Brownian dynamics simulations of DNA-ligand interactions: a theoretical study on the kinetics of DAPI-DNA complexation

Brownian dynamics study of the association between the 70S ribosome and elongation factor G

Protein synthesis on the ribosome involves a number of external protein factors that bind at its functional sites. One key factor is the elongation factor G (EF-G) that facilitates the translocation of transfer RNAs between their binding sites, as well as advancement of the messenger RNA by one codon. The details of the EF-G/ribosome diffusional encounter and EF-G association pathway still remain unanswered. Here, we applied Brownian dynamics methodology to study bimolecular association in the bacterial EF-G/70S ribosome system. We estimated the EF-G association rate constants at 150 and 300 mM monovalent ionic strengths and obtained reasonable agreement with kinetic experiments. We have also elucidated the details of EF-G/ribosome association paths and found that positioning of the L11 protein of the large ribosomal subunit is likely crucial for EF-G entry to its binding site.

Association of aminoglycosidic antibiotics with the ribosomal A-site studied with Brownian dynamics

Brownian dynamics methodology was applied to simulate the encounter of aminoglycosidic antibiotics with the ribosomal A-site RNA. Studied antibiotics included neamine, neomycin, ribostamycin and paromomycin which differ in chemical structure, the number of pseudo-sugar rings and the net charge. The influence of structural, electrostatic and hydrodynamic properties of antibiotics on the kinetics of their association with the ribosomal A-site was analyzed. The computed diffusion limited rates of association are of the order of 10(10)[Formula: see text] and they weakly depend on ionic strength. Prior to binding antibiotics often slide along the RNA groove with the time scale of approximately 10 ns per base pair in case of neamine. We observed that upon forming the encounter complex aminoglycosides displace from the binding pocket up to two Mg(2+) ions.

Binding pathways of ligands to HIV-1 protease: coarse-grained and atomistic simulations

Multiscale simulations (coarse-grained Brownian dynamics simulations and all-atom molecular dynamics simulations in implicit solvent) were applied to reveal the binding processes of ligands as they enter the binding site of the HIV-1 protease. The initial structures used for the molecular dynamics simulations were generated based on the Brownian dynamics trajectories, and this is the first molecular dynamics simulation of modeling the association of a ligand with the protease. We found that a protease substrate successfully binds to the protein when the flaps are fully open. Surprisingly, a smaller cyclic urea inhibitor (XK263) can reach the binding site when the flaps are not fully open. However, if the flaps are nearly closed, the inhibitor must rearrange or binding can fail because the inhibitor cannot attain proper conformations to enter the binding site. Both the peptide substrate and XK263 can also affect the protein's internal motion, which may help the flaps to open. Simulations allow us to efficiently study the ligand binding processes and may help those who study drug discovery to find optimal association pathways and to design those ligands with the best binding kinetics.

Gated binding of ligands to HIV-1 protease: Brownian dynamics simulations in a coarse-grained model

The internal motions of proteins may serve as a "gate" in some systems, which controls ligand-protein association. This study applies Brownian dynamics simulations in a coarse-grained model to study the gated association rate constants of HIV-1 proteases and drugs. The computed gated association rate constants of three protease mutants, G48V/V82A/I84V/L90M, G48V, and L90M with three drugs, amprenavir, indinavir, and saquinavir, yield good agreements with experiments. The work shows that the flap dynamics leads to "slow gating". The simulations suggest that the flap flexibility and the opening frequency of the wild-type, the G48V and L90M mutants are similar, but the flaps of the variant G48V/V82A/I84V/L90M open less frequently, resulting in a lower gated rate constant. The developed methodology is fast and provides an efficient way to predict the gated association rate constants for various protease mutants and ligands.