Advances in theory and algorithms for electronic structure calculations must be incorporated into program packages to enable them to become routinely used by the broader chemical community. This work reviews advances made over the past five years or so that constitute the major improvements contained in a new release of the Q-Chem quantum chemistry package, together with illustrative timings and applications. Specific developments discussed include fast methods for density functional theory calculations, linear scaling evaluation of energies, NMR chemical shifts and electric properties, fast auxiliary basis function methods for correlated energies and gradients, equation-of-motion coupled cluster methods for ground and excited states, geminal wavefunctions, embedding methods and techniques for exploring potential energy surfaces.

clinicaltrials.gov Identifier: NCT00645918.

Based on recent developments in generalized Born (GB) theory that employ rapid volume integration schemes (M. S. Lee, F. R. Salabury, Jr., and C. L. Brooks III, J Chem Phys 2002, 116, 10606) we have recast the calculation of the self-electrostatic solvation energy to utilize a simple smoothing function at the dielectric boundary. The present GB model is formulated in this manner to provide consistency with the Poisson-Boltzmann (PB) theory previously developed to yield numerically stable electrostatic solvation forces based on finite-difference methods (W. Im, D. Beglov, and B. Roux, Comp Phys Commun 1998, 111, 59). Our comparisons show that the present GB model is indeed an efficient and accurate approach to reproduce corresponding PB solvation energies and forces. With only two adjustable parameters--a(0) to modulate the Coulomb field term, and a(1) to include a correction term beyond Coulomb field--the PB solvation energies are reproduced within 1% error on average for a variety of proteins. Detailed analysis shows that the PB energy can be reproduced within 2% absolute error with a confidence of about 95%. In addition, the solvent-exposed surface area of a biomolecule, as commonly used in calculations of the nonpolar solvation energy, can be calculated accurately and efficiently using the simple smoothing function and the volume integration method. Our implicit solvent GB calculations are about 4.5 times slower than the corresponding vacuum calculations. Using the simple smoothing function makes the present GB model roughly three times faster than GB models, which attempt to mimic the Lee-Richards molecular volume.

In a recent article (Lee, M. S.; Salsbury, F. R. Jr.; Brooks, C. L., III. J Chem Phys 2002, 116, 10606), we demonstrated that generalized Born (GB) theory provides a good approximation to Poisson electrostatic solvation energy calculations if one uses the same definitions of molecular volume for each. In this work, we present a new and improved analytic method for reproducing the Lee-Richards molecular volume, which is the most common volume definition for Poisson calculations. Overall, 1% errors are achieved for absolute solvation energies of a large set of proteins and relative solvation energies of protein conformations. We also introduce an accurate SASA approximation that uses the same machinery employed by our GB method and requires a small addition of computational cost. The combined methodology is shown to yield an efficient and accurate implicit solvent representation for simulations of biopolymers.

The generalized Born (GB) model is a simple continuum dielectric model for the calculation of molecular electrostatic solvation energies. It is a pairwise approximation to the solution of the Poisson equation for continuum electrostatic solvation. Key to the GB method is the calculation of Born radii for every atom in the system. We introduce two new methods for determining Born radii. The first is a two-parameter grid-based method that uses nearly the same molecular volume that is used in conventional Poisson calculations. The second is a five-parameter analytical method that utilizes a molecular volume built from a superposition of atomic functions. The analytical method, distinct from the grid-based algorithm, is amenable to force-based calculations, e.g., energy minimization and molecular dynamics. Unlike other Born radii methods, both algorithms employ a new empirically determined correction term that includes energetic effects beyond the Coulomb field approximation. With this correction term, the grid-based algorithm generally yields Born radii with greater than 0.99 correlation versus converged numerically derived Poisson Born radii. The analytical method reproduces Born radii with approximately 0.95 correlation versus Poisson-derived Born radii. With respect to absolute solvation energies, the grid-based method achieves an overall 1.3% error versus converged Poisson solutions for a set of 3029 single-chain proteins obtained from the Brookhaven Protein Data Bank. On the other hand, the analytic method delivers modest 2–4 % errors versus the Poisson solutions for the same data set. Results concerning absolute solvation energies of RNA and relative solvation energies in two sets of protein conformations are also presented.