Design of Novel Relaxase Substrates Based on Rolling Circle Replicases for Bioconjugation to DNA Nanostructures

During bacterial conjugation and rolling circle replication, HUH endonucleases, respectively known as relaxases and replicases, form a covalent bond with ssDNA when they cleave their target sequence (nic site). Both protein families show structural similarity but limited amino acid identity. Moreover, the organization of the inverted repeat (IR) and the loop that shape the nic site differs in both proteins. Arguably, replicases cleave their target site more efficiently, while relaxases exert more biochemical control over the process. Here we show that engineering a relaxase target by mimicking the replicase target, results in enhanced formation of protein-DNA covalent complexes. Three widely different relaxases, which belong to MOBF, MOBQ and MOBP families, can properly cleave DNA sequences with permuted target sequences. Collaterally, the secondary structure that the permuted targets acquired within a supercoiled plasmid DNA resulted in poor conjugation frequencies underlying the importance of relaxase accessory proteins in conjugative DNA processing. Our results reveal that relaxase and replicase targets can be interchangeable in vitro. The new Rep substrates provide new bioconjugation tools for the design of sophisticated DNA-protein nanostructures.This work was financed by grants BFU2014-55534-C2-1-P from the Spanish Ministry of Economy and Competitiveness and 612146/FP7-ICT- 2013 and 282004/FP7-HEALTH.2011.2.3.1-2 from the European Union Seventh Framework Programme to FC and grant BFU2014-55534-C2-2-P from the Spanish Ministry of Economy and Competitiveness to GM. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes