and complements previous hypotheses on the resource allocation strategies used by Bacteria and Archaea to manage energy efficiency in gene expression.

Molecular Mechanisms of DNA Replication and Repair Machinery: Insights from Microscopic Simulations

Reproduction, the hallmark of biological activity, requires making an accurate copy of the genetic material to allow the progeny to inherit parental traits. In all living cells, the process of DNA replication is carried out by a concerted action of multiple protein species forming a loose protein-nucleic acid complex, the replisome. Proofreading and error correction generally accompany replication but also occur independently, safeguarding genetic information through all phases of the cell cycle. Advances in biochemical characterization of intracellular processes, proteomics and the advent of single-molecule biophysics have brought about a treasure trove of information awaiting to be assembled into an accurate mechanistic model of the DNA replication process. In this review, we describe recent efforts to model elements of DNA replication and repair processes using computer simulations, an approach that has gained immense popularity in many areas of molecular biophysics but has yet to become mainstream in the DNA metabolism community. We highlight the use of diverse computational methods to address specific problems of the fields and discuss unexplored possibilities that lie ahead for the computational approaches in these areas.