2 research outputs found
Systematic comparison of Amber and Rosetta energy functions for protein structure evaluation.
<p>An accurate energy function is an essential component of biomolecular
structural modeling and design. The
comparison of differently derived energy functions enables analysis of the
strengths and weaknesses of each energy function, and provides independent
benchmarks for evaluating improvements within a given energy function. We compared the molecular mechanics Amber
empirical energy function to two versions of the Rosetta energy function
(talaris2014 and REF2015) in decoy discrimination and loop modeling tests. Both
Rosetta's talaris2014 and Amber's ff14SBonlySC energy functions performed well
in scoring the native state as the lowest energy conformation in many cases. In 24/150 cases with Rosetta, and in 2/150
cases using Amber, a false minimum is found that is absent in the alternative
landscape. In 21/150 cases, both energy function-generated landscapes featured
false minima. The newest version of the Rosetta energy function, REF2015, which
has more physically-derived terms than talaris2014, performs significantly
better, highlighting the improvements made to the Rosetta scoring approach. To
take advantage of the semi-orthogonal nature of these energy functions, we developed
a Pareto optimization approach that combines Amber and Rosetta energy
landscapes to predict the most near-native model for a given protein. This algorithm
improves upon predictions from either energy function in isolation, and should
aid in model selection for structure prediction and loop modeling tasks. </p
Structure and ion transport of lithium-rich Li1+xAlxTi2−x(PO4)3 with 0.3
© 2020 Elsevier B.V. New solid state electrolytes are becoming increasingly sought after in the drive to replace flammable liquid electrolytes. To this end, several Li conducting solids have been identified as promising candidates including Li stuffed garnets and more recently Li-rich materials such as Li1+xAlxTi2−x(PO4)3 with 0.3Ti4+ compared to Li+–>Al3+. Furthermore, our calculated ionic conductivities are in excellent agreement with experimental values, highlighting the robustness of our computational models