(123e) Ligand Binding Free Energy Predictions Based On Single Steered Molecular Dynamics for Hydrophobic and Hydrogen Bonding Governed Interactions With An ?-Helix | AIChE

(123e) Ligand Binding Free Energy Predictions Based On Single Steered Molecular Dynamics for Hydrophobic and Hydrogen Bonding Governed Interactions With An ?-Helix

Authors 

Marzinek, J. - Presenter, Unilever R&D Colworth Science Park
Zhao, Y., China Agricultural University
Lian, G., Unilever R&D Colworth Science Park
Mantalaris, A., Imperial College London
Pistikopoulos, E. N., Centre for Process Systems Engineering, Imperial College



Free energy is one of the most desirable and important thermodynamic properties in simulations and experiments of biological systems.1,2 Recently, an increasing number of studies have been reported in the literature on binding free energy (ΔG) calculations of small molecules to proteins within a molecular dynamics (MD) simulation framework, often with accompanying experimental validation. However, high accuracy predictions of this thermodynamic property, in simulation systems that include explicit solvent, are computationally very expensive. Previously, we proposed a linear correlation (at given temperature and pulling rate) between the maximum pulling force (Fmax) obtained from a single steered MD (SMD) simulation and ΔG calculated via umbrella sampling (US).3 We reported an application of this method to epigallocatechin-3-gallate (EGCG) binding keratin filaments, the outermost skin layer protein. In the present study, we extend this to investigate the binding of four additional ligands characterized by different octanol/water partition coefficient values (ranging from -2 to 2) to the α-helical part of keratin. Together with our previous work 35 µs of simulation sampling in explicit solvent has been generated. Validation of the simulation results is performed via isothermal titration calorimetry (ITC) for three of those ligands. The calculated binding ΔG’s for these small molecules are in excellent agreement with the experimental data. We also see the same relation between Fmaxfrom SMD and ΔG for each of these molecules. Hence, our results provides a means to precisely predict the binding ΔG of small molecules with various physiochemical properties to the most common protein secondary structural element via hydrogen bonds and/or hydrophobic interactions based on a single and reproducible short pulling simulation (hundreds of picoseconds) instead of time consuming US calculations (hundreds of nanoseconds).

References

1. Beveridge, D. L.; Dicapua, F. M. Free-Energy Via Molecular Simulation - Applications to Chemical and Biomolecular Systems. Annu Rev Biophys Biophys Chem. 1989, 18, 431-492.

2. Deng, Y. Q.; Roux, B. Computations of Standard Binding Free Energies with Molecular Dynamics Simulations. J. Phys. Chem. B. 2009, 113(8), 2234-2246.

3. Torrie GM, Valleau JP. Non-Physical Sampling Distributions in Monte-Carlo Free-Energy Estimation - Umbrella Sampling. Journal of Computational Physics. 1977; 23(2):187-199.