In fact, the function i fj [Eq. (11.40)] actually reduces the errors in GB solvation energies while simultaneously accelerating the calculations [45]. To wit, when quasi-perfect R6 radii [62], which can be computed cheaply, are used in place of the perfect radii that are only available in benchmark calculations, the mean absolute error in as compared to C-PCM benchmarks is reduced from 8.7 kcal/mol for the canonical GB operator q/StiH 5.1 kcal/mol for the interpolating function At the same time, use of reduces the cost by a factor of three relative to the canonical GB model based on [45]. The new interpolating function [Pg.387]

In this section we focus on technical rather than theoretical developments, but ones that are absolutely essential if PCMs are going to be brought to bear on macromolecules. [Pg.387]

Balcazar, J.L., Diaz, J., Gavald., R., Watanabe, O. Algorithms for learning finite automata from queries a unified view. In Du, D.Z., Ko, K.I. (eds.) Advances in Algorithms, Languages, and Complexity, pp. 73-91. Kluwer Academic Publishers, Dordrech (1997)... [Pg.62]

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