Probe the Binding Mode of Aristololactam‐β‐D‐glucoside to Phenylalanine Transfer RNA in Silico

Abstract

Understanding the interactions of drug molecules with biomacromolecules at a micro-scale level is essential to design potent drugs for the treatments of human genome diseases. To unravel the mechanism of binding of aristololactam-b-D-glucoside (ADG) and phenylalanine transfer RNA (tRNA Phe ), an integrated computational strategy combining quantum mechanics (QM) calculation, molecular docking and atomistic molecular dynamics (MD) simulation was present in this work. QM calculations were performed to derive the partial charges of ADG, molecular docking was used to determine the binding poses of ADG on the tRNA Phe , and atomistic MD simulations were conducted to examine the thermal stability of five predicted binding poses for the complex of ADG and the tRNA Phe . The binding free energies of the five complexes were then calculated using the molecular mechanics/generalized born surface area approach with the variable internal dielectric constant model. By comparing computed affinities and experimentally-measured values in the binding free energy, we identified a most likely binding structure of ADG and the tRNA Phe . Further analysis of energy of the ADG-tRNA complex revealed that the aristololactam of ADG provides binding specificity to the tRNA Phe , and the D-glucoce contributes to the affinity for binding with the tRNA Phe .[a] Dr.

In silicostudy of the binding of daunomycin and phenylalanine transfer RNA: probe molecular recognition for structure-based drug design

“…In contrast, an electrostatic repulsion occurs between daunomycinone and nucleotide U 50 , resulting in the positive intermolecular ELE + EGB energies. As evidenced by our previous binding studies of peptides and RNAs 54,55 and of drug molecules and proteins, 56,57 the intermolecular VDW energy is responsible for binding specificity of biomolecules and the intermolecular ELE+EGB energy is for the binding affinity of biomolecules. Thus, we learn from Fig.…”

Extended Concerted Rotation Technique Enhances the Sampling Efficiency of the Computational Peptide-Design Algorithm

“…Three independent simulations were carried out for each peptide- boxB RNA complex in 120 ns to ensure that our systems reached an equilibrated state. To accurately evaluate the charge–charge interactions between charged (or polar) molecules, we employed a variable internal dielectric constant model to capture electrostatic shielding effects. − Using the implicit-solvent MM/GBSA approach with the variable internal dielectric constant model, we postanalyzed the last 5 ns simulation trajectories of the peptide- boxB RNA complexes to calculate their binding free energies. Details of the procedures and postanalysis of the atomistic MD simulations can be found in our previous work …”

“…This was later improved by taking into account both the binding energy of the peptide-target complex and the free energy of the peptide when stabilized in the bound conformation . The peptide’s binding free energy and free energy in the bound state were calculated by using the implicit-solvent MM/GBSA approach with the variable internal dielectric constant model. − An early version of the algorithm was used to computationally design a 15-mer peptide to have good ability to recognize human lysine tRNA species (tRNA Lys3 ), a primer for HIV reverse transcription. Synthesis of the computationally designed peptide and experimental characterization by the Agris group revealed that the designed peptide has an affinity ( K d = 0.05 μM) that is 10-fold better than that of a peptide identified experimentally via phage display …”