Free energy landscape of siRNA-polycation complexation: Elucidating the effect of molecular geometry, polymer flexibility, and charge neutralization

<div><p>The success of medical threatments with DNA and silencing interference RNA is strongly related to the design of efficient delivery technologies. Cationic polymers represent an attractive strategy to serve as nucleic-acid carriers with the envisioned advantages of efficient complexation, low cost, ease of production, well-defined size, and low polydispersity index. However, the balance between efficacy and toxicity (safety) of these polymers is a challenge and in need of improvement. With the aim of designing more effective polycationic-based gene carriers, many parameters such as carrier morphology, size, molecular weight, surface chemistry, and flexibility/rigidity ratio need to be taken into consideration. In the present work, the binding mechanism of three cationic polymers (polyarginine, polylysine and polyethyleneimine) to a model siRNA target is computationally investigated at the atomistic level. In order to better understand the polycationic carrier-siRNA interactions, replica exchange molecular dynamic simulations were carried out to provide an exhaustive exploration of all the possible binding sites, taking fully into account the siRNA flexibility together with the presence of explicit solvent and ions. Moreover, well-tempered metadynamics simulations were employed to elucidate how molecular geometry, polycation flexibility, and charge neutralization affect the siRNA-polycations free energy landscape in term of low-energy binding modes and unbinding free energy barriers. Significant differences among polymer binding modes have been detected, revealing the advantageous binding properties of polyarginine and polylysine compared to polyethyleneimine.</p></div

Distribution plot of the Radius of Gyration (RG) of polyARG, polyLYS, PEI27 and PEI45, respectively.

<p>The computational data were taken from the last 20 ns of the Replica Exchange Molecular Dynamics trajectory at 300K, for each molecular system.</p

Structure of the siRNA sequence dGdG(AGCAGCACCUUCAGGAU)dUdU and the polycationic polymers investigated in the present work.

<p>Structure of the siRNA sequence dGdG(AGCAGCACCUUCAGGAU)dUdU and the polycationic polymers investigated in the present work.</p

Nucleotides that are mainly responsible for siRNA-polycation interaction have been identified by contact probability plots [71] in case of PEI27, PEI45, polyARG and polyLYS systems.

<p>Nucleotides that are mainly responsible for siRNA-polycation interaction have been identified by contact probability plots [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0186816#pone.0186816.ref071" target="_blank">71</a>] in case of PEI27, PEI45, polyARG and polyLYS systems.</p

Free energy profile (kJ/mol) of siRNA-PEI27 interaction represented as function of siRNA-polycation distance from the major inertia axis of the target siRNA (distance from axis-DFA) and the projection of the siRNA-polymer distance on the major inertia axis of the target siRNA (projection on axis-POA).

<p>The free energy minima computed by metadynamics are compared with the system configurations sampled by REMD simulations (black triangle). The deepest binding site is highlighted with BS1. The visual inspection of each binding site is reported together with the corresponding electrostatic map (right). Potential isocontours are shown at +5kT/e (blue) and -5kT/e (red) and obtained by solution of the LPBE at 150 mM ionic strength with a solute dielectric of 4 and a solvent dielectric of 78.4.</p

Additional file 1: of Thermodynamic and kinetic stability of the Josephin Domain closed arrangement: evidences from replica exchange molecular dynamics

Supporting Information to Thermodynamic and Kinetic Stability of the Josephin Domain Closed Arrangement: Evidences from Replica Exchange Molecular Dynamics. Additional Information on Replica Exchange applied approach, kinetic estimation. (PDF 1183 kb

Time evolution of the JD radius of gyration (a) and hairpin angle (b) throughout the MD trajectory of each replica.

<p>(c) Visual inspection of the JD conformations taken from the classical MD simulations. The MD trajectories reveal a JD transition from an open state to a closed state, through an half-open and half-closed state. For each snapshot the α3 region (Asp57-Leu62) is highlighted with a different color: green (open), yellow (half-open), orange (half-closed) and red (closed).</p

Root Mean Square Fluctuation plot.

<p><b>Each point represents the mean fluctuation for each JD residue calculated over the whole MD trajectory (500 ns and five replicas taken together) filtered on the first PCA eigenvector.</b> The hairpin region (Val31-Leu62), composed by helix α2 (dashed red line) and α3 (continuous red line) is highlighted in blue. Secondary structure α6 (Asp145-Glu158) is highlighted in dark green.</p

Free energy profiles of the JD transition pathway as function of the (a) radius of gyration (RG) and (b) hairpin angle.

<p>The depth of the energy well corresponding to the absolute free energy minimum is highlighted in red. The absolute free energy well is set as zero.</p

Radius of Gyration (RG) distribution of the single JD, from trajectories of JD^Wat(a), JD-JD (b), and JD^A101/A103 (c) simulations.

<p>The experimental RG value of 1YZB and 2AGA (open/closed hairpin, respectively) are indicated for comparison.</p