Method Evaluations for Adsorption Free Energy Calculations at the Solid/Water Interface through Metadynamics, Umbrella Sampling, and Jarzynski's Equality

Abstract

Considerable interest in characterizing protein/peptide-surface interactions has prompted extensive computational studies on calculations of adsorption free energy. However, in many cases, each individual study has focused on the application of free energy calculations to a specific system; therefore, it is difficult to combine the results into a general picture for choosing an appropriate strategy for the system of interest. Herein, three well-established computational algorithms are systemically compared and evaluated to compute the adsorption free energy of small molecules on two representative surfaces. The results clearly demonstrate that the characteristics of studied interfacial systems have crucial effects on the accuracy and efficiency of the adsorption free energy calculations. For the hydrophobic surface, steered molecular dynamics exhibits the highest efficiency, which appears to be a favorable method of choice for enhanced sampling simulations. However, for the charged surface, only the umbrella sampling method has the ability to accurately explore the adsorption free energy surface. The affinity of the water layer to the surface significantly affects the performance of free energy calculation methods, especially at the region close to the surface. Therefore, a general principle of how to discriminate between methodological and sampling issues based on the interfacial characteristics of the system under investigation is proposed.

Entropy–Enthalpy Compensation in Peptide Adsorption on Solid Surfaces: Dependence on Surface Hydration

“…Details could be found in our previous studies. 23 Entropic and Enthalpic Components of the Adsorption Free Energy. In this study, our efforts have been exerted into estimating the entropic and enthalpic components of the adsorption free energy to thoughtfully unravel the thermodynamic characteristics of peptide adsorption at the surface− water interface.…”

“…12,22 Previously, we have systemically evaluated the benefits and pitfalls of each method and proposed a general principle of how to prescreen the sampling methods according to the interfacial characteristics of the system. 23 The free energy decomposition has illustrated that the binding of peptide/protein with a surface is considered as the delicate balance between the interactions of the adsorbate with both the surface and solvent. 24 It has been further revealed that the water phase provides a repelling force against peptide adsorptions, whereas the surface−peptide interaction serves as the driving force to peptide adsorption.…”

“…Many efforts have been exerted to obtain the adsorption free energy, including enthalpic and entropic contributions, which serves as a fundamental measure of the binding affinity between a protein/peptide and a surface. Several well-developed simulation methods based on the enhanced sampling techniques, such as umbrella sampling (US), metadynamics, and steered molecular dynamics (SMD) simulation, have been applied to extract thermodynamic data for many surface–water–protein interfaces. , Previously, we have systemically evaluated the benefits and pitfalls of each method and proposed a general principle of how to prescreen the sampling methods according to the interfacial characteristics of the system …”

Advanced simulation techniques for the thermodynamic and kinetic characterization of biological systems

“…Several attempts were done to critically compare the performance of different free-energy calculation methods [139,[222][223][224][225][226][227][228]. This is a non-trivial task, which becomes even more difficult if kinetic properties are the target.…”

“…This can be theoretically formulated using the principle of maximum entropy (pMaxEnt) [236]. Pitera and Chodera [237] showed how to implement pMaxEnt by a linear bias applied on a single simulation with an unknown force constant (the Lagrangian multiplier) that can be obtained iteratively or on-the-fly during the simulation [228,[237][238][239]. Alternatively, instead of searching for the Lagrangian multiplier, one can perform multiple simulations in parallel and couple them with an harmonic potential centred on the value of the equilibrium observable of interest, the so called replica-averaging approach [240][241][242].…”