Discrete Molecular Dynamics Simulation of Biomolecules

Understanding Effects of PAMAM Dendrimer Size and Surface Chemistry on Serum Protein Binding with Discrete Molecular Dynamics Simulations

“…DMD is a special form of a MD algorithm, where the conventional continuous potentials are replaced by stepwise functions. , A comprehensive description of the DMD algorithm has been published elsewhere. , Briefly, a united-atom model with an implicit solvent was used to represent a molecular system, in which all heavy atoms and polar hydrogen atoms of proteins and PAMAM dendrimers were explicitly modeled. Interatomic interactions were adapted from the Medusa force field, , which included van der Waals (VDW), solvation, hydrogen bonds, and electrostatic interactions.…”

Solving protein structures using short-distance cross-linking constraints as a guide for discrete molecular dynamics simulations

“…This algorithm has been shown to provide more efficient sampling of the protein conformational space than traditional molecular dynamics simulations, allowing more rapid folding of large proteins. Also, the discrete energy representation allows for the incorporation of experimental pairwise atom proximity constraints (31,32); for each experimental constraint, we have introduced an additional potential to the force field developed (32,33). The combination of these potentials constrains the positions of the cross-linked atoms during simulations.…”

Out-of-Equilibrium Biophysical Chemistry: The Case for Multidimensional, Integrated Single-Molecule Approaches

“… 135 , 136 Discrete molecular dynamics (DMD), an event-driven MD approach featuring higher sampling efficiency over conventional MD, 137 − 139 has been developed to efficiently study the dynamics of biomolecules. 140 The increased computational efficiency results from the usage of discretized potential functions and recalculation of atomic ballistic equations only for atoms that are involved in a collision event. 141 , 142 The DMD force field incorporates the CHARMM van der Waals interaction parameters, the Lazaridis and Karplus implicit solvent model 143 (the effective energy function, EEF1), screened electrostatic interactions between charged residues, and explicit modeling of hydrogen bonds.…”

“…Usually, conventional all-atom MD simulations with parallel computing can reach time scales up to microseconds that capture many physiologically important dynamics but still fall short of covering the wide range of functionally relevant time scales up to milliseconds and seconds. , Also, conventional MD simulations can rarely unveil the features of the high energy transition states that lie in regions of the free energy landscape, as the simulated systems often get trapped in local-minimum conformations . To overcome this limitation, enhanced sampling methods such as replica exchange MD and metadynamics have been developed to handle the inherent quasi-nonergodicity and analyze complex dynamics, determine structural information, and efficiently sample the rugged folding landscape of biophysical systems. , Discrete molecular dynamics (DMD), an event-driven MD approach featuring higher sampling efficiency over conventional MD, − has been developed to efficiently study the dynamics of biomolecules . The increased computational efficiency results from the usage of discretized potential functions and recalculation of atomic ballistic equations only for atoms that are involved in a collision event. , The DMD force field incorporates the CHARMM van der Waals interaction parameters, the Lazaridis and Karplus implicit solvent model (the effective energy function, EEF1), screened electrostatic interactions between charged residues, and explicit modeling of hydrogen bonds.…”