Fragment-based error estimation in biomolecular modeling

• Reliable simulations of biomolecules depend on the accuracy of potential functions.
• Potential function errors propagate and increase with system size.
• We propose a statistics-based method for estimating potential model uncertainties.
• Conformational sampling naturally diminishes errors in free energy.

Computer simulations are becoming an increasingly more important component of drug discovery. Computational models are now often able to reproduce and sometimes even predict outcomes of experiments. Still, potential energy models such as force fields contain significant amounts of bias and imprecision. We have shown how even small uncertainties in potential energy models can propagate to yield large errors, and have devised some general error-handling protocols for biomolecular modeling with imprecise energy functions. Herein we discuss those protocols within the contexts of protein–ligand binding and protein folding.