- The net charge of the final model immersed in its solvent
environment should be neutral. - Use the latest version of a force field suitable for biological
macromolecules to describe the protein component of the
system. - Use a generalized force field to describe the drug component
of the system, deriving any missing parameters by analogy or ab
initio, such that they are compatible with the protein force
field. - Parameters with poor analogy should be validated against
experiment, or optimized by fitting to quantum mechanical
potentials. - Minimizing the potential energy of the system is key to resolv-
ing any high energy conformations that may lead to instabilities
going into the simulation phase of the project. - The simulation should be slowly heated to a target temperature
that mimic’s the model’s realistic environment. - Imposing positional (harmonic) restraints to maintain the pro-
tein fold and drug binding mode during heating, and gradually
releasing those restraints once the target temperature has been
reached, allows the system to slowly adjust to its native envi-
ronmental conditions. - Extend the equilibration phase of the project until the property
of interest for the study, e.g., drug binding mode, has
converged. - Extend the production (data collection) phase of the project
until sufficient sampling of the system is obtained, e.g.,
hundreds of nanoseconds at minimum for most protein–drug
complexes.
Acknowledgements
The authors acknowledge funding from the University of Delaware
and the National Institutes of Health COBRE grant
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